diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..9832387 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,3 @@ +third_party/UO_Model3D_v13/model/*.blend filter=lfs diff=lfs merge=lfs -text +third_party/UO_Model3D_v13/model/*.fbx filter=lfs diff=lfs merge=lfs -text +third_party/UO_Model3D_v13/model/*.glb filter=lfs diff=lfs merge=lfs -text diff --git a/THIRD_PARTY_NOTICES.md b/THIRD_PARTY_NOTICES.md index d986475..962c833 100644 --- a/THIRD_PARTY_NOTICES.md +++ b/THIRD_PARTY_NOTICES.md @@ -1,8 +1,9 @@ # Third-party notices SpriteMotion's own code, schemas, documentation and annotations are under the -MIT license in [LICENSE](LICENSE). The repository does not bundle any -third-party software or content. The items below are dependencies you install +MIT license in [LICENSE](LICENSE). The one exception is the UO_Model3D v13 body +described below; apart from it the repository does not bundle third-party +software or content. The items below are dependencies you install yourself, or software the tools talk to. ## Contributed code @@ -14,6 +15,13 @@ scripts in `games/ultima-online/outfit-lab/` (`atlas_to_vd.py`, `uo_vd_writer.py`, `vd.py`) and `tools/vd/` were contributed by Levy and are included with his permission. +## UO_Model3D v13 + +`third_party/UO_Model3D_v13/` holds UO_Model3D v13 by Levy, shared with the +artist's permission (the model, its fitting pipeline and `vdtool`). It is not +under the MIT license. It contains no data extracted from the Ultima Online +client; see its [NOTICE](third_party/UO_Model3D_v13/NOTICE.md). + ## Runtime dependencies (installed by pip) | Package | Use | License | diff --git a/tests/integration/test_repository.py b/tests/integration/test_repository.py index 2f3e137..9068153 100644 --- a/tests/integration/test_repository.py +++ b/tests/integration/test_repository.py @@ -49,14 +49,24 @@ def test_no_game_assets_or_local_paths_are_published(): files = tracked_files() starter = REPO / 'examples/cc0-starter' approved = json.loads((starter / 'provenance.json').read_text())['files'] + model = REPO / 'third_party/UO_Model3D_v13' + model_approved = json.loads((model / 'provenance.json').read_text())['files'] for path in files: rel = path.relative_to(REPO).as_posix() assert not rel.startswith("workspace/") or rel == "workspace/README.md", rel if path.parent == starter and path.name in approved: assert path.suffix == '.glb' assert hashlib.sha256(path.read_bytes()).hexdigest() == approved[path.name]['sha256'], rel + elif rel.startswith('third_party/UO_Model3D_v13/') and rel.removeprefix('third_party/UO_Model3D_v13/') in model_approved: + data = path.read_bytes() # a git-lfs pointer carries the sha256 of the real file + pointer = re.search(rb'^oid sha256:([0-9a-f]{64})$', data, re.MULTILINE) if data.startswith(b'version https://git-lfs') else None + digest = pointer.group(1).decode() if pointer else hashlib.sha256(data).hexdigest() + assert digest == model_approved[rel.removeprefix('third_party/UO_Model3D_v13/')], rel else: assert path.suffix.lower() not in {".mul", ".uop", ".idx", ".blend", ".fbx", ".glb"}, rel + if rel.startswith('third_party/UO_Model3D_v13/'): + assert path.suffix.lower() not in {".vd", ".mul", ".uop", ".idx", ".pkl"}, f"client-derived or unsafe file: {rel}" + assert not {'client', 'extract'} & set(path.parts), rel if rel.startswith("games/") and path.suffix.lower() in {".png", ".bmp", ".gif"}: pytest.fail(f"image under games/ (game art must never be committed): {rel}") if path.suffix.lower() in {".py", ".gd", ".json", ".md", ".bat", ".toml", ".cfg", ".godot", ".tscn", diff --git a/third_party/UO_Model3D_v13/NOTICE.md b/third_party/UO_Model3D_v13/NOTICE.md new file mode 100644 index 0000000..7dda9d4 --- /dev/null +++ b/third_party/UO_Model3D_v13/NOTICE.md @@ -0,0 +1,32 @@ +# UO_Model3D v13 + +UO_Model3D v13 by Levy, shared with the artist's permission. + +A rigged 3D rebuild of the Ultima Online male body (body 0x190) with its fitting pipeline. SpriteMotion uses it as the +canonical body (rig `UO_Rig`, 112 bones after the 2026-10 weapon-bone update). Start with `README_EN.md` (English) or +`README.md` (Polish). + +## What is here + +`model/` (`.blend`, `.fbx`, `.glb`, albedo PNGs), `pipeline/`, `vdtool/`, and the two READMEs. The three model files are +stored with git LFS (`git lfs pull` after cloning). + +## What is deliberately not here + +Everything extracted from the Ultima Online client is EA data and is not published: + +- `client/` (original body and horse frames, extraction output). +- All `.vd` files (`body400.vd`, `horse200.vd`, `pipeline/body13/mul/`, the example shirt layer), the original-frame atlas + (`UO_Original_Atlas.png`, `uo_original_frames.json`), the compare GIFs and shirt preview, and fit targets built from + original silhouettes (`views_*.npz`, `horse.npz`). +- All `*.pkl` result caches (also unsafe to load from a stranger). +- The packed original-frame atlas inside the `.blend`: `model/UO_Body_0x190.blend` is the stripped copy. + +The READMEs still describe those files and the "exact modes" that need them. To use them, supply your own client: +copy your `anim1_0x0190.vd` to `pipeline/body400.vd`, then run `build_originals.py` and `pack_originals.py` as the +README says. The scripts that rebuild them stay in `pipeline/`. + +## License + +Shared with permission of the artist (Levy). `pipeline/body13/mh/` holds MakeHuman base data, which the MakeHuman +project publishes under CC0. diff --git a/third_party/UO_Model3D_v13/README.md b/third_party/UO_Model3D_v13/README.md new file mode 100644 index 0000000..b2c904c --- /dev/null +++ b/third_party/UO_Model3D_v13/README.md @@ -0,0 +1,497 @@ +# UO Body 0x190: model 3D z animacji Ultima Online + +Nagi mężczyzna (body 0x190 / 400) odtworzony w 3D z pliku animacji klienta UO `anim1_0x0190.vd`: +35 akcji × 5 kierunków, 210 klatek na kierunek, razem 1050 obrazków. Realistyczne ciało (MakeHuman, CC0) w proporcjach +postaci UO, szkielet 55 kości z palcami i łańcuchami materiału, wszystkie 35 animacji dopasowane do oryginalnych klatek. +Służy do projektowania nowych warstw ubrań, zbroi, włosów, płaszczy i broni: plik `.blend` renderuje nowe klatki UO +i od razu zapisuje je do `.vd`. + +English version: [`README_EN.md`](README_EN.md). + +**Spis treści** +1. [Zawartość](#1-zawartość) +2. [Jak działa model](#2-jak-działa-model) +3. [Modelowanie przedmiotu](#3-modelowanie-przedmiotu) +4. [Render do klatek i pliku `.vd`](#4-render-do-klatek-i-pliku-vd) +5. [Docinanie](#5-docinanie) +6. [Narzędzie `vdtool`](#6-narzędzie-vdtool) +7. [Import do gry](#7-import-do-gry) +8. [Dokładność](#8-dokładność) +9. [Jak powstał model](#9-jak-powstał-model) +10. [Odtworzenie modelu (pipeline)](#10-odtworzenie-modelu-pipeline) +11. [Ograniczenia i częste problemy](#11-ograniczenia-i-częste-problemy) + +--- + +## 1. Zawartość + +| Plik / folder | Co to jest | +|---|---| +| `UO_Body_0x190.blend` | Główny plik (Blender 4.2 – 5.2): ciało, szkielet, 35 akcji, szablony płaszcza i spódnicy, kamera UO, scena warstw ubrań, bryły konia, skrypty. | +| `UO_Body_0x190.glb` | glTF 2.0: siatka + szkielet + animacje + tekstura (Unity, Godot, three.js, Blender). | +| `UO_Body_0x190.fbx` | FBX: siatka + szkielet + animacje (Maya, 3ds Max, Unreal, Unity). | +| `UO_Body_Texture.png`, `UO_Body_Albedo_dir0..4.png` | Tekstura albedo (szara jak skóra w UO, bez światła) i jej warianty dla 5 kierunków UO. | +| `compare/*.gif` | U góry oryginalny sprite, pod spodem model wyrenderowany kamerą UO (5 kierunków). | +| `example_clothing/` | Przykładowa warstwa (koszula) w `Example_Shirt_layer.vd` i jej podgląd na oryginalnym ciele. | +| `vdtool/vdtool.py` | Narzędzie do rozpakowywania i pakowania `.vd` (rozdział 6). | +| `pipeline/` | Skrypty i dane, którymi zrekonstruowano model (rozdział 10). | +| `pipeline/body400.vd`, `pipeline/horse200.vd` | Oryginalne pliki klienta: ciało 0x190 (`anim1_0x0190.vd`) i koń 0xC8. | +| `client/body_0x190_frames/`, `client/horse_0xC8_frames/` | Oryginalne klatki ciała (1050) i konia (300) jako PNG + `meta.json` (`vdtool extract`). | + +**Oryginalne klatki.** Plik `.blend` zawiera oryginalne klatki ciała z klienta UO (do trybów dokładnych, rozdział 2). +Jest tylko do własnego użytku. Nie udostępniaj go publicznie. Kopia bez oryginałów (`strip_originals.py`) ich nie ma. Żeby je dodać +z własnego klienta: skopiuj `anim1_0x0190.vd` jako `pipeline/body400.vd`, a w `pipeline/` uruchom +`python build_originals.py` oraz `python pack_originals.py --blend ../model/UO_Body_0x190.blend`. + +## 2. Jak działa model + +**Siatka `UO_Body`** +- Realistyczne ciało na bazie MakeHuman (CC0): 13 380 wierzchołków, UV, palce, stopy z palcami, twarz. + Proporcje (grubość rąk, nóg, tułowia, głowa) dopasowane do oryginalnych klatek z ograniczeniami anatomicznymi. +- Pozycja spoczynkowa to A-pose. Jednostki to metry, postać patrzy w −Y, oś Z w górę. **Podłoga to z = 0.** +- Nie ma korekt kształtu (shape keys): sylwetkę w każdej klatce ustawiają same kości, więc przedmiot po prostu idzie + za kośćmi. + +**Szkielet `UO_Rig`** (55 kości ciała + łańcuchy materiału, sufiksy `.L`/`.R`): +- 19 kości UO: `pelvis → spine → chest → neck → head`, `chest → clavicle → upper_arm → forearm → hand`, + `pelvis → thigh → shin → foot`. `pelvis` jest korzeniem i niesie przesunięcie postaci. Obojczyki unoszą bark. +- `upper_arm_twist`, `forearm_twist` (skręt ramienia i przedramienia), 15 kości palców na dłoń (`finger1-1` … + `finger5-3`, `finger1` to kciuk), `toe` (palce stóp). Kolekcje kości: *Fingers*, *Twist*, *Toes*, *Cloth*. +- Wagi pochodzą z MakeHuman (gładkie stawy, bez „cukierków” w łokciach i barkach). +- **Grubość w klatce:** skala X/Z kości `upper_arm`, `forearm`, `hand`, `thigh`, `shin`, `foot`, `head` (Y = 1) lekko + pogrubia lub wyszczupla kończynę tam, gdzie oryginał tego wymaga. Następna kość łańcucha tej skali nie dziedziczy + (Inherit Scale = None), więc długość kończyn się nie zmienia. Przedmiot przypięty do tych kości pogrubia się razem ze skórą. +- **Palce:** w każdej klatce dłoń jest zaciśnięta tak jak na oryginale (zgięcie palców i kciuka dopasowane do klatek). +- **Łańcuchy materiału:** `skirt_K_S` (8 łańcuchów × 3 kości wokół miednicy) i `cloak_K_S` (7 × 4, z tyłu od barków). + Ich ruch dopasowano do oryginalnych klatek spódnicy (anim 449) i płaszcza (anim 468) z `anim.mul`, także na koniu. + +**Dopasowanie do klatek.** Poza każdej z 210 klatek jest dopasowana do 5 kierunków oryginału naraz (1050 obrazków), +bez żadnych korekt kształtu. Obrót prawej dłoni dopasowano dodatkowo do oryginalnych klatek katany (anim 627), więc +broń w dłoni leży jak w grze (klinga średnio co do 0,8 px). + +**Animacje.** Każda akcja UO to akcja Blendera `NN_nazwa` (z fake userem). 1 klatka UO = 3 klatki sceny (24 fps), +z płynną interpolacją. Chód i bieg są zapętlone. Właściwości akcji: `uo_action` (numer) i `uo_frames` (liczba klatek). + +| # | akcja | # | akcja | # | akcja | +|---|---|---|---|---|---| +| 0 | walk_unarmed | 12 | attack_2h_bash | 24 | mounted_run | +| 1 | walk_armed | 13 | attack_2h_slash | 25 | mounted_stand | +| 2 | run_unarmed | 14 | attack_2h_pierce | 26 | mounted_attack_1h | +| 3 | run_armed | 15 | combat_advance | 27 | mounted_attack_bow | +| 4 | stand | 16 | spell_directed | 28 | mounted_attack_crossbow | +| 5 | fidget_1 | 17 | spell_area | 29 | mounted_attack_2h | +| 6 | fidget_2 | 18 | attack_bow | 30 | block | +| 7 | combat_idle_1h | 19 | attack_crossbow | 31 | punch | +| 8 | combat_idle_2h | 20 | get_hit | 32 | bow | +| 9 | attack_1h_slash | 21 | die_forward | 33 | salute | +| 10 | attack_1h_pierce | 22 | die_backward | 34 | eat | +| 11 | attack_1h_bash | 23 | mounted_walk | | | + +Lewa i prawa strona zgadza się z oryginałem (kończyn nigdy nie zamieniano). W akcjach konnych postać siedzi w powietrzu, +bo koń jest w UO osobną animacją. + +**Kamera `UO_Camera`** patrzy dokładnie jak kamera gry. +- Rzut ortograficzny, elewacja 28,45°, 36 px/m, obraz 136×120, punkt zaczepienia w środku piksela (68, 86). Tak są zapisane oryginalne + klatki ciała. `render_uo_layer.py` renderuje na większym płótnie (`CANVAS`, domyślnie 256×256 z zaczepem (128, 192), 36 px/m bez zmian), + bo 136×120 ucina broń dwuręczną, włócznie i wysokie nakrycia głowy (rozdział 4). +- Punkt zaczepienia jest 7 cm nad podłogą (`uo_anchor_height`), bo tak wynika ze wszystkich klatek. +- Kierunek UO ustawia właściwość `uo_direction` (0–4) na `UO_Rig`: 0 przodem, 2 profilem w lewo, 4 tyłem. + Kierunki 5–7 to lustra 3–1, które robi klient. + +**Materiał i światło UO.** Światło UO (jedno, przy kamerze, prawie od przodu) wyznaczyłem z klatek i oddzieliłem od koloru ciała. +- `uo_look = 1` (domyślnie): „wygląd UO”, albedo × (0,08 otoczenia + 0,92 światła UO). Render wygląda jak klatki z gry. +- `uo_look = 0`: zwykłe PBR (Principled BSDF), do edycji i silników gier. Tej wersji używają `.glb`/`.fbx`. +- Grupa węzłów **`UO_Look`** daje to samo światło przedmiotom. Węzeł „Skin hue” opcjonalnie barwi skórę. +- **Tryby dokładne** (wymagają oryginalnych klatek w pliku i silnika Cycles): + - `EXACT_COLORS`: ciało jest „pomalowane” oryginalną klatką UO rzutowaną z kamery, więc ma dokładnie oryginalne kolory. + - `EXACT_BODY`: warstwa ciała jest identyczna z oryginałem, a w warstwie ubrania ciało zasłania przedmiot dokładnie + po oryginalnym obrysie. + +**Koń (akcje 23–29).** Kolekcja `Horse_Proxy` zawiera przybliżoną bryłę konia (body 0xC8) dla każdej klatki konnej. +Bryła decyduje, **co** jest za koniem, a **gdzie** koń jest, wyznacza dokładny obrys z jego klatek (tekst +`uo_horse_masks.json`). Dzięki temu koń zasłania jeźdźca i przedmioty co do piksela. + +**Skrypty w pliku `.blend`** (Text Editor; wybierz je z listy tekstów w nagłówku edytora): + +| Tekst | Rola | +|---|---| +| `render_uo_layer.py` | Render warstwy do klatek i `.vd` (uruchamiasz Alt+P). | +| `light_raster.py`, `light_data.py`, `light_fit.py`, `light_items.py` | Analiza światła i cieni sprite'ów UO (geometria ciała 3D na piksel, promienie do światła, dopasowania, statystyka wszystkich animacji ubieralnych). Wyniki: `docs/qa/light_shadow.md`. | +| `uo_materials.py` | Materiały obcego modelu (PBR, tekstury) → „UO look”: podpina kolor (tekstura, kolor, atrybut koloru) pod węzeł `UO_Look`, zachowuje przezroczystość (alpha ≥ 0,5 = piksel w sprite'cie), wyrzuca parametry PBR (roughness, mapy normalnych, odbicia otoczenia), ale **metal dostaje odblask w stylu UO** (zmierzony na sprite'ach napierśnika i hełmu: `SPEC_STRENGTH` 1,0 × albedo, `SPEC_POWER` 16; płyta 2,0/19, kolczuga 0,7/11, patrz `docs/qa/light_shadow.md`); `SATURATION = 0` daje szary przedmiot do farbowania w grze. Uruchom po `uo_import_item.py`. | +| `uo_import_item.py` | Wprowadza obcy model (darmowy, `.glb` `.fbx` `.obj` `.dae`…) na ciało: wypieka siatkę bez obcego szkieletu i wag, skaluje i ustawia na wysokości oryginalnego przedmiotu UO danego typu (`KIND`), wrzuca do `Clothing` (przed `uo_fit_item.py`, rozdział 3). | +| `uo_fit_item.py` | Obraca rękawy zaznaczonego przedmiotu na ręce i wypycha go ze skóry (przed `uo_bind_item.py`, rozdział 3). | +| `uo_bind_item.py` | Podpina zaznaczony przedmiot do ciała jednym uruchomieniem: parent, Armature i wagi (rozdział 3). | +| `uo_cloth_bake.py` | Symulacja tkaniny dla szat, sukni, spódnic i płaszczy, po `uo_bind_item.py` (rozdział 3). | +| `uo_shield_keys.py` | Podmienia ruch kości tarczy `shield.L` w starszym pliku na najnowszy (tarcza i jej podpięcie zostają). | +| `uo_weapon_bones.py` | Dodaje kości broni (lewa dłoń: `polearm.L`, `axe2h.L`, `bow.L`; prawa: `weapon1h.R`) i klucze ich ruchu z `weapon_motion.json` (uruchamiane już w pliku; do ponownego wgrania ruchu). | +| `uo_place_weapon.py` | Stawia zaznaczoną broń (trzon po osi +Z, czubek w górę) na linii chwytu jej klasy, przed `uo_bind_item.py`. Głowicę (ostrze, topór) modeluj jako płaską płytkę w płaszczyźnie XZ, szeroką stroną na +X; skrypt obraca broń wokół trzonu tak jak w oryginalnej broni `REF_ANIM` (np. 624 halabarda, 613 topór kata, 623 szabla), a kość kręci nią dalej wg zmierzonego rollu (`weapon_motion.json`, pole `roll`). Łuki: roll nieokreślony. | +| `weapon_roll_fit.py`, `weapon_roll_lib.py`, `weapon_roll_apply.py`, `weapon_classify.py`, `test_weapon_roll.py` | Pomiar rollu (obrotu wokół własnej osi) wszystkich oryginalnych broni z `anim`..`anim5`, klasyfikacja broni do kości, zapis do `weapon_motion.json`, test renderu płytki ze sprite'em. Wyniki: `docs/qa/weapon_roll.md`. | +| `weapon_motion.json` | Dane: chwyt (punkt, kierunek, położenie dolnego końca) i ruch 4 klas broni (3 w lewej dłoni, 1H w prawej), 210 póz każda. | +| `uo_place_shield.py` | Stawia zaznaczoną tarczę na lewym przedramieniu jak w UO i dosuwa ją do ręki (przed `uo_bind_item.py`, rozdział 3). | +| `uo_vd_writer.py` | Zapis `.vd`, używany przez render (nie uruchamiaj go ręcznie). | +| `uo_job.py` | Uruchamia długie skrypty (render, symulacja tkaniny) krok po kroku z modalnego operatora: okno Blendera nie „wiesza się” (pasek postępu na dole, ESC przerywa). Używany przez `render_uo_layer.py` i `uo_cloth_bake.py` (nie uruchamiaj go ręcznie). | +| `uo_horse_masks.json`, `uo_original_frames.json` | Dane: obrysy konia i oryginalne klatki. | + +Skrypty są w pliku `.blend`, nie w obiektach. Pracuj więc zawsze w `UO_Body_0x190.blend` (File → Open) i dołączaj +do niego swoje przedmioty, a nie odwrotnie. + +## 3. Modelowanie przedmiotu + +1. **Otwórz `UO_Body_0x190.blend`** i zezwól na skrypty: Preferences → Save & Load → *Auto Run Python Scripts* + albo „Allow Execution” w żółtym pasku. +2. **Pozycja spoczynkowa:** zaznacz `UO_Rig` → Object Data Properties (ikona ludzika) → Pose → *Rest Position*. + Modeluj na ciele w A-pose, a na koniec wróć do *Pose Position*. +3. **Dodaj przedmiot:** wymodeluj go albo zaimportuj (File → Import / Append) i wrzuć do kolekcji **`Clothing`**. + **Model z zewnątrz (np. darmowy):** ustaw w tekście **`uo_import_item.py`** `FILE` (ścieżka do `.glb`, `.fbx`, `.obj`, `.dae`…) + i `KIND` (`shirt`, `plate`, `arms`, `pants`, `legs`, `boots`, `gloves`, `helm`, `skirt`, `cloak`) i uruchom (Alt+P). Skrypt + wypieka siatkę (bez szkieletu i wag z pliku), wyrzuca z pliku wszystko poza siatką, skaluje i ustawia przedmiot tak, żeby + jego wysokość pokryła się z oryginalnym przedmiotem UO tego typu na ciele (zakresy z oryginalnych sprite'ów), i wypisuje + `PART` do `uo_bind_item.py`. Siatki w pliku są wylistowane: oczy, ciało modelu i kształty pomocnicze wyłącz przez `SKIP`. + Jeśli przedmiot patrzy tyłem, ustaw `TURN = 180`. Potem **`uo_materials.py`** (materiały obcego modelu w „UO look”; bez tego błyszczący metal + z modelu wyjdzie w renderze o ok. 55/255 inny niż światło UO; metal dostaje odblask jak w UO), `uo_fit_item.py` i `uo_bind_item.py` (punkty niżej). Sprawdź licencję + modelu. Testy: `pipeline/test_import_item.py` (obcy plik), `pipeline/test_materials.py` (materiały). + Wszystko w tej kolekcji trafia do renderowanej warstwy. `Example_Shirt` usuń albo wyłącz w renderze. +4. **Ubranie, zbroja, hełm, buty, rękawice** (rzeczy, które się uginają): skrypt **`uo_bind_item.py`**. + 1. Każdy przedmiot, który w grze jest osobny (napierśnik, naramienniki, rękawice, buty, hełm), rób jako osobny + obiekt. W klatce 136×120 px widać niewiele szczegółów, więc siatka do ok. 20 tys. wierzchołków w zupełności + wystarczy (za gęstą zmniejsz modyfikatorem *Decimate*). + 2. **Dopasowanie do ciała** (opcjonalnie, w pozycji spoczynkowej): zaznacz przedmiot i uruchom **`uo_fit_item.py`**. + Najpierw rękawy (`MATCH_ARMS`): jeśli przedmiot był robiony pod ręce ustawione inaczej (niżej, bardziej do + przodu, zgięte w łokciu), skrypt sam znajduje ten kąt i obraca rękawy na ręce postaci. Przedmioty bez rękawów + zostają bez zmian. Potem części bliżej skóry niż `MIN_GAP` (15 mm) albo w ciele zostają wypchnięte. Pchnięcie + przesuwa cały obszar wokół w jedną stronę i wygasa płynnie na max(`RADIUS` = 4 cm, `SPREAD` × pchnięcie), więc + zamiast guzów rękaw poszerza się albo przesuwa w całości, a fałdy, nity i wzory idą razem z nim. Duże ściany + podziel wcześniej (Tryb edycji, A, PPM → Pod podziel, Liczba cięć 2), bo mogą przecinać ciało między + wierzchołkami. Ponowne uruchomienie nic już nie zmienia. `MAX_GAP > 0` dodatkowo dociąga odstające miejsca + (zmienia wygląd, domyślnie wyłączone). Położenie i rozmiar ustaw sam. + 3. Zaznacz przedmiot, otwórz tekst **`uo_bind_item.py`**, ustaw `PART` (typ przedmiotu) i uruchom (Alt+P). + Każdy wierzchołek przedmiotu idzie za skórą, która leży **pod nim** (wzdłuż normalnej, `MAP = "under"`), + a wagi są wygładzane na przedmiocie (`SMOOTH = 4`). + + | `PART` | Przedmiot | Za czym idzie | + |---|---|---| + | `"chest"` | napierśnik, kamizelka, tunika | skóra pod spodem; naramiennik na barku w 80% na obojczyku, rękaw niżej na ramieniu za ręką (płynne przejście), dół w 70% za miednicą | + | `"torso"` | coś tylko na tułowiu | pelvis, spine, chest, neck | + | `"shoulders"` | naramienniki | chest, upper_arm | + | `"arms"` | rękawy, osłony ramion | upper_arm, forearm | + | `"gloves"` | rękawice, karwasze | forearm, hand | + | `"legs"` | spodnie, nagolenniki do pasa | pelvis, thigh, shin | + | `"boots"` | buty, nagolenniki | shin, foot | + | `"helm"` | hełm, kaptur, maska | head | + | `"neck"` | obojczyk zbroi, kołnierz | neck, chest, head | + | `"all"` | cała zbroja w jednym obiekcie | skóra pod spodem, wszystkie kości | + | `"robe"` | szata, suknia | góra jak skóra, od pasa w dół łańcuchy spódnicy (płynne przejście 35 cm); rękawy zawsze za rękami | + | `"skirt"` | spódnica, kilt | łańcuchy `skirt_*` (szablon `UO_Template_Skirt`) | + | `"cloak"` | płaszcz, peleryna | łańcuchy `cloak_*` + karczek na barkach (szablon `UO_Template_Cloak`) | + | `"hair"`, `"beard"`, `"hat"` | włosy, broda, czapka | sztywno na `head` (w UO włosy i brody są sztywne) | + | `"weapon1h"` | miecz, maczuga, młot, topór 1H, kryss, kilof | kość `weapon1h.R` na prawej dłoni, ruch dopasowany do 13 oryginalnych broni (0,7–1,3 px zamiast 1,4–2,1 px); najpierw `uo_place_weapon.py` z `PART = "weapon1h"` | + | `"weapon"` / `"weapon.L"` | broń bez kalibracji | sztywno na `hand.R` / `hand.L` | + | `"polearm"` (`"staff"`, `"weapon2h"`) | kij, włócznia, oszczep, widły, halabarda, berdysz, laska, kostur | kość `polearm.L` na lewej dłoni, ruch dopasowany do oryginalnych broni (0,6–1,1 px zamiast 5–6 px); najpierw `uo_place_weapon.py` | + | `"axe2h"` | topór dwuręczny, siekiera i młot w lewej dłoni | kość `axe2h.L` (jak wyżej, błąd 1,2–1,7 px) | + | `"shield"` | tarcza | sztywno na `shield.L` (kość tarczy na przedramieniu, ruch jak tarcza z UO) | + | `"bow"` / `"crossbow"` | łuk / kusza | kość `bow.L` na lewej dłoni (błąd 1,6–2,1 px zamiast 3 px) | + | `"quiver"` | kołczan | sztywno na `chest` | + + Rękawice (`"gloves"`) idą też za palcami, rękawy (`"arms"`) za kośćmi skrętu, buty (`"boots"`) za palcami stóp. + Szablony materiału (kolekcja *Templates*, niewidoczne w renderze) możesz skopiować jako bazę własnego płaszcza + albo spódnicy: kształt zmieniaj w pozycji spoczynkowej, potem `uo_bind_item.py` z `PART = "cloak"` / `"skirt"`. + + Dla `"chest"` bark ustawiasz w linii tego typu: `"upper_arm": (0.2, 0.15, 0.45)` = przy stawie 20% za ręką, + od 45% długości ramienia 100% (rękaw), pomiędzy płynnie. `"thigh": (0.3, 0.1, 0.4)` tak samo dla ud i poł. + + 4. Skrypt robi parent do `UO_Rig`, modyfikator *Armature* i wagi, więc przedmiot rusza się razem ze skórą pod nim. + Uruchom go ponownie po każdej zmianie kształtu przedmiotu (stare wagi zostaną zastąpione). + 5. Wersja ręczna (gdy chcesz własne wagi): Ctrl+P → *Armature Deform → With Empty Groups*, wagi pomaluj + albo skopiuj modyfikatorem *Data Transfer* (Vertex Groups, *Nearest Face Interpolated*) i usuń grupy kości, + których przedmiot nie zakrywa. + 6. Skóra przebijająca przedmiot o kilka mm (w podglądzie 3D) nie robi dziur w klatkach: przy renderze ciało zasłania + przedmiot dopiero wtedy, gdy jest przed nim o więcej niż `HOLDOUT_MARGIN` (1 cm, rozdział 4). + 7. **Tkanina** (opcjonalnie: szata, suknia, spódnica, płaszcz). Zaznacz podpięty przedmiot, zapisz plik i uruchom + **`uo_cloth_bake.py`**. Dół przedmiotu (to, co `uo_bind_item.py` dało na łańcuchy materiału) staje się tkaniną + Blendera: opada, buja się i odbija od ciała. Barki, pierś i rękawy zostają przypięte do szkieletu. + - `GOAL` (0,5): jak mocno materiał ciągnie do kształtu łańcuchów dopasowanych do oryginalnych klatek UO + (0 = czysta tkanina, 1 = bez tkaniny). `MATERIAL`: `silk`, `cotton`, `wool` albo `leather`. + - Każda akcja jest liczona osobno. Najpierw materiał układa się przez `PREROLL` klatek w pierwszej pozie. + Akcje zapętlone w grze (chód, bieg, stanie) są liczone `LOOP_CYCLES` razy i brany jest ostatni cykl, więc + pętla nie skacze. W akcjach konnych przeszkodą jest też koń z danej klatki (kolekcja `Horse_Proxy`). + - `CHAIN_SWING` (0,5): jak bardzo materiał idzie za rozkołysem łańcuchów z UO; mniej = spokojniejszy w szybkich + akcjach (chód bojowy, bieg). + - Po symulacji każda klatka jest sprawdzana z prawdziwym ciałem: miejsca, które weszły w skórę albo są bliżej + niż `FIX_GAP` (4 mm), są płynnie wypychane, więc skóra nie przebija przez materiał. + - Wynik trafia do `uo_cloth/.npz` obok pliku `.blend`. `render_uo_layer.py` używa go sam, a po + bake'u odtwarzanie akcji w podglądzie 3D też pokazuje tkaninę (po ponownym otwarciu pliku uruchom skrypt + z `BAKE = False`, żeby wrócił podgląd). + - Warstwy przedmiotu (płaszcz na tunice) zderzają się ze sobą (`SELF_COLLISION`), więc spodnia nie wychodzi + przez wierzchnią. + - Trwa to 30–60 minut dla wszystkich akcji (mniej: niższe `SIM_VERTS`, `QUALITY` albo tylko wybrane + `ACTIONS`). Po zmianie przedmiotu (kształt, dopasowanie, wagi) uruchom go ponownie; nieaktualny wynik jest + pomijany. `REMOVE = True` wraca do samego podpięcia. +5. **Broń, tarcza, włosy** (rzeczy sztywne): `uo_bind_item.py` z `PART = "weapon"`, `"shield"`, `"hair"` itd. + (tabela wyżej). Miecz ustaw w pozycji spoczynkowej tak, żeby rękojeść była w zaciśniętej prawej dłoni, a klinga + wychodziła po stronie kciuka: tak leży broń na oryginalnych klatkach UO. Tarczę postaw pionowo, licem do widoku z + przodu (Numpad 1), zaznacz i uruchom **`uo_place_shield.py`**: sama stanie na zewnętrznej stronie lewego + przedramienia (jak tarcza heater z UO) i dosunie się do ręki na `GAP` = 1 cm; potem `PART = "shield"`. W + renderze tarczy ustaw `BODY_GAP = 0`, żeby się nie wyginała. +6. **Materiał:** Add → Group → **`UO_Look`**, kolor lub teksturę podepnij na wejście *Albedo*. Rzeczy, które w grze mają + przyjmować kolor (hue), rób w odcieniach szarości. +7. **Sprawdź ruch:** Dope Sheet → Action Editor → wybieraj akcje `NN_nazwa` i odtwarzaj (Spacja). Widok z kamery gry: + Numpad 0, kierunek zmieniasz `uo_direction`. +8. **Wskazówki:** + - Ubranie rób ok. 1–2 cm nad skórą. + - Sprawdzaj zwłaszcza ataki, czary i upadki. + - Spódnice, szaty i płaszcze bindujesz presetami `"skirt"`, `"robe"`, `"cloak"` (idą za łańcuchami materiału), + a naturalny ruch materiału daje potem `uo_cloth_bake.py` (krok 4.7). + +## 4. Render do klatek i pliku `.vd` + +1. Silnik renderowania: **Cycles** (skrypt i tak sam go ustawi, razem z 1 próbką na piksel). +2. Otwórz tekst **`render_uo_layer.py`** i ustaw opcje na początku: + ```python + LAYER = "clothing" # "clothing" = warstwa przedmiotu, "body" = ciało, "all" = podgląd razem + CANVAS = (256, 256) # rozmiar renderu w px (szer., wys.); .vd i tak przycina każdą klatkę do zawartości + ANCHOR = (128, 192) # punkt zaczepienia w płótnie. 256×256 / (128, 192) mieści 444 z 449 animacji ludzi i ekwipunku + # klienta Nelderim (poza nim: latarnia, epolety z papugą). Stary rozmiar: (136, 120) i (68, 86) + ONLY = ["04_stand"] # test jednej akcji; [] = wszystkie 35 akcji + OUTLINE = 0.38 # ciemny kontur 1 px jak w UO (1.0 = bez konturu) + OUT_DIR = "//uo_render/" # folder obok pliku .blend + WRITE_VD = True + VD_FILE = "//uo_render/%s.vd" + HORSE_HOLDOUT = True # akcje konne: koń zasłania przedmiot + EXACT_BODY = True # docinanie po obrysie oryginalnego ciała + EXACT_COLORS = True # kolory ciała z oryginału (LAYER = "body" / "all") + HOLDOUT_MARGIN = 0.01 # ciało zasłania przedmiot, gdy jest przed nim o > 1 cm (płytkie przebicia skóry + # nie robią dziur); 0 = zwykły holdout Cycles + OCCLUDERS = [...] # części ciała, które mogą zasłaniać przedmiot: ręce, dłonie, głowa, nogi; + # tułów nigdy (przedmioty leżą na nim) + OWN_PARTS_NEVER_HIDE = True # części ciała, do których przedmiot jest oskórowany (spodnie: uda, golenie), nigdy go nie + # zasłaniają: przedmiot je okrywa, a ich skóra przed powłoką obcinała paski po bokach + TORSO_HIDE_MARGIN = 0.12 # tylko gdy noszony jest płaszcz: tułów zasłania przedmiot, gdy ten jest za nim o > 12 cm + # (płaszcz wisi za plecami, a z przodu widać tylko jego boki) + DESPECKLE = 28 # pojedyncze ciemne kropki w środku przedmiotu (głębokie detale, nity) dostają kolor + # otoczenia (0 = wył.) + FILL_HOLES = 4 # dziurki do 4 px otoczone przedmiotem są wypełniane (0 = wył.) + BODY_GAP = 0.006 # w każdej klatce części ubrania bliżej niż 6 mm rąk, dłoni, nóg lub głowy są wypychane + # na zewnątrz - ręka przebijająca rękaw w ruchu nie robi dziury (0 = wył.) + MIN_PIECE = 8 # oderwane kawałki przedmiotu mniejsze niż 8 px (brzeg kołnierza / mankietu uciętego + # przez głowę lub dłoń) są usuwane; największy kawałek zostaje zawsze (0 = wył.) + ``` +3. Uruchom **Run Script** (Alt+P). Pełna warstwa to 1050 klatek, ok. 15–30 min na CPU. Warstwa ubrania renderuje się + bez ciała, a to, co ciało zasłania, skrypt liczy z głębokości (z `HOLDOUT_MARGIN = 0` każda klatka renderuje się + dwa razy: z ciałem i bez). +4. Wynik w `uo_render/`: + - `clothing/frames/NN_akcja/dirK/NN.png`: klatki na płótnie `CANVAS` (domyślnie 256×256), + - `clothing/meta.json`: kolejność i punkt zaczepienia, + - **`clothing.vd`**: gotowy plik. + +**Render w częściach.** Kolejne przebiegi do tego samego `OUT_DIR` się sumują. Możesz np. ustawić broń pod ataki +i wyrenderować `ONLY = ["09_attack_1h_slash", ...]`, potem zmienić ułożenie i wyrenderować pozostałe akcje. Każdy przebieg +zapisuje `.vd` ze wszystkimi akcjami wyrenderowanymi do tej pory. Żeby zacząć od zera, usuń folder `uo_render/`. + +**Przerwanie renderu:** w oknie Blendera naciśnij **ESC** (postęp widać w pasku stanu na dole; okno nie zawiesza się, ale na czas +renderu blokuje inne akcje). W trybie tła (`blender -b`, moduł `bpy`) utwórz pusty plik `STOP` w folderze wyjściowym +(np. `uo_render/clothing/STOP`) albo naciśnij Ctrl+C. Gotowe klatki PNG zostają. + +**Kilka przedmiotów:** każdy renderuj osobno. W `Clothing` zostaw jeden przedmiot i zmień `VD_FILE`, np. +`"//uo_render/helm.vd"`. + +## 5. Docinanie + +- **Zasłanianie przez ciało:** warstwa ubrania zawiera tylko to, czego ciało nie zasłania, tak jak w UO. + Z `EXACT_BODY = True` granica biegnie dokładnie po obrysie oryginalnego ciała. Model 3D decyduje tylko, co jest przed, + a co za ciałem, więc przedmiot pasuje do oryginalnego ciała co do piksela. +- **Koń:** w akcjach konnych przedmiot zasłania koń, dokładnie po obrysie z jego klatek. +- **Wygląd UO:** czarne tło pod krawędziami, przezroczystość 0/1 (UO nie obsługuje półprzezroczystości) i ciemny kontur + 1 px (`OUTLINE`). +- **Przycinanie klatek:** `.vd` zapisuje każdą klatkę przyciętą do zawartości, razem z punktem zaczepienia. PNG-i mają + celowo pełne płótno, żeby klatki się pokrywały. Przycięte PNG da `vdtool extract --raw`. +- **`LAYER = "body"`:** z `EXACT_BODY = True` ciało jest identyczne z oryginałem, a z `False` to czysty model 3D + (~98% zgodności). + +## 6. Narzędzie `vdtool` + +`vdtool/vdtool.py` (Python 3.8+, `pip install pillow numpy`) rozpakowuje `.vd` do PNG i pakuje z powrotem w tej samej +kolejności (akcja → kierunek → klatka). Rozpakowanie i spakowanie bez zmian daje plik identyczny bajt w bajt. + +```bash +python vdtool.py info plik.vd # typ, akcje, liczba klatek +python vdtool.py extract plik.vd praca # -> praca/meta.json + praca/frames/NN_akcja/dirK/NN.png +python vdtool.py extract plik.vd praca --raw # klatki przycięte do zawartości +python vdtool.py pack praca nowy.vd # PNG + meta.json -> .vd +python vdtool.py verify plik.vd nowy.vd # co się zmieniło +python mul2vd.py anim.idx anim.mul wynik 701 468 # animacje z plików klienta (np. włosy 701, peleryna 468) -> .vd +``` + +- **Tryb płótna (domyślny):** wszystkie klatki mają ten sam rozmiar i wspólny punkt zaczepienia (`meta.json → anchor`). + Przy pakowaniu każda klatka jest sama przycinana, a środek wyliczany. Najlepszy do edycji i dorysowywania. +- **`--raw`:** oryginalne, przycięte rozmiary. Nie zmieniaj wymiarów ani liczby klatek, nadaje się tylko do retuszu pikseli. + +**Zasady edycji:** +1. Nie przesuwaj rysunku względem płótna: 1 px na płótnie to 1 px w grze. +2. Przezroczystość jest 0/1: alfa ≥ 128 to piksel widoczny, poniżej to przezroczysty. +3. Każdy blok (akcja + kierunek) ma jedną paletę 256 kolorów 15-bit. Przy > 256 kolorach narzędzie redukuje paletę + (median cut) i ostrzega. Czysta czerń jest zamieniana na prawie czarną, bo `0x0000` to przezroczystość. +4. Elementy barwione hue rysuj w szarości (R = G = B). +5. Klatki możesz dodawać (kolejny numer) i usuwać (od końca). Każdy z 5 kierunków akcji powinien mieć tyle samo klatek. +6. Nie zmieniaj nazw folderów ani `meta.json`. Pusta klatka jest dozwolona. + +**Format `.vd`** (little-endian): +``` +int16 magic = 6, int16 animType = 0 (high, 22 akcje) | 1 (low, 13) | 2 (people, 35) +indeks: liczba_akcji*5 wpisów {int32 lookup, int32 length, int32 extra} (-1 = brak); blok = akcja*5 + kierunek +blok: uint16 palette[256] (RGB555), int32 frameCount, int32 frameOffset[frameCount] (od pozycji frameCount) +klatka: int16 centerX, centerY; uint16 width, height; serie {uint32 header, byte pixel[header & 0xFFF]}; 0x7FFF7FFF +header: bity 22..31 = (x - centerX) & 0x3FF, bity 12..21 = (y - centerY - height) & 0x3FF, bity 0..11 = długość serii +punkt zaczepienia w klatce = (centerX, centerY + height) +``` + +## 7. Import do gry + +UOFiddler → **Animations → Animation Edit** → wybierz plik animacji i ID ciała lub przedmiotu → **Import from VD** → +wskaż plik `.vd` → zapisz (Save). Plik `.vd` musi mieć ten sam typ co cel (ciała ludzkie i ich przedmioty mają typ 2, +people). Każdy przedmiot ma osobne ID animacji. + +## 8. Dokładność + +- **Tryb dokładny (`EXACT_BODY = True`):** wyrenderowana warstwa ciała jest identyczna z oryginałem (wszystkie 1050 klatek, + sprawdzone `vdtool verify`). +- **Sam model 3D (`EXACT_BODY = False`):** średnia zgodność obrysu (IoU) **0,879** na 1050 klatkach, **bez żadnych + korekt kształtu** (same kości). Wg kierunku: 0,876–0,893. Kolory na wspólnych pikselach są dokładne z `EXACT_COLORS`. + +| # | akcja | IoU | # | akcja | IoU | # | akcja | IoU | +|---|---|---|---|---|---|---|---|---| +| 0 | walk_unarmed | 0.905 | 12 | attack_2h_bash | 0.882 | 24 | mounted_run | 0.858 | +| 1 | walk_armed | 0.901 | 13 | attack_2h_slash | 0.887 | 25 | mounted_stand | 0.853 | +| 2 | run_unarmed | 0.896 | 14 | attack_2h_pierce | 0.872 | 26 | mounted_attack_1h | 0.853 | +| 3 | run_armed | 0.896 | 15 | combat_advance | 0.881 | 27 | mounted_attack_bow | 0.865 | +| 4 | stand | 0.912 | 16 | spell_directed | 0.879 | 28 | mounted_attack_crossbow | 0.852 | +| 5 | fidget_1 | 0.909 | 17 | spell_area | 0.851 | 29 | mounted_attack_2h | 0.830 | +| 6 | fidget_2 | 0.896 | 18 | attack_bow | 0.868 | 30 | block | 0.884 | +| 7 | combat_idle_1h | 0.882 | 19 | attack_crossbow | 0.887 | 31 | punch | 0.884 | +| 8 | combat_idle_2h | 0.878 | 20 | get_hit | 0.896 | 32 | bow | 0.892 | +| 9 | attack_1h_slash | 0.860 | 21 | die_forward | 0.855 | 33 | salute | 0.902 | +| 10 | attack_1h_pierce | 0.879 | 22 | die_backward | 0.857 | 34 | eat | 0.893 | +| 11 | attack_1h_bash | 0.882 | 23 | mounted_walk | 0.859 | | | | + +Różnice to prawie wyłącznie 1-pikselowe paski wzdłuż krawędzi (oryginał rysowano innym modelem 3D). Dużych błędów, np. +ręki w innym miejscu niż na oryginale, nie ma, więc wycięcia w przedmiotach trafiają w rękę. Dla porównania: poprzedni +model bez swoich 1254 korekt miał 0,880, a z nimi 0,979 (ale przedmioty musiały kopiować te korekty). + +**Przedmioty UO.** Test na prawdziwych przedmiotach z `anim.mul` (koszula, spodnie, buty, rękawice, hełm, zbroja +płytowa): przylegające do ciała przedmioty wyrenderowane na tym modelu odtwarzają oryginalne klatki (razem z wycięciami +na ręce) tak samo dobrze jak poprzedni model z korektami. **Materiał:** spódnica IoU 0,83 (konno 0,62), płaszcz 0,73 +(konno 0,67) względem oryginalnych klatek spódnicy i płaszcza. **Broń:** klinga w dłoni średnio 0,8 px od klingi katany z UO. + +## 9. Jak powstał model + +**Obecne ciało (MakeHuman).** +1. **Kształt:** siatka MakeHuman (CC0, mężczyzna, umięśnienie 0,6) przeniesiona na szkielet UO: każda kończyna na swoją + kość (długość i obwód), tułów mapą wysokości (szerokość, głębokość na 7 poziomach), szyja i głowa osobno, przejścia + wagami MakeHuman. Grubości dopasowane do oryginalnych klatek z karą za nienaturalne kształty. +2. **Szkielet:** 19 kości UO bez zmian + skręt ramion, 15 kości palców na dłoń, palce stóp; wagi z MakeHuman. +3. **Pozy:** każda klatka dopasowana do 5 kierunków naraz (własny szybki rasteryzer + LBS jak w Blenderze), naprzemiennie + z kształtem; grubość kończyn (skala X/Z kości) i zaciśnięcie dłoni też dopasowane w każdej klatce. +4. **Dłoń i broń:** chwyt miecza skalibrowany na oryginalnych klatkach katany (anim 627), potem obrót dłoni w każdej + klatce tak, żeby klinga pokrywała się z oryginałem. Tarcza: kość `shield.L` (dziecko `forearm.L`), jej + obrót i przesunięcie dopasowane w każdej klatce do oryginalnej tarczy (anim 582) we wszystkich 5 kierunkach naraz + (IoU z oryginałem średnio 0,48 → 0,76); lico tarczy od ciała, góra do góry (dwie kary w dopasowaniu), tarcza może + odsunąć się od przedramienia, gdy ręka modelu rusza się inaczej niż tarcza UO. +5. **Konno:** jeździec widoczny tylko tam, gdzie jest przed koniem, i nie może wchodzić w bryłę konia. +6. **Materiał:** łańcuchy kości spódnicy i płaszcza dopasowane klatka po klatce do oryginalnych klatek spódnicy (449) + i płaszcza (468), z zasłanianiem przez ciało, bez przenikania nóg i konia. +7. **Tekstura:** kolory z oryginalnych klatek rzutowane na UV MakeHuman, światło UO usunięte (albedo), osobno dla + 5 kierunków. + +**Pierwsza wersja modelu** (proporcje i kamera UO wyznaczone z klatek, na nich opiera się obecne ciało): +1. **Dekodowanie `.vd`:** paleta RGB555, klatki RLE, punkt zaczepienia. +2. **Kamera UO z samych klatek:** wspólne dopasowanie proporcji ciała i kamery do obrysów z 5 kierunków dało rzut + ortograficzny, elewację 28,45°, 36 px/m, zaczepienie w środku piksela i podłogę 7 cm pod nim. +3. **Kształt:** parametryczne ciało zamienione na siatkę z czworokątów. Wierzchołki dopasowane do obrysów wszystkich klatek + (symetria, gładkość), plus „napompowanie” o 6,5 mm kompensujące bias dopasowania. +4. **Szkielet:** kości w dopasowanych stawach, wagi bone heat, obojczyki. +5. **Pozy (gradientowo, JAX):** każda klatka dopasowana na siatce ze skinningiem (LBS jak w Blenderze) w 5 kierunkach naraz. + Człony celu: + - wierzchołki w obrysie, + - każdy piksel krawędzi osiągnięty, + - limity anatomiczne (zgięcie i skręt osobno, zawiasy łokci i kolan), + - gładkość w czasie, + - kara za wejście pod podłogę. + Start jest od klatki najbliższej znanej pozie, więc bez zamiany L/P. +6. **Wyjście z minimów lokalnych:** przeszukanie wielostartowe (skręt i przechył tułowia, warianty rąk, nóg i orientacji + ciała). Wybór zawsze po prawdziwym IoU zrasteryzowanej siatki, potem wygładzenie drgań A→B→A. +7. **Koń:** bryła wizualna z 5 widoków klatek konia, bez objętości jeźdźca, przycinana dokładnym obrysem konia. +8. **Korekty na klatkę:** przesunięcia wierzchołków dopasowane regułą renderera (piksel liczy się, gdy jego środek jest + w trójkącie). Potem każdy błędny piksel przypisany do odpowiedzialnego trójkąta i korekta na kierunek. + Wszystko zapisane jako shape keys sterowane driverami. +9. **Tekstura i wygląd UO:** światło UO wyznaczone z klatek i usunięte z koloru, dające albedo. Obróbka UO + (czarne tło, alfa 0/1, kontur 0,38) zmierzona na oryginale. +10. **Tryby dokładne:** oryginalne klatki spakowane jako atlas; materiał rzutuje je z kamery UO, a skrypt renderu używa + ich obrysu przy ciele i zasłanianiu ubrań. +11. **Weryfikacja:** rig w Blenderze odtwarza dopasowaną siatkę co do < 0,1 mm, a rasteryzer zgadza się z Cycles + co do 1 piksela. + +## 10. Odtworzenie modelu (pipeline) + +**Obecne ciało** (folder `pipeline/body13/`, uruchamiane z tego folderu; wymagania: `numpy scipy numba pillow "bpy==4.2.*"`). +Zapisane wyniki (`*.json`, `*.npz`) pozwalają powtórzyć dowolny krok. Dane MakeHuman (CC0) są w `mh/`, klatki przedmiotów +UO z `anim.mul` (spódnica, płaszcz, katana, tarcza, koszula, spodnie, buty, zbroja, hełm) w `mul/`. + +| Etap | Skrypty | Wynik | +|---|---|---| +| Dane z pierwszej wersji | `prep_views.py`, `dump_poses.py`, `dump_horse.py`, `dump_v12.py` | `views_*.npz`, `rig_poses.npz`, `horse.npz` | +| Kształt | `shape13.py`, `fit_shape2.py` | `shape_r2.json` | +| Szkielet 55 kości | `skel13.py` | (w pamięci, `build_v13.py`) | +| Pozy | `run_poses13.py`, `views_from_poses13.py`, `run_mounted13.py` (+ `horse_sdf.py`) | `poses13_*.json` | +| Broń i dłoń | `weaponfit.py`, `handfit.py`, `shieldfit.py` | `grip_katana2.json`, `poses13_r5.json`, `shield_heater.json` | +| Materiał | `cloth13.py`, `clothfit.py`, `run_cloth.py`, `run_cloth_mounted.py` | `cloth_449all.json`, `cloth_468all.json` | +| Tekstura | `bake13.py` | albedo 5 kierunków | +| Budowa pliku | `build_v13.py`, potem `../export.py` | `.blend`, `.glb`, `.fbx` | +| Pomiary i podglądy | `eval13.py`, `itemval.py`, `gen_items.py`, `make_gif.py` | IoU, losowe zestawy, GIF-y | + +**Pierwsza wersja modelu** (skrypty w `pipeline/`): + +Skrypty są w `pipeline/`, uruchamia się je z tego folderu. Wymagania: Python 3.11, +`pip install numpy pillow scipy scikit-image jax optax "bpy==4.2.*"`. Pliki klienta są już w `pipeline/`: ciało +`body400.vd` i koń (0xC8) `horse200.vd`. Pliki `*.pkl` to zapisane wyniki, więc kroki można wznawiać. + +| Etap | Skrypty | Wynik | +|---|---|---| +| Proporcje i kamera | `run_shape.py` | `shape_fit.pkl` | +| Siatka, szkielet, scena | `build.py` (`basemesh.py`, `sdfmesh.py`, `rig.py`, `texbake.py`) | `.blend` | +| Kształt z klatek | `refine_mesh.py`, `inflate_test.py` | `refine_mesh.pkl`, `refine_infl.pkl` | +| Światło i tekstura | `delight_bake.py`, `perdir_bake.py` | albedo, `uo_light.pkl` | +| Pozy na siatce | `posefit_seq.py`, `posefit_search.py`, `posefit_polish.py`, `jitter_fix.py`, `reeval.py` | `final_poses_v10.pkl` | +| Koń | `horse_hull.py`, `add_horse_proxy.py` | bryły i obrysy konia | +| Budowa wersji | `patch_final.py` → `uo_layers_setup.py` → `add_horse_proxy.py` → `export.py` | `.blend`, `.glb`, `.fbx` | +| Korekty kształtu | `corr_fit.py` (etap 1), `corr_fit34.py` (piksele + kierunki), `add_exact.py` | shape keys w `.blend` | +| Tryby dokładne | `build_originals.py`, `add_exact.py`, `pack_originals.py`, `strip_originals.py` | wersja finalna | +| Pomiary | `render_body_vd.py --pure`, `compare2.py`, `err_parts.py`, `gross.py`, `zoom.py` | IoU, GIF-y | + +Ważne ustawienia: `UO_DELTA=refine_mesh.pkl` przy dopasowaniu póz, `refine_infl.pkl` przy ocenie i budowie; +`UO_CLAV=1` włącza obojczyki. + +## 11. Ograniczenia i częste problemy + +**Ograniczenia** +- Rysunek mięśni jest bardziej miękki niż na sprite'ach, bo tekstura uśrednia wiele klatek. +- Palce i twarz pochodzą z MakeHuman (na klatkach ~60 px ich nie widać). +- Sam model 3D różni się od oryginału głównie 1-pikselowymi paskami na krawędziach (ok. 12% pikseli sylwetki). + Tryby dokładne (`EXACT_BODY`) usuwają to z renderów: ciało jest zawsze oryginalne, model decyduje tylko, co jest + przed, a co za nim. +- Na koniu dolna część spódnicy i płaszcza może wchodzić w konia: przy renderze koń ją zasłania (jak w UO). +- Koń to przybliżona bryła do zasłaniania, a nie model do edycji. + +**Częste problemy** + +| Problem | Rozwiązanie | +|---|---| +| Text Editor jest pusty | Wybierz tekst z listy w nagłówku edytora. Jeśli lista jest pusta, otwórz `UO_Body_0x190.blend` przez File → Open (nie importuj `.glb`/`.fbx` i nie dołączaj ciała do innej sceny). | +| Czarne albo dziwne ciało na renderze | Włącz *Auto Run Python Scripts* i otwórz plik ponownie. Ustaw Cycles. Sprawdź `LAYER`. | +| Tryby dokładne nic nie zmieniają | W pliku nie ma oryginalnych klatek: użyj `.blend` z tego repozytorium albo `pack_originals.py`. | +| Przedmiot przebija się przez ciało | Uruchom `uo_bind_item.py` z właściwym `PART` i zrób przedmiot odrobinę większy. | +| Przedmiot rozciąga się za ręką lub nogą | Ma wagi kości, których nie zakrywa. Uruchom `uo_bind_item.py` z właściwym `PART`. | +| Blender „wisi” przy skrypcie | Przedmiot ma za dużo wierzchołków. Zmniejsz go (*Decimate*). | +| Przedmiot stoi w miejscu | Brak modyfikatora *Armature* albo wag (rozdział 3). | +| Postać „skacze” w `vdtool` | Rysunek przesunięty względem punktu zaczepienia. | +| Poszarpane krawędzie po imporcie | Półprzezroczyste piksele: ustaw alfę 0 albo 255. | +| UOFiddler odrzuca plik | Inny typ animacji niż cel (ciała ludzkie: typ 2). | +| Render trwa długo | Testuj z `ONLY = ["04_stand"]`, pełny render zrób na końcu. | diff --git a/third_party/UO_Model3D_v13/README_EN.md b/third_party/UO_Model3D_v13/README_EN.md new file mode 100644 index 0000000..89efdc7 --- /dev/null +++ b/third_party/UO_Model3D_v13/README_EN.md @@ -0,0 +1,558 @@ +# UO Body 0x190: a 3D model from Ultima Online animations + +A naked male body (body 0x190 / 400) rebuilt in 3D from the UO client animation file `anim1_0x0190.vd`: +35 actions × 5 directions, 210 frames per direction, 1050 images in total. A realistic body (MakeHuman, CC0) in the +UO character's proportions, a 55-bone rig with fingers and cloth bone chains, and all 35 animations fitted to the +original frames. It is meant for designing new clothing, armour, hair, cloak and weapon layers: the `.blend` renders +new UO frames and writes them straight into a `.vd` file. + +Polish version: [`README.md`](README.md). + +**Contents** +1. [What's included](#1-whats-included) +2. [How the model works](#2-how-the-model-works) +3. [Modelling an item](#3-modelling-an-item) +4. [Rendering frames and the `.vd` file](#4-rendering-frames-and-the-vd-file) +5. [Cutting](#5-cutting) +6. [The `vdtool` tool](#6-the-vdtool-tool) +7. [Importing into the game](#7-importing-into-the-game) +8. [Accuracy](#8-accuracy) +9. [How the model was built](#9-how-the-model-was-built) +10. [Rebuilding the model (pipeline)](#10-rebuilding-the-model-pipeline) +11. [Limitations and common problems](#11-limitations-and-common-problems) +12. [Notes for AI assistants](#12-notes-for-ai-assistants) + +--- + +## 1. What's included + +| File / folder | What it is | +|---|---| +| `UO_Body_0x190.blend` | Main file (Blender 4.2 – 5.2): body, rig, 35 actions, cloak and skirt templates, UO camera, clothing-layer scene, horse proxies, scripts. | +| `UO_Body_0x190.glb` | glTF 2.0: mesh + rig + animations + texture (Unity, Godot, three.js, Blender). | +| `UO_Body_0x190.fbx` | FBX: mesh + rig + animations (Maya, 3ds Max, Unreal, Unity). | +| `UO_Body_Texture.png`, `UO_Body_Albedo_dir0..4.png` | Albedo texture (grey like UO skin, lighting removed) and its variants for the 5 UO directions. | +| `compare/*.gif` | Top: original sprite; bottom: the model rendered through the UO camera (5 directions). | +| `example_clothing/` | Example layer (a shirt) in `Example_Shirt_layer.vd`, with a preview over the original body. | +| `vdtool/vdtool.py` | Tool to unpack and repack `.vd` files (section 6). | +| `pipeline/` | Scripts and data used to rebuild the model (section 10). | +| `pipeline/body400.vd`, `pipeline/horse200.vd` | Original client files: body 0x190 (`anim1_0x0190.vd`) and horse 0xC8. | +| `client/body_0x190_frames/`, `client/horse_0xC8_frames/` | Original body (1050) and horse (300) frames as PNG + `meta.json` (`vdtool extract`). | + +**Original frames.** The `.blend` contains the original UO client body frames (for the exact modes, +section 2). It is for your own use only; do not share it publicly. A stripped copy (`strip_originals.py`) does not contain them. +To add them from your own client: copy `anim1_0x0190.vd` to `pipeline/body400.vd`, then run +`python build_originals.py` and `python pack_originals.py --blend ../model/UO_Body_0x190.blend` in `pipeline/`. + +## 2. How the model works + +**Mesh `UO_Body`** +- A realistic body based on MakeHuman (CC0): 13,380 vertices, UVs, fingers, toes, a face. Its proportions (arm, leg and + torso girth, the head) are fitted to the original frames with anatomical constraints. +- Rest pose: A-pose. Units are metres, the character faces −Y, Z is up. **The floor is z = 0.** +- There are no shape corrections (shape keys): the bones alone set the silhouette in every frame, so an item simply + follows the bones. + +**Rig `UO_Rig`** (55 body bones + cloth chains, `.L`/`.R` suffixes): +- 19 UO bones: `pelvis → spine → chest → neck → head`, `chest → clavicle → upper_arm → forearm → hand`, + `pelvis → thigh → shin → foot`. `pelvis` is the root and carries the character's translation. Clavicles raise the shoulder. +- `upper_arm_twist`, `forearm_twist` (arm twist), 15 finger bones per hand (`finger1-1` … `finger5-3`, `finger1` is the + thumb), `toe`. Bone collections: *Fingers*, *Twist*, *Toes*, *Cloth*. +- Weights come from MakeHuman (smooth joints, no candy-wrapper elbows or shoulders). +- **Girth per frame:** the X/Z scale of `upper_arm`, `forearm`, `hand`, `thigh`, `shin`, `foot`, `head` (Y = 1) makes a + limb slightly thicker or thinner where the original needs it. The next bone of the chain does not inherit it + (Inherit Scale = None), so limb lengths do not change. Items bound to these bones get thicker with the skin. +- **Fingers:** in every frame the hand is clenched like on the original (finger and thumb curl fitted to the frames). +- **Cloth chains:** `skirt_K_S` (8 chains × 3 bones around the pelvis) and `cloak_K_S` (7 × 4, down the back from the + shoulders). Their motion is fitted to the original skirt (anim 449) and cloak (anim 468) frames from `anim.mul`, + mounted actions included. + +**Fitted to the frames.** The pose of each of the 210 frames is fitted to all 5 directions of the original at once +(1050 images), with no shape corrections. The right hand's rotation is also fitted to the original katana frames +(anim 627), so a weapon sits in the hand like in the game (the blade within 0.8 px on average). + +**Animations.** Each UO action is a Blender action `NN_name` (with a fake user). 1 UO frame = 3 scene frames (24 fps), +with smooth interpolation. Walk and run loop. Action properties: `uo_action` (number) and `uo_frames` (frame count). + +| # | action | # | action | # | action | +|---|---|---|---|---|---| +| 0 | walk_unarmed | 12 | attack_2h_bash | 24 | mounted_run | +| 1 | walk_armed | 13 | attack_2h_slash | 25 | mounted_stand | +| 2 | run_unarmed | 14 | attack_2h_pierce | 26 | mounted_attack_1h | +| 3 | run_armed | 15 | combat_advance | 27 | mounted_attack_bow | +| 4 | stand | 16 | spell_directed | 28 | mounted_attack_crossbow | +| 5 | fidget_1 | 17 | spell_area | 29 | mounted_attack_2h | +| 6 | fidget_2 | 18 | attack_bow | 30 | block | +| 7 | combat_idle_1h | 19 | attack_crossbow | 31 | punch | +| 8 | combat_idle_2h | 20 | get_hit | 32 | bow | +| 9 | attack_1h_slash | 21 | die_forward | 33 | salute | +| 10 | attack_1h_pierce | 22 | die_backward | 34 | eat | +| 11 | attack_1h_bash | 23 | mounted_walk | | | + +Left and right match the original (limbs were never swapped). In the mounted actions the rider sits in the air, +because in UO the horse is a separate animation. + +**The `UO_Camera`** sees exactly like the game camera. +- Orthographic, elevation 28.45°, 36 px/m, 136×120 image, anchor on the centre of pixel (68, 86). This is how the original body frames + are stored. `render_uo_layer.py` renders on a bigger canvas (`CANVAS`, default 256×256 with anchor (128, 192), still 36 px/m), + because 136×120 cuts off two-handed weapons, spears and tall headgear (chapter 4). +- The anchor is 7 cm above the floor (`uo_anchor_height`); all frames agree on this. +- The UO direction is the property `uo_direction` (0–4) on `UO_Rig`: 0 faces the camera, 2 is a profile facing left, + 4 faces away. Directions 5–7 are mirrors of 3–1, made by the client. + +**Material and UO lighting.** The UO light (one light at the camera, almost frontal) was estimated from the frames and +separated from the body colour. +- `uo_look = 1` (default): the "UO look", albedo × (0.08 ambient + 0.92 UO light). Renders look like the game frames. +- `uo_look = 0`: plain PBR (Principled BSDF) for editing and game engines. The `.glb`/`.fbx` use this. +- The node group **`UO_Look`** gives items the same lighting. The "Skin hue" node optionally tints the skin. +- **Exact modes** (need the original frames in the file and the Cycles engine): + - `EXACT_COLORS`: the body is painted with the original UO frame projected from the camera, so it has exactly the + original colours. + - `EXACT_BODY`: the body layer is identical to the original, and in a clothing layer the body hides the item exactly + along the original outline. + +**Horse (actions 23–29).** The `Horse_Proxy` collection holds an approximate horse volume (body 0xC8) for every mounted +frame. The volume decides **what** is behind the horse; **where** the horse is comes from the exact outline of its +frames (text `uo_horse_masks.json`). The horse therefore hides the rider and items to the pixel. + +**Scripts inside the `.blend`** (Text Editor; pick them from the text list in the editor header): + +| Text | Purpose | +|---|---| +| `render_uo_layer.py` | Renders a layer to frames and `.vd` (run with Alt+P). | +| `light_raster.py`, `light_data.py`, `light_fit.py`, `light_items.py` | Light and shadow analysis of the UO sprites (per-pixel geometry of the 3D body, rays to the light, fits, statistics of all wearable animations). Results: `docs/qa/light_shadow.md` (Polish). | +| `uo_materials.py` | Puts the materials of a foreign model (PBR, textures) into the UO look: wires the colour (texture, colour, colour attribute) into the `UO_Look` node, keeps transparency (alpha >= 0.5 = pixel in the sprite), drops PBR parameters (roughness, normal maps, environment reflections), but **metal gets a UO-style highlight** (measured on the plate and helm sprites: `SPEC_STRENGTH` 1.0 × albedo, `SPEC_POWER` 16; plate 2.0/19, mail 0.7/11, see `docs/qa/light_shadow.md`); `SATURATION = 0` gives a grey item for in-game dyeing. Run it after `uo_import_item.py`. | +| `uo_import_item.py` | Brings a foreign (e.g. free) model (`.glb` `.fbx` `.obj` `.dae`…) onto the body: bakes the mesh without the file's skeleton and weights, scales it and puts it at the height of the original UO item of that kind (`KIND`), in `Clothing` (before `uo_fit_item.py`, section 3). | +| `uo_fit_item.py` | Turns the selected item's sleeves onto the arms and pushes it out of the skin (before `uo_bind_item.py`, section 3). | +| `uo_bind_item.py` | Binds the selected item to the body in one run: parent, Armature and weights (section 3). | +| `uo_cloth_bake.py` | Cloth simulation for robes, dresses, skirts and cloaks, after `uo_bind_item.py` (section 3). | +| `uo_shield_keys.py` | Replaces the motion of the shield bone `shield.L` in an older file with the latest one (the shield and its binding stay). | +| `uo_weapon_bones.py` | Adds the weapon bones (left hand: `polearm.L`, `axe2h.L`, `bow.L`; right hand: `weapon1h.R`) and keys their motion from `weapon_motion.json` (already run in the file; to load the motion again). | +| `uo_place_weapon.py` | Puts the selected weapon (shaft along +Z, tip up) on the grip line of its class, before `uo_bind_item.py`. Model the head (blade, axe) as a flat plate in the XZ plane, wide side on +X; the script turns the weapon about its shaft like the original weapon `REF_ANIM` (e.g. 624 halberd, 613 executioner's axe, 623 cutlass) and the bone then turns it by the measured roll (`weapon_motion.json`, field `roll`). Bows: roll undetermined. | +| `weapon_roll_fit.py`, `weapon_roll_lib.py`, `weapon_roll_apply.py`, `weapon_classify.py`, `test_weapon_roll.py` | Measure the roll (turn about the weapon's own axis) of all original weapons of `anim`..`anim5`, classify weapons to bones, write into `weapon_motion.json`, render test of a plate against the sprite. Results: `docs/qa/weapon_roll.md`. | +| `weapon_motion.json` | Data: grip (point, direction, butt position) and motion of the 4 weapon classes (3 in the left hand, 1H in the right), 210 poses each. | +| `uo_place_shield.py` | Puts the selected shield on the left forearm as UO holds it and slides it onto the arm (before `uo_bind_item.py`, section 3). | +| `uo_vd_writer.py` | `.vd` writer used by the renderer (don't run it directly). | +| `uo_job.py` | Runs long scripts (render, cloth bake) step by step from a modal operator, so Blender's window does not freeze (progress in the status bar, ESC cancels). Used by `render_uo_layer.py` and `uo_cloth_bake.py` (don't run it directly). | +| `uo_horse_masks.json`, `uo_original_frames.json` | Data: horse outlines and original frames. | + +The scripts live in the `.blend` file, not in objects. Always work in `UO_Body_0x190.blend` (File → Open) and bring your +items into it, not the other way round. + +## 3. Modelling an item + +1. **Open `UO_Body_0x190.blend`** and allow scripts: Preferences → Save & Load → *Auto Run Python Scripts*, or + "Allow Execution" in the yellow bar. +2. **Rest pose:** select `UO_Rig` → Object Data Properties (stick-figure icon) → Pose → *Rest Position*. Model on the + body in the A-pose, then switch back to *Pose Position*. +3. **Add the item:** model it or import it (File → Import / Append) and put it into the **`Clothing`** collection. + **A model from outside (e.g. a free one):** in the text **`uo_import_item.py`** set `FILE` (path to a `.glb`, `.fbx`, `.obj`, + `.dae`…) and `KIND` (`shirt`, `plate`, `arms`, `pants`, `legs`, `boots`, `gloves`, `helm`, `skirt`, `cloak`) and run it + (Alt+P). It bakes the mesh (without the file's skeleton and weights), throws away everything but the mesh, scales and + places the item so that its height matches the original UO item of that kind on the body (ranges from the original + sprites), and prints the `PART` for `uo_bind_item.py`. The meshes in the file are listed: leave out eyes, the model's body + and helper shapes with `SKIP`. If the item faces backwards set `TURN = 180`. Then **`uo_materials.py`** (the foreign materials into the UO look; without it the model's shiny metal renders about 55/255 off the UO light; metal gets a UO-style highlight), `uo_fit_item.py` and `uo_bind_item.py` + (below). Check the model's licence. Tests: `pipeline/test_import_item.py` (foreign file), `pipeline/test_materials.py` (materials). + Everything in this collection goes into the rendered layer. Delete `Example_Shirt` or disable it in renders. +4. **Clothing, armour, helmet, boots, gloves** (things that bend): the script **`uo_bind_item.py`**. + 1. Make every piece that is a separate item in the game (breastplate, pauldrons, gloves, boots, helmet) a separate + object. A 136×120 px frame shows little detail, so up to about 20k vertices is plenty (reduce a dense mesh + with a *Decimate* modifier). + 2. **Fit to the body** (optional, in Rest Position): select the item and run **`uo_fit_item.py`**. First the + sleeves (`MATCH_ARMS`): if the item was made for arms held differently (lower, more forward, bent at the + elbow), the script finds that pose and turns the sleeves onto the body's arms. Items without sleeves are left + alone. Then parts closer to the skin than `MIN_GAP` (15 mm) or inside the body are pushed out. A push moves the + whole area around it the same way and fades out smoothly over max(`RADIUS` = 4 cm, `SPREAD` × the push), so a + sleeve widens or moves as a whole instead of getting bumps, and folds, rivets and reliefs go with it. Subdivide + big faces first (Edit Mode, A, right click → Subdivide, Number of Cuts 2), as they can cut through the body + between their corners. Running it again changes nothing. `MAX_GAP > 0` also pulls standing-off parts in + (changes the look, off by default). Place and size the item yourself. + 3. Select the item, open the text **`uo_bind_item.py`**, set `PART` (the kind of item) and run it (Alt+P). + Every item vertex follows the skin **right under it** (along its normal, `MAP = "under"`), and the weights + are smoothed over the item (`SMOOTH = 4`). + + | `PART` | Item | What it follows | + |---|---|---| + | `"chest"` | breastplate, vest, tunic | skin under it; pauldron on the shoulder 80% on the collarbone, sleeve further down the arm follows the arm (smooth transition), bottom 70% on the pelvis | + | `"torso"` | something on the torso only | pelvis, spine, chest, neck | + | `"shoulders"` | pauldrons | chest, upper_arm | + | `"arms"` | sleeves, arm armour | upper_arm, forearm | + | `"gloves"` | gloves, gauntlets, bracers | forearm, hand | + | `"legs"` | trousers, leg armour up to the waist | pelvis, thigh, shin | + | `"boots"` | boots, greaves | shin, foot | + | `"helm"` | helmet, hood, mask | head | + | `"neck"` | gorget, collar | neck, chest, head | + | `"all"` | full suit in one object | skin under it, every bone | + | `"robe"` | robe, dress | top like the skin, from the waist down the skirt chains (35 cm smooth transition); sleeves always follow the arms | + | `"skirt"` | skirt, kilt | the `skirt_*` chains (template `UO_Template_Skirt`) | + | `"cloak"` | cloak, cape | the `cloak_*` chains + a yoke over the shoulders (template `UO_Template_Cloak`) | + | `"hair"`, `"beard"`, `"hat"` | hair, beard, cap | rigid on `head` (UO hair and beards are rigid) | + | `"weapon1h"` | sword, mace, hammer, 1H axe, kryss, pickaxe | bone `weapon1h.R` on the right hand, motion fitted to 13 original weapons (0.7-1.3 px instead of 1.4-2.1 px); run `uo_place_weapon.py` with `PART = "weapon1h"` first | + | `"weapon"` / `"weapon.L"` | uncalibrated weapon | rigid on `hand.R` / `hand.L` | + | `"polearm"` (`"staff"`, `"weapon2h"`) | staff, spear, javelin, pitchfork, halberd, bardiche, crook | bone `polearm.L` on the left hand, motion fitted to the original weapons (0.6-1.1 px instead of 5-6 px); run `uo_place_weapon.py` first | + | `"axe2h"` | two-handed axe, hatchet / hammer in the left hand | bone `axe2h.L` (same, 1.2-1.7 px error) | + | `"shield"` | shield | rigid on `shield.L` (shield bone on the forearm, moves like the UO shield) | + | `"bow"` / `"crossbow"` | bow / crossbow | bone `bow.L` on the left hand (1.6-2.1 px error instead of 3 px) | + | `"quiver"` | quiver | rigid on `chest` | + + Gloves (`"gloves"`) also follow the fingers, sleeves (`"arms"`) the twist bones, boots (`"boots"`) the toes. + The cloth templates (collection *Templates*, hidden in renders) can be copied as a base for your own cloak or + skirt: reshape them in Rest Position, then run `uo_bind_item.py` with `PART = "cloak"` / `"skirt"`. + + For `"chest"` the shoulder is set in that type's line: `"upper_arm": (0.2, 0.15, 0.45)` = 20% on the arm at the + joint, 100% from 45% of the arm's length (the sleeve), smooth in between. `"thigh": (0.3, 0.1, 0.4)` likewise for the thighs. + + 4. The script parents the item to `UO_Rig`, adds the *Armature* modifier and sets the weights, so the item moves + with the skin under it. Run it again after every change to the item's shape (old weights are replaced). + 5. Manual way (your own weights): Ctrl+P → *Armature Deform → With Empty Groups*, paint the weights or copy them with + a *Data Transfer* modifier (Vertex Groups, *Nearest Face Interpolated*) and delete the groups of bones the item + does not cover. + 6. Skin poking a few mm through the item (in the 3D view) does not cut holes in the frames: when rendering, the body + hides the item only where it is more than `HOLDOUT_MARGIN` (1 cm, section 4) in front of it. + 7. **Cloth** (optional: robe, dress, skirt, cloak). Select the bound item, save the file and run + **`uo_cloth_bake.py`**. The lower part of the item (what `uo_bind_item.py` put on the cloth chains) becomes + Blender cloth: it falls, swings and collides with the body. Shoulders, chest and sleeves stay pinned to the + skeleton. + - `GOAL` (0.5): how strongly the cloth is pulled towards the shape of the chains fitted to the original UO + frames (0 = pure cloth, 1 = no cloth). `MATERIAL`: `silk`, `cotton`, `wool` or `leather`. + - Every action is simulated on its own. The cloth first settles for `PREROLL` frames in the first pose. + Actions the game loops (walk, run, stand) run `LOOP_CYCLES` times and the last cycle is kept, so the loop + has no jump. In the mounted actions the horse of each frame (collection `Horse_Proxy`) is an obstacle too. + - `CHAIN_SWING` (0.5): how much of the UO chains' swing the cloth follows; lower = calmer in fast actions + (war walk, run). + - After the simulation every frame is checked against the real body: parts inside the skin or closer + than `FIX_GAP` (4 mm) are pushed out smoothly, so the skin never shows through the cloth. + - The result goes to `uo_cloth/.npz` next to the `.blend`. `render_uo_layer.py` uses it automatically, + and after the bake playing an action in the 3D viewport shows the cloth too (after reopening the file run + the script with `BAKE = False` to get that preview back). + - Layers of the item (a coat over a tunic) collide with each other (`SELF_COLLISION`), so the inner one never + shows through the outer one. + - All actions take 30-60 minutes (less: lower `SIM_VERTS`, `QUALITY` or only some `ACTIONS`). Run it + again after changing the item (shape, fit, weights); an outdated bake is skipped. `REMOVE = True` goes back + to the plain bound item. +5. **Weapon, shield, hair** (rigid things): `uo_bind_item.py` with `PART = "weapon"`, `"shield"`, `"hair"` etc. (table + above). Place a sword in Rest Position with the grip inside the clenched right hand and the blade on the thumb side: + that is how weapons sit on the original UO frames. Stand a shield upright with its face towards the front view + (Numpad 1), select it and run **`uo_place_shield.py`**: it goes onto the outside of the left forearm (like the UO + heater shield) and slides onto the arm, `GAP` = 1 cm; then `PART = "shield"`. Render a shield with + `BODY_GAP = 0` so it does not bend. +6. **Material:** Add → Group → **`UO_Look`**, and plug your colour or texture into its *Albedo* input. Make anything that + should take a hue in-game in greyscale. +7. **Check the motion:** Dope Sheet → Action Editor → pick the `NN_name` actions and play (Space). Game-camera view: + Numpad 0; change the direction with `uo_direction`. +8. **Tips:** + - Make clothing about 1–2 cm above the skin. + - Check attacks, spells and deaths in particular. + - Bind skirts, robes and cloaks with the `"skirt"`, `"robe"`, `"cloak"` presets (they follow the cloth chains); + `uo_cloth_bake.py` then gives the cloth natural motion (step 4.7). + +## 4. Rendering frames and the `.vd` file + +1. Render engine: **Cycles** (the script sets it itself, with 1 sample per pixel). +2. Open the text **`render_uo_layer.py`** and set the options at the top: + ```python + LAYER = "clothing" # "clothing" = item layer, "body" = body, "all" = preview of both + CANVAS = (256, 256) # render size in px (width, height); the .vd crops every frame to its content anyway + ANCHOR = (128, 192) # anchor pixel inside the canvas. 256x256 / (128, 192) holds 444 of the 449 people and equipment + # animations of the Nelderim client (outside: a lantern, a parrot epaulet). Old size: (136, 120), (68, 86) + ONLY = ["04_stand"] # test one action; [] = all 35 actions + OUTLINE = 0.38 # dark 1-px outline like UO art (1.0 = none) + OUT_DIR = "//uo_render/" # folder next to the .blend + WRITE_VD = True + VD_FILE = "//uo_render/%s.vd" + HORSE_HOLDOUT = True # mounted actions: the horse hides the item + EXACT_BODY = True # cut along the original body outline + EXACT_COLORS = True # body colours from the original (LAYER = "body" / "all") + HOLDOUT_MARGIN = 0.01 # the body hides the item where it is > 1 cm in front of it (shallow skin pokes cut + # no holes); 0 = plain Cycles holdout + OCCLUDERS = [...] # body parts that may hide the item: arms, hands, head, legs; never the torso + # (items are worn over it) + OWN_PARTS_NEVER_HIDE = True # body parts the item is skinned to (trousers: thighs, shins) never hide it: the item wraps + # them, and their skin in front of the shell cut 1-px strips off the sides + TORSO_HIDE_MARGIN = 0.12 # only when a cloak is worn: the torso hides the item where it is > 12 cm behind it + # (a cloak hangs behind the back; from the front only its sides show) + DESPECKLE = 28 # single dark dots inside the item (deep details, rivets) take the colour around + # them (0 = off) + FILL_HOLES = 4 # holes up to 4 px fully surrounded by the item are filled (0 = off) + BODY_GAP = 0.006 # every frame, parts of the items closer than 6 mm to the arms, hands, legs or head are + # pushed out - an arm poking through a sleeve in motion cuts no hole (0 = off) + MIN_PIECE = 8 # detached bits of the item under 8 px (a collar / cuff rim cut off by the head or a + # hand) are removed; the biggest piece always stays (0 = off) + ``` +3. Run **Run Script** (Alt+P). A full layer is 1050 frames, about 15–30 minutes on a CPU. A clothing layer is rendered + without the body, and the script works out from depth what the body hides (with `HOLDOUT_MARGIN = 0` every frame + is rendered twice: with and without the body). +4. Output in `uo_render/`: + - `clothing/frames/NN_action/dirK/NN.png`: frames on a `CANVAS` canvas (256×256 by default), + - `clothing/meta.json`: frame order and anchor, + - **`clothing.vd`**: the finished file. + +**Rendering in parts.** Runs into the same `OUT_DIR` add up. For example, set the weapon up for attacks and render +`ONLY = ["09_attack_1h_slash", ...]`, then change the placement and render the other actions. Every run writes a `.vd` +with all actions rendered so far. Delete the `uo_render/` folder to start from scratch. + +**Cancelling a render:** press **ESC** in Blender's window (progress is in the status bar at the bottom; the window does not freeze, +but other input is blocked while it renders). In background mode (`blender -b`, the `bpy` module) create an empty file named `STOP` +in the output folder (e.g. `uo_render/clothing/STOP`) or press Ctrl+C. Finished PNG frames are kept. + +**Several items:** render each one separately. Keep one item in `Clothing` and change `VD_FILE`, e.g. +`"//uo_render/helm.vd"`. + +## 5. Cutting + +- **Hidden by the body:** a clothing layer contains only what the body does not hide, as in UO. With `EXACT_BODY = True` + the cut follows the outline of the original body exactly. The 3D model only decides what is in front of or behind the + body, so the item fits the original body to the pixel. +- **Horse:** in the mounted actions the horse hides the item, exactly along the outline from its frames. +- **UO look:** black under edges, 0/1 transparency (UO has no semi-transparency) and a dark 1-px outline (`OUTLINE`). +- **Cropping:** the `.vd` stores every frame cropped to its content, together with the anchor. The PNGs keep the full + canvas on purpose so frames line up. `vdtool extract --raw` gives cropped PNGs. +- **`LAYER = "body"`:** with `EXACT_BODY = True` the body is identical to the original; with `False` it is the pure + 3D model (~98% agreement). + +## 6. The `vdtool` tool + +`vdtool/vdtool.py` (Python 3.8+, `pip install pillow numpy`) unpacks a `.vd` into PNGs and packs them back in the same +order (action → direction → frame). Unpacking and repacking without changes gives a byte-identical file. Its messages +are in Polish. + +```bash +python vdtool.py info file.vd # type, actions, frame counts +python vdtool.py extract file.vd work # -> work/meta.json + work/frames/NN_action/dirK/NN.png +python vdtool.py extract file.vd work --raw # frames cropped to their content +python vdtool.py pack work new.vd # PNG + meta.json -> .vd +python vdtool.py verify file.vd new.vd # what changed +python mul2vd.py anim.idx anim.mul out 701 468 # animations from the client files (e.g. hair 701, cloak 468) -> .vd +``` + +- **Canvas mode (default):** all frames have the same size and share the anchor (`meta.json → anchor`). When packing, + each frame is cropped and its centre computed. Best for editing and drawing. +- **`--raw`:** original cropped sizes. Don't change sizes or frame counts; only for retouching pixels. + +**Editing rules:** +1. Don't move the drawing relative to the canvas: 1 px on the canvas is 1 px in the game. +2. Transparency is 0/1: alpha ≥ 128 is visible, below that it is transparent. +3. Every block (action + direction) has one palette of 256 15-bit colours. With more than 256 colours the tool reduces the + palette (median cut) and warns. Pure black becomes near-black, because `0x0000` means transparent. +4. Draw hue-able parts in grey (R = G = B). +5. You can add frames (next number) and remove them (from the end). All 5 directions of an action should have the same + number of frames. +6. Don't rename folders or edit `meta.json`. An empty frame is allowed. + +**`.vd` format** (little-endian): +``` +int16 magic = 6, int16 animType = 0 (high, 22 actions) | 1 (low, 13) | 2 (people, 35) +index: actions*5 entries {int32 lookup, int32 length, int32 extra} (-1 = empty); block = action*5 + direction +block: uint16 palette[256] (RGB555), int32 frameCount, int32 frameOffset[frameCount] (from the frameCount position) +frame: int16 centerX, centerY; uint16 width, height; runs {uint32 header, byte pixel[header & 0xFFF]}; 0x7FFF7FFF +header: bits 22..31 = (x - centerX) & 0x3FF, bits 12..21 = (y - centerY - height) & 0x3FF, bits 0..11 = run length +anchor inside the frame = (centerX, centerY + height) +``` + +## 7. Importing into the game + +UOFiddler → **Animations → Animation Edit** → pick the animation file and the body or item ID → **Import from VD** → +choose the `.vd` → Save. The `.vd` must have the same type as the target (human bodies and their items are type 2, +people). Each item has its own animation ID. + +## 8. Accuracy + +- **Exact mode (`EXACT_BODY = True`):** the rendered body layer is identical to the original (all 1050 frames, checked + with `vdtool verify`). +- **Pure 3D model (`EXACT_BODY = False`):** mean silhouette IoU **0.879** over 1050 frames, **with no shape + corrections** (bones only). By direction: 0.876–0.893. Colours on overlapping pixels are exact with `EXACT_COLORS`. + +| # | action | IoU | # | action | IoU | # | action | IoU | +|---|---|---|---|---|---|---|---|---| +| 0 | walk_unarmed | 0.905 | 12 | attack_2h_bash | 0.882 | 24 | mounted_run | 0.858 | +| 1 | walk_armed | 0.901 | 13 | attack_2h_slash | 0.887 | 25 | mounted_stand | 0.853 | +| 2 | run_unarmed | 0.896 | 14 | attack_2h_pierce | 0.872 | 26 | mounted_attack_1h | 0.853 | +| 3 | run_armed | 0.896 | 15 | combat_advance | 0.881 | 27 | mounted_attack_bow | 0.865 | +| 4 | stand | 0.912 | 16 | spell_directed | 0.879 | 28 | mounted_attack_crossbow | 0.852 | +| 5 | fidget_1 | 0.909 | 17 | spell_area | 0.851 | 29 | mounted_attack_2h | 0.830 | +| 6 | fidget_2 | 0.896 | 18 | attack_bow | 0.868 | 30 | block | 0.884 | +| 7 | combat_idle_1h | 0.882 | 19 | attack_crossbow | 0.887 | 31 | punch | 0.884 | +| 8 | combat_idle_2h | 0.878 | 20 | get_hit | 0.896 | 32 | bow | 0.892 | +| 9 | attack_1h_slash | 0.860 | 21 | die_forward | 0.855 | 33 | salute | 0.902 | +| 10 | attack_1h_pierce | 0.879 | 22 | die_backward | 0.857 | 34 | eat | 0.893 | +| 11 | attack_1h_bash | 0.882 | 23 | mounted_walk | 0.859 | | | | + +The differences are almost only 1-pixel bands along the edges (the original was drawn from a different 3D model). +There are no large errors such as an arm in a different place than on the original, so the cut-outs in items hit the +arm. For comparison: the previous model scored 0.880 without its 1254 corrections and 0.979 with them (but items had +to copy those corrections). + +**UO items.** A test on real items from `anim.mul` (shirt, trousers, boots, gloves, helmet, plate armour): body-hugging +items rendered on this model reproduce the original frames (cut-outs for the arms included) as well as the previous +model with its corrections. **Cloth:** skirt IoU 0.83 (mounted 0.62), cloak 0.73 (mounted 0.67) against the original skirt and cloak frames. +**Weapons:** the blade in the hand is 0.8 px from the UO katana blade on average. + +## 9. How the model was built + +**The current body (MakeHuman).** +1. **Shape:** the MakeHuman mesh (CC0, male, muscle 0.6) moved onto the UO skeleton: every limb onto its bone (length and + girth), the torso with a height map (width and depth at 7 levels), neck and head separately, blended with the + MakeHuman weights. Girths fitted to the original frames with a penalty on unnatural shapes. +2. **Rig:** the 19 UO bones unchanged + arm twist, 15 finger bones per hand, toes; MakeHuman weights. +3. **Poses:** every frame fitted to all 5 directions at once (own fast rasteriser + LBS like Blender's), alternating with + the shape; limb girth (bone X/Z scale) and the clench of the hands are fitted per frame too. +4. **Hand and weapon:** the sword grip calibrated on the original katana frames (anim 627), then the hand's rotation in + every frame so that the blade covers the original. The shield: bone `shield.L` (child of `forearm.L`), + its turn and shift fitted in every frame to the original shield (anim 582) in all 5 directions at once (IoU with + the original 0.48 -> 0.76 on average); its face away from the body and its top up (two penalties in the fit), + and it may move off the forearm where the model's arm moves differently from the UO shield. +5. **Mounted:** the rider is seen only where it is in front of the horse and must not enter the horse volume. +6. **Cloth:** the skirt and cloak bone chains fitted frame by frame to the original skirt (449) and cloak (468) frames, + hidden by the body, without entering the legs or the horse. +7. **Texture:** colours from the original frames projected onto the MakeHuman UVs, the UO light removed (albedo), + separately for the 5 directions. + +**The first version of the model** (UO proportions and camera found from the frames; the current body builds on them): +1. **Decoding the `.vd`:** RGB555 palette, RLE frames, anchor point. +2. **The UO camera from the frames alone:** a joint fit of body proportions and camera to the silhouettes of all + 5 directions gave an orthographic projection, elevation 28.45°, 36 px/m, the anchor on the pixel centre and the + floor 7 cm below it. +3. **Shape:** a parametric body turned into a quad mesh. Vertices fitted to the silhouettes of all frames (symmetry, + smoothness), plus a 6.5 mm inflation that compensates the fitting bias. +4. **Rig:** bones at the fitted joints, bone-heat weights, clavicles. +5. **Poses (gradient-based, JAX):** every frame fitted on the skinned mesh (LBS like Blender's) in all 5 directions at + once. Loss terms: + - vertices inside the silhouette, + - every edge pixel reached, + - anatomical limits (swing and twist separately, hinge elbows and knees), + - temporal smoothness, + - a penalty for going below the floor. + Fitting starts from the frame closest to a known pose, so limbs are never swapped. +6. **Escaping local minima:** a multi-start search (torso twist and lean, variants of arms, legs and body orientation). + Candidates are always chosen by the true IoU of the rasterised mesh, then A→B→A jitter is smoothed out. +7. **Horse:** a visual hull from the 5 views of the horse frames, without the rider's volume, clipped by the exact + horse outline. +8. **Per-frame corrections:** vertex offsets fitted with the renderer's own rule (a pixel counts when its centre is + inside a triangle). Then every wrong pixel was attached to the triangle responsible, and a per-direction correction + was added. Everything is stored as driven shape keys. +9. **Texture and UO look:** the UO light was estimated from the frames and divided out of the colour, giving the albedo. + The UO post-process (black under edges, 0/1 alpha, 0.38 outline) was measured on the original. +10. **Exact modes:** the original frames are packed as an atlas; the material projects them from the UO camera, and the + render script uses their outline for the body and for hiding clothing. +11. **Verification:** the Blender rig reproduces the fitted mesh to < 0.1 mm, and the rasteriser agrees with Cycles to + within 1 pixel. + +## 10. Rebuilding the model (pipeline) + +**The current body** (folder `pipeline/body13/`, run from that folder; requirements: `numpy scipy numba pillow "bpy==4.2.*"`). +The saved results (`*.json`, `*.npz`) let you repeat any step. The MakeHuman data (CC0) is in `mh/`, the UO item frames +from `anim.mul` (skirt, cloak, katana, shield, shirt, trousers, boots, armour, helmet) in `mul/`. + +| Stage | Scripts | Result | +|---|---|---| +| Data from the first version | `prep_views.py`, `dump_poses.py`, `dump_horse.py`, `dump_v12.py` | `views_*.npz`, `rig_poses.npz`, `horse.npz` | +| Shape | `shape13.py`, `fit_shape2.py` | `shape_r2.json` | +| 55-bone rig | `skel13.py` | (in memory, `build_v13.py`) | +| Poses | `run_poses13.py`, `views_from_poses13.py`, `run_mounted13.py` (+ `horse_sdf.py`) | `poses13_*.json` | +| Weapon and hand | `weaponfit.py`, `handfit.py`, `shieldfit.py` | `grip_katana2.json`, `poses13_r5.json`, `shield_heater.json` | +| Cloth | `cloth13.py`, `clothfit.py`, `run_cloth.py`, `run_cloth_mounted.py` | `cloth_449all.json`, `cloth_468all.json` | +| Texture | `bake13.py` | albedo for 5 directions | +| Building the file | `build_v13.py`, then `../export.py` | `.blend`, `.glb`, `.fbx` | +| Measurements and previews | `eval13.py`, `itemval.py`, `gen_items.py`, `make_gif.py` | IoU, random outfits, GIFs | + +**The first version of the model** (scripts in `pipeline/`): + +The scripts are in `pipeline/` and run from that folder. Requirements: Python 3.11, +`pip install numpy pillow scipy scikit-image jax optax "bpy==4.2.*"`. The client files are already in `pipeline/`: the +body `body400.vd` and the horse (0xC8) `horse200.vd`. The `*.pkl` files are saved results, so steps can be resumed. + +| Stage | Scripts | Result | +|---|---|---| +| Proportions and camera | `run_shape.py` | `shape_fit.pkl` | +| Mesh, rig, scene | `build.py` (`basemesh.py`, `sdfmesh.py`, `rig.py`, `texbake.py`) | `.blend` | +| Shape from the frames | `refine_mesh.py`, `inflate_test.py` | `refine_mesh.pkl`, `refine_infl.pkl` | +| Lighting and texture | `delight_bake.py`, `perdir_bake.py` | albedo, `uo_light.pkl` | +| Poses on the mesh | `posefit_seq.py`, `posefit_search.py`, `posefit_polish.py`, `jitter_fix.py`, `reeval.py` | `final_poses_v10.pkl` | +| Horse | `horse_hull.py`, `add_horse_proxy.py` | horse volumes and outlines | +| Building a version | `patch_final.py` → `uo_layers_setup.py` → `add_horse_proxy.py` → `export.py` | `.blend`, `.glb`, `.fbx` | +| Shape corrections | `corr_fit.py` (stage 1), `corr_fit34.py` (pixels + directions), `add_exact.py` | shape keys in the `.blend` | +| Exact modes | `build_originals.py`, `add_exact.py`, `pack_originals.py`, `strip_originals.py` | final version | +| Measurements | `render_body_vd.py --pure`, `compare2.py`, `err_parts.py`, `gross.py`, `zoom.py` | IoU, GIFs | + +Key settings: `UO_DELTA=refine_mesh.pkl` when fitting poses and `refine_infl.pkl` when evaluating and building; +`UO_CLAV=1` enables the clavicles. + +## 11. Limitations and common problems + +**Limitations** +- Muscle drawing is softer than on the sprites, because the texture averages many frames. +- Fingers and the face come from MakeHuman (they cannot be seen on ~60 px frames). +- The pure 3D model differs from the original mostly by 1-pixel bands along the edges (about 12% of the silhouette + pixels). The exact modes (`EXACT_BODY`) remove this from renders: the body is always the original, the model only + decides what is in front of it and what is behind. +- On horseback the lower part of a skirt or cloak may go into the horse: the horse hides it when rendering (like in UO). +- The horse is an approximate occluder, not a model for editing. + +**Common problems** + +| Problem | Fix | +|---|---| +| The Text Editor is empty | Pick a text from the list in the editor header. If the list is empty, open `UO_Body_0x190.blend` with File → Open (don't import the `.glb`/`.fbx` and don't append the body into another scene). | +| The body renders black or wrong | Enable *Auto Run Python Scripts* and reopen the file. Use Cycles. Check `LAYER`. | +| Exact modes change nothing | The file has no original frames: use the `.blend` from this repository or `pack_originals.py`. | +| The item cuts into the body | Run `uo_bind_item.py` with the right `PART`, and make the item slightly larger. | +| The item stretches after an arm or leg | It has weights of bones it does not cover. Run `uo_bind_item.py` with the right `PART`. | +| Blender freezes while the script runs | The item has too many vertices. Reduce it (*Decimate*). | +| The item stays in place | The *Armature* modifier or the weights are missing (section 3). | +| The character "jumps" in `vdtool` | The drawing moved relative to the anchor. | +| Jagged edges after import | Semi-transparent pixels: set alpha to 0 or 255. | +| UOFiddler rejects the file | Different animation type than the target (human bodies: type 2). | +| Rendering takes long | Test with `ONLY = ["04_stand"]`, and do the full render at the end. | + +## 12. Notes for AI assistants + +``` +PURPOSE : 3D model of UO body 0x190 (male, naked) rebuilt from anim1_0x0190.vd; used to author clothing layers (.vd). +VD FORMAT : see section 6. Colour 0x0000 = transparent (remap real black to 1). +SPACE : metres, Z up, character faces -Y, floor z = 0, UO anchor point = world (0, 0, 0.07). +CAMERA : "UO_Camera", orthographic, elevation 28.45 deg, 36 px/m, 136x120 px, anchor on pixel (68, 86), +0.5 px in x. +DIRECTIONS : UO_Rig["uo_direction"] = d (0..4) rotates the rig by -45 deg * d; 0 = facing camera, 2 = profile facing + left, 4 = facing away; 5..7 are mirrors of 3..1 made by the client. +RIG : 55 bones: pelvis (root) spine chest neck head; clavicle/upper_arm/forearm/hand .L/.R; thigh/shin/foot .L/.R; + upper_arm_twist/forearm_twist .L/.R; finger1-1..finger5-3 .L/.R (finger1 = thumb, local X = curl axis, + Z to the palm); toe.L/R. Cloth chains skirt_K_S (8x3, parent pelvis), cloak_K_S (7x4, parent chest). + Quaternion rotations, MakeHuman weights. Per-frame girth = pose-bone scale (x, 1, z) on upper_arm, + forearm, hand, thigh, shin, foot, head; forearm/hand/shin/foot have Inherit Scale = None. +ACTIONS : 35 Blender actions "NN_name", props uo_action (0..34) and uo_frames; UO frame i -> scene frame 1 + 3*i. + Every action keys UO_Rig["uo_action_id"]. +BODY : UO_Body = MakeHuman mesh (13380 verts, UVs), no shape keys. Items: text "uo_bind_item.py" (PART preset -> + allowed bones): nearest skin point restricted to body triangles whose dominant bone is allowed; MAP "under": + skin hit along the item vertex normal (else nearest); weights = body weights there (allowed bones only, + renormalised); SMOOTH passes of neighbour averaging over the item. Finger/twist/toe groups count as hand/ + arm/foot. RIGID presets (hair, beard, hat, weapon, shield, bow, crossbow, quiver): 100 % on one bone. + CLOTH presets (skirt, cloak, robe): weights of the nearest point of UO_Template_Skirt / UO_Template_Cloak + (robe: blended with the skin weights over 0.15 m below the template top). +HOLDOUT : clothing layer = Cycles render without the body; own z-buffer raster of body and items; the body hides a + pixel where depth_body < depth_item - HOLDOUT_MARGIN (0.01 m), using only body triangles whose dominant bone is + in OCCLUDERS (no torso); transparent patches <= FILL_HOLES px fully + surrounded by the item are filled (from the render without the body, else the neighbours' colour); + 8-connected pieces < MIN_PIECE px other than the biggest are cleared after the UO post-process. +BODY GAP : per UO frame (once for all 5 directions) the posed bound items (welded nodes) are pushed BODY_GAP out of + the posed OCCLUDERS triangles (BVH nearest, 12 rounds, displacement smoothed over the item edges) and shown + through shape key 'uo_fix' with the Armature modifier off; removed again after the run (also on STOP). +BIND FOLD : uo_bind_item PARTS[...][1] = share of a limb bone's weight kept; the rest moves to the parent bone + (hand>forearm>upper_arm>clavicle, foot>shin>thigh>pelvis, head>neck); a tuple (share, t0, t1) ramps the share along the bone; "chest" = + upper_arm (0.2, 0.15, 0.45), thigh (0.3, 0.1, 0.4). +MOUNTED : horse = body 0xC8; rider->horse action pairing 23->0, 24->1, 25..29->2. Objects Horse_a{action}_f{frame} + (holdout proxies, parented to UO_Rig) + text "uo_horse_masks.json" (key "action,frame,dir" -> + base64(zlib(packbits(120x136 bool)))). Hiding happens only inside the horse silhouette. +EXACT : image "UO_Original_Atlas" (1050 original frames, 35 cols x 30 rows of 136x120) + text + "uo_original_frames.json" (tiles; base64(zlib(RGBA)) per "action,frame,dir"); scene props uo_tile_col, + uo_tile_row, uo_exact drive the projection. Present in this repository's .blend; strip_originals.py removes them. +MATERIAL : scene["uo_look"]: 1 = albedo * (0.08 + 0.92 * max(0, N.L)), light fixed to the camera; 0 = plain PBR. +RENDERING : text "render_uo_layer.py": LAYER ("clothing" | "body" | "all"), ONLY, OUTLINE = 0.38, WRITE_VD, OUT_DIR, + VD_FILE, HORSE_HOLDOUT, EXACT_BODY, EXACT_COLORS. Cycles, 1 sample, box filter 0.01. Post-process: + premultiply over black, alpha threshold 0.5 -> 0/1, 1-px boundary outline * 0.38. Runs into the same + OUT_DIR accumulate; a file named STOP in the output folder cancels. + Output: frames/NN_action/dirK/NN.png + meta.json (vdtool layout) + .vd (anim_type 2, anchor 68,86). +QUALITY : exact mode: identical to the original body; pure model (bones only): mean silhouette IoU 0.879. +RULES : never swap left/right limbs relative to the original frames; new layers must keep the same 35 actions, + 5 directions and frame counts as the body; do not redistribute UO client files or this repository's .blend. +REBUILD : Tools/UOModel3D/pipeline (section 10); the client .vd must be copied in as body400.vd, the horse as + horse200.vd. +``` diff --git a/third_party/UO_Model3D_v13/model/UO_Body_0x190.blend b/third_party/UO_Model3D_v13/model/UO_Body_0x190.blend new file mode 100644 index 0000000..ed8579d --- /dev/null +++ b/third_party/UO_Model3D_v13/model/UO_Body_0x190.blend @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9ff8c601431157943d735b358c9a1fbcb42c713c5b618c8cb01f7ff46a8a63f4 +size 11900963 diff --git a/third_party/UO_Model3D_v13/model/UO_Body_0x190.fbx b/third_party/UO_Model3D_v13/model/UO_Body_0x190.fbx new file mode 100644 index 0000000..0aca08d --- /dev/null +++ b/third_party/UO_Model3D_v13/model/UO_Body_0x190.fbx @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5ae555aba7ce45cb52c6e37e602998a4a82ca496e224464dbfc7b348233dc9af +size 21020956 diff --git a/third_party/UO_Model3D_v13/model/UO_Body_0x190.glb b/third_party/UO_Model3D_v13/model/UO_Body_0x190.glb new file mode 100644 index 0000000..422062f --- /dev/null +++ b/third_party/UO_Model3D_v13/model/UO_Body_0x190.glb @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:802ab9f1fefbdfba135b8d69f6c756a632d4e87f25b5a8462f9274c56a6189d2 +size 6387344 diff --git a/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir0.png b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir0.png new file mode 100644 index 0000000..0afddcb Binary files /dev/null and b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir0.png differ diff --git a/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir1.png b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir1.png new file mode 100644 index 0000000..2c035a7 Binary files /dev/null and b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir1.png differ diff --git a/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir2.png b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir2.png new file mode 100644 index 0000000..6230488 Binary files /dev/null and b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir2.png differ diff --git a/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir3.png b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir3.png new file mode 100644 index 0000000..04a1588 Binary files /dev/null and b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir3.png differ diff --git a/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir4.png b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir4.png new file mode 100644 index 0000000..2a2558c Binary files /dev/null and b/third_party/UO_Model3D_v13/model/UO_Body_Albedo_dir4.png differ diff --git a/third_party/UO_Model3D_v13/model/UO_Body_Texture.png b/third_party/UO_Model3D_v13/model/UO_Body_Texture.png new file mode 100644 index 0000000..3946850 Binary files /dev/null and b/third_party/UO_Model3D_v13/model/UO_Body_Texture.png differ diff --git a/third_party/UO_Model3D_v13/pipeline/add_exact.py b/third_party/UO_Model3D_v13/pipeline/add_exact.py new file mode 100644 index 0000000..b67acfa --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/add_exact.py @@ -0,0 +1,185 @@ +"""Blender step: per-frame corrective shape keys (driven by the rig's action + frame), packed original UO frames +(atlas for the shader projection + JSON for the render script), exact-colour projection in the body material, +clothing bound with Surface Deform, new render_uo_layer.py. +usage: python add_exact.py --src out_v10/UO_Body_0x190.blend --out out_v11 --corr corr_all.pkl""" +import bpy, sys, os, pickle, json +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) +from bpy_compat import clear_fcurves, new_fcurve +import numpy as np +arg = lambda k: sys.argv[sys.argv.index(k) + 1] +SRC, OUT, CORR = arg("--src"), arg("--out"), arg("--corr") +os.makedirs(OUT, exist_ok=True) +bpy.context.preferences.filepaths.save_version = 0 +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(SRC)) +sc = bpy.context.scene +rig = bpy.data.objects["UO_Rig"]; body = bpy.data.objects["UO_Body"] +corr = pickle.load(open(CORR, "rb")) +acts = {int(a["uo_action"]): a for a in bpy.data.actions if "uo_action" in a} +CYC = {0, 1, 2, 3, 23, 24} +STEP = 3 + +# ---------------------------------------------------------------- 0) split the few concave quads (Surface Deform needs +# convex polygons); the split follows Blender's own tessellation, so renders do not change +import bmesh +rig.animation_data.action = None +me = body.data +if me.shape_keys is None: + me.calc_loop_triangles() + lt = {} + for t in me.loop_triangles: + lt.setdefault(t.polygon_index, []).append(tuple(t.vertices)) + conc = [] + for p in me.polygons: + if len(p.vertices) != 4: + continue + v = [me.vertices[k].co for k in p.vertices] + sg = [((v[(k + 1) % 4] - v[k]).cross(v[(k + 2) % 4] - v[(k + 1) % 4])).dot(p.normal) > 0 for k in range(4)] + if not all(sg): + conc.append(p.index) + bm = bmesh.new(); bm.from_mesh(me); bm.faces.ensure_lookup_table(); bm.verts.ensure_lookup_table() + uvl = bm.loops.layers.uv.active + for pi, f in [(pi, bm.faces[pi]) for pi in conc]: + uv = {l.vert.index: l[uvl].uv.copy() for l in f.loops} if uvl else {} + smooth, mi = f.smooth, f.material_index + new_faces = [] + for tri in lt[pi]: + nf = bm.faces.new([bm.verts[k] for k in tri]); nf.smooth = smooth; nf.material_index = mi + if uvl: + for l in nf.loops: l[uvl].uv = uv[l.vert.index] + new_faces.append(nf) + bm.faces.remove(f) + bm.normal_update(); bm.to_mesh(me); bm.free(); me.update() + print("split concave quads:", len(conc)) + +# ---------------------------------------------------------------- 1) corrective shape keys +# every UO action keys the rig property "uo_action_id" (constant), so the shape-key drivers know the current action +rig["uo_action_id"] = -1 +for a_, act_ in acts.items(): + clear_fcurves(act_, '["uo_action_id"]') + fc = new_fcurve(act_, '["uo_action_id"]') + kp = fc.keyframe_points.insert(1, float(a_)); kp.interpolation = "CONSTANT" +me = body.data +if me.shape_keys is None: + body.shape_key_add(name="Basis", from_mix=False) +kb = me.shape_keys.key_blocks +base = np.zeros(len(me.vertices) * 3, np.float32); kb["Basis"].data.foreach_get("co", base); base = base.reshape(-1, 3) +for k in [k for k in kb if k.name.startswith("uo_")]: + body.shape_key_remove(k) +n = 0 +for (a, i), r in sorted(corr.items()): + F = int(acts[a]["uo_frames"]) + sk = body.shape_key_add(name="uo_%02d_%02d" % (a, i), from_mix=False) + sk.data.foreach_set("co", (base + r["D"]).ravel()) + sk.slider_min, sk.slider_max = 0.0, 1.0 + d = sk.driver_add("value").driver + d.type = "SCRIPTED" + v = d.variables.new(); v.name = "ua"; v.type = "SINGLE_PROP" + v.targets[0].id_type = "OBJECT"; v.targets[0].id = rig; v.targets[0].data_path = '["uo_action_id"]' + f0 = 1 + STEP * i + e = "(ua == %d) * max(0, 1 - abs(frame - %d) / %d)" % (a, f0, STEP) + if a in CYC and i == 0 and F > 1: + e = "(ua == %d) * max(0, 1 - abs(frame - %d) / %d, 1 - abs(frame - %d) / %d)" % (a, f0, STEP, f0 + STEP * F, STEP) + d.expression = e + n += 1 + for dk, E in sorted((r.get("Ed") or {}).items()): # per-direction correction: only in UO direction dk + if float(np.abs(E).max()) < 1e-5: + continue + sk2 = body.shape_key_add(name="uo_%02d_%02d_d%d" % (a, i, dk), from_mix=False) + sk2.data.foreach_set("co", (base + E).ravel()) + sk2.slider_min, sk2.slider_max = 0.0, 1.0 + d2 = sk2.driver_add("value").driver; d2.type = "SCRIPTED" + for nm, path in (("ua", '["uo_action_id"]'), ("dd", '["uo_direction"]')): + v2 = d2.variables.new(); v2.name = nm; v2.type = "SINGLE_PROP" + v2.targets[0].id_type = "OBJECT"; v2.targets[0].id = rig; v2.targets[0].data_path = path + d2.expression = e.replace("(ua == %d)" % a, "(ua == %d) * (dd == %d)" % (a, dk), 1) + n += 1 +me.shape_keys.use_relative = True +print("shape keys", n, "simple expressions:", all(k.driver.is_simple_expression for k in me.shape_keys.animation_data.drivers)) +rig.animation_data.action = acts[4]; sc.frame_set(1) +print("check: driver valid", all(k.driver.is_valid for k in me.shape_keys.animation_data.drivers), + "stand key value", me.shape_keys.key_blocks.get("uo_04_00").value if me.shape_keys.key_blocks.get("uo_04_00") else None) +rig.animation_data.action = None + +# ---------------------------------------------------------------- 2) original frames +old = bpy.data.images.get("UO_Original_Atlas") +if old: + bpy.data.images.remove(old) +img = bpy.data.images.load(os.path.abspath("UO_Original_Atlas.png")); img.name = "UO_Original_Atlas" +img.colorspace_settings.name = "sRGB"; img.alpha_mode = "STRAIGHT"; img.pack() +meta = json.load(open("uo_original_frames.json")) +t = bpy.data.texts.get("uo_original_frames.json") or bpy.data.texts.new("uo_original_frames.json") +t.from_string(json.dumps(meta)) +sc["uo_tile_col"] = 0; sc["uo_tile_row"] = 0; sc["uo_exact"] = 1.0 + +# ---------------------------------------------------------------- 3) projection in the body material +mat = body.data.materials[0]; nt = mat.node_tree; N = nt.nodes.new; L = nt.links.new +for nd in [nd for nd in nt.nodes if nd.name.startswith("UOX_")]: + nt.nodes.remove(nd) +out = next(nd for nd in nt.nodes if nd.type == "OUTPUT_MATERIAL") +grp = next(nd for nd in nt.nodes if nd.type == "GROUP" and nd.node_tree and nd.node_tree.name == "UO_Look") + + +def node(kind, name, loc, label=None): + nd = N(kind); nd.name = "UOX_" + name; nd.location = loc; nd.label = label or name; return nd + + +def driven_value(name, prop, loc): + nd = node("ShaderNodeValue", name, loc, "scene['%s'] (driver)" % prop) + dr = nd.outputs[0].driver_add("default_value").driver; dr.type = "SCRIPTED" + v = dr.variables.new(); v.name = "p"; v.type = "SINGLE_PROP"; v.targets[0].id_type = "SCENE"; v.targets[0].id = sc + v.targets[0].data_path = '["%s"]' % prop; dr.expression = "p" + return nd + + +def math(op, name, loc, a=None, b=None): + nd = node("ShaderNodeMath", name, loc); nd.operation = op + for k_, x in enumerate((a, b)): + if x is None: continue + if isinstance(x, (int, float)): nd.inputs[k_].default_value = x + else: L(x, nd.inputs[k_]) + return nd + + +X0, Y0 = 400, -900 +tc = node("ShaderNodeTexCoord", "texco", (X0 - 1400, Y0)) +sep = node("ShaderNodeSeparateXYZ", "sep", (X0 - 1200, Y0)); L(tc.outputs["Window"], sep.inputs[0]) +col = driven_value("col", "uo_tile_col", (X0 - 1200, Y0 - 200)); row = driven_value("row", "uo_tile_row", (X0 - 1200, Y0 - 300)) +ex = driven_value("exact", "uo_exact", (X0 - 400, Y0 - 350)); lk = driven_value("look", "uo_look", (X0 - 400, Y0 - 450)) +C, R = meta["cols"], meta["rows"] +u = math("MULTIPLY", "u", (X0 - 800, Y0), math("ADD", "u0", (X0 - 1000, Y0), col.outputs[0], sep.outputs["X"]).outputs[0], 1.0 / C) +v1 = math("SUBTRACT", "v0", (X0 - 1000, Y0 - 150), sep.outputs["Y"], row.outputs[0]) +v = math("MULTIPLY", "v", (X0 - 800, Y0 - 150), math("ADD", "v1", (X0 - 900, Y0 - 150), v1.outputs[0], float(R - 1)).outputs[0], 1.0 / R) +cmb = node("ShaderNodeCombineXYZ", "uv", (X0 - 600, Y0)); L(u.outputs[0], cmb.inputs[0]); L(v.outputs[0], cmb.inputs[1]) +tex = node("ShaderNodeTexImage", "atlas", (X0 - 400, Y0), "original UO frame (projected from the UO camera)") +tex.image = img; tex.interpolation = "Closest"; tex.extension = "CLIP"; L(cmb.outputs[0], tex.inputs[0]) +em = node("ShaderNodeEmission", "emit", (X0 - 100, Y0)); L(tex.outputs["Color"], em.inputs["Color"]) +fac = math("MULTIPLY", "fac", (X0 - 100, Y0 - 300), math("MULTIPLY", "fac0", (X0 - 250, Y0 - 300), tex.outputs["Alpha"], ex.outputs[0]).outputs[0], lk.outputs[0]) +mix = node("ShaderNodeMixShader", "mix", (X0 + 150, Y0 + 300), "exact UO colours (original frames) / model") +L(fac.outputs[0], mix.inputs[0]); L(grp.outputs[0], mix.inputs[1]); L(em.outputs[0], mix.inputs[2]) +L(mix.outputs[0], out.inputs["Surface"]) + +# ---------------------------------------------------------------- 4) clothing follows the corrected body: +# Armature (as before) + the body's corrections copied onto the item (text block uo_transfer_corrections.py) +tt = bpy.data.texts.get("uo_transfer_corrections.py") or bpy.data.texts.new("uo_transfer_corrections.py") +tt.from_string(open("uo_transfer_corrections.py").read()) +tb = bpy.data.texts.get("uo_bind_item.py") or bpy.data.texts.new("uo_bind_item.py") # one-click bind (weights per body part) +tb.from_string(open("uo_bind_item.py").read()) +tf = bpy.data.texts.get("uo_fit_item.py") or bpy.data.texts.new("uo_fit_item.py") # push the item out of the skin +tf.from_string(open("uo_fit_item.py").read()) +bpy.ops.object.select_all(action="DESELECT") +for ob in (bpy.data.collections["Clothing"].all_objects if "Clothing" in bpy.data.collections else []): + if ob.type == "MESH": + for m_ in [m_ for m_ in ob.modifiers if m_.type == "SURFACE_DEFORM"]: + ob.modifiers.remove(m_) + if not any(m_.type == "ARMATURE" for m_ in ob.modifiers): + am = ob.modifiers.new("Armature", "ARMATURE"); am.object = rig + ob.select_set(True) +rig.animation_data.action = None +exec(compile(tt.as_string(), "uo_transfer_corrections.py", "exec"), {"__name__": "__main__"}) +rig.animation_data.action = acts[4] + +# ---------------------------------------------------------------- 5) render script +txt = bpy.data.texts.get("render_uo_layer.py") or bpy.data.texts.new("render_uo_layer.py") +txt.from_string(open("render_uo_layer.py").read()) +bpy.ops.wm.save_as_mainfile(filepath=os.path.abspath(os.path.join(OUT, "UO_Body_0x190.blend"))) +print("saved") diff --git a/third_party/UO_Model3D_v13/pipeline/add_horse_proxy.py b/third_party/UO_Model3D_v13/pipeline/add_horse_proxy.py new file mode 100644 index 0000000..c9be7ca --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/add_horse_proxy.py @@ -0,0 +1,70 @@ +"""Add horse proxy meshes (visual hulls of the UO horse 0xC8) to the .blend as hidden holdout objects.""" +import bpy, sys, os, pickle +import numpy as np + +SRC = sys.argv[sys.argv.index("--src") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +os.makedirs(OUT, exist_ok=True) +bpy.context.preferences.filepaths.save_version = 0 +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(SRC)) +sc = bpy.context.scene +rig = bpy.data.objects["UO_Rig"] +hulls = pickle.load(open(os.environ.get("UO_HULL_OUT", "horse_hulls.pkl"), "rb")) +LIFT = float(sc.get("uo_anchor_height", 0.0)) # the fit's coordinates have the UO anchor at z = 0 + +col = bpy.data.collections.get("Horse_Proxy") or bpy.data.collections.new("Horse_Proxy") +if col.name not in sc.collection.children: + sc.collection.children.link(col) +mat = bpy.data.materials.new("Horse_Proxy_Mat"); mat.diffuse_color = (0.45, 0.33, 0.22, 1) +for old in [o for o in bpy.data.objects if o.name.startswith("Horse_")]: + bpy.data.objects.remove(old) +for (ra, i), (v, f) in sorted(hulls.items()): + name = f"Horse_a{ra}_f{i}" + me = bpy.data.meshes.new(name) + me.from_pydata((v + np.array([0.0, 0.0, LIFT])).tolist(), [], f.tolist()); me.update() + ob = bpy.data.objects.new(name, me) + col.objects.link(ob) + bpy.context.view_layer.objects.active = ob + dec = ob.modifiers.new("Decimate", "DECIMATE"); dec.ratio = 0.06 + with bpy.context.temp_override(object=ob, active_object=ob): + bpy.ops.object.modifier_apply(modifier=dec.name) + for p in me.polygons: + p.use_smooth = True + me.materials.append(mat) + ob.parent = rig # turns with uo_direction like the rider + ob.hide_render = True + ob.hide_viewport = True + ob["uo_rider_action"] = ra; ob["uo_rider_frame"] = i + +# exact 2D horse silhouettes (from the UO horse sprites) for every mounted frame and direction: the proxy only decides +# WHAT is behind the horse, the sprite mask decides WHERE the horse is (pixel-exact edges) +import json, zlib, base64 +sys.path.insert(0, "../vdtool") +import vdtool +_, horse = vdtool.read_vd("horse200.vd") +HORSE_OF = {23: 0, 24: 1, 25: 2, 26: 2, 27: 2, 28: 2, 29: 2} +AX, AY, CW, CH = 68, 86, 136, 120 +masks = {} +for act in bpy.data.actions: + if "uo_action" not in act or int(act["uo_action"]) not in HORSE_OF: + continue + a = int(act["uo_action"]); ha = HORSE_OF[a] + for d in range(5): + blk = horse[ha * 5 + d] + for i in range(int(act["uo_frames"])): + fr = blk["frames"][i % len(blk["frames"])] + al = vdtool.frame_rgba(fr, blk["palette"])[..., 3] > 0 + m = np.zeros((CH, CW), bool) + ys, xs = np.nonzero(al) + ys, xs = ys + AY - (fr["cy"] + fr["h"]), xs + AX - fr["cx"] + ok = (ys >= 0) & (ys < CH) & (xs >= 0) & (xs < CW) + m[ys[ok], xs[ok]] = True + masks["%d,%d,%d" % (a, i, d)] = base64.b64encode(zlib.compress(np.packbits(m.ravel()).tobytes(), 9)).decode() +mt = bpy.data.texts.get("uo_horse_masks.json") or bpy.data.texts.new("uo_horse_masks.json") +mt.from_string(json.dumps(dict(format="rider_action,frame,dir -> base64(zlib(packbits(120x136 bool)))", masks=masks))) +print("horse masks", len(masks)) + +txt = bpy.data.texts.get("render_uo_layer.py") or bpy.data.texts.new("render_uo_layer.py") +txt.from_string(open("render_uo_layer.py").read()) +bpy.ops.wm.save_as_mainfile(filepath=os.path.abspath(os.path.join(OUT, "UO_Body_0x190.blend"))) +print("saved") diff --git a/third_party/UO_Model3D_v13/pipeline/bake_all.py b/third_party/UO_Model3D_v13/pipeline/bake_all.py new file mode 100644 index 0000000..2691f1b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/bake_all.py @@ -0,0 +1,120 @@ +"""Bake the UV texture from ALL non-mounted sprite frames (refined mesh + refined poses), robust weighted mean.""" +import sys, pickle, time +import numpy as np +from scipy.ndimage import binary_erosion +TEX = int(sys.argv[1]) if len(sys.argv) > 1 and sys.argv[1].isdigit() else 1024 +sys.argv = ["refine_mesh.py", "0"] +exec(open("refine_mesh.py").read().split("params = dict(delta=")[0]) +SS = 3 +r = pickle.load(open("refine_mesh.pkl", "rb")) +delta = jnp.asarray(r["delta"]) +poses = {k: jnp.asarray(v) for k, v in r["poses"].items()} +tri_uv = np.asarray(md["tri_uv"]) + + +def raster_vec(P, fn_depth, W_, H_, maxbox=24): + """Vectorised rasteriser for small triangles. P (T,3,2) pixel coords. Returns (tri, px, py, bary) of covered centres.""" + mn = np.floor(P.min(1)).astype(int); mx = np.ceil(P.max(1)).astype(int) + size = np.clip(mx - mn, 0, maxbox) + a, b, c = P[:, 0], P[:, 1], P[:, 2] + den = (b[:, 1] - c[:, 1]) * (a[:, 0] - c[:, 0]) + (c[:, 0] - b[:, 0]) * (a[:, 1] - c[:, 1]) + ok = np.abs(den) > 1e-12 + out_t, out_x, out_y, out_b = [], [], [], [] + for dy in range(int(size[:, 1].max()) + 1): + for dx in range(int(size[:, 0].max()) + 1): + sel = ok & (dx <= size[:, 0]) & (dy <= size[:, 1]) + t = np.nonzero(sel)[0] + px = mn[t, 0] + dx; py = mn[t, 1] + dy + cx, cy = px + 0.5, py + 0.5 + aa, bb, cc, dd = a[t], b[t], c[t], den[t] + l0 = ((bb[:, 1] - cc[:, 1]) * (cx - cc[:, 0]) + (cc[:, 0] - bb[:, 0]) * (cy - cc[:, 1])) / dd + l1 = ((cc[:, 1] - aa[:, 1]) * (cx - cc[:, 0]) + (aa[:, 0] - cc[:, 0]) * (cy - cc[:, 1])) / dd + l2 = 1 - l0 - l1 + m = (l0 >= -1e-4) & (l1 >= -1e-4) & (l2 >= -1e-4) & (px >= 0) & (py >= 0) & (px < W_) & (py < H_) + out_t.append(t[m]); out_x.append(px[m]); out_y.append(py[m]); out_b.append(np.stack([l0[m], l1[m], l2[m]], 1)) + return np.concatenate(out_t), np.concatenate(out_x), np.concatenate(out_y), np.concatenate(out_b) + + +# texel -> (triangle, barycentric) +t0 = time.time() +uvpx = tri_uv.copy(); uvpx[..., 0] *= TEX; uvpx[..., 1] = (1 - uvpx[..., 1]) * TEX +tt, tx, ty, tb = raster_vec(uvpx, None, TEX, TEX) +key = ty * TEX + tx +_, first = np.unique(key, return_index=True) +tt, tx, ty, tb = tt[first], tx[first], ty[first], tb[first] +NT = len(tt) +print("texels", NT, f"{time.time()-t0:.1f}s", flush=True) + +# per-view brightness gains (UO light is fixed while the body turns) +cores = np.zeros_like(masks) +for s in range(NS): + for d in range(5): + cores[s, d] = binary_erosion(masks[s, d], iterations=1) +colors = {} +for s, (a, i) in enumerate(samples): + colors[s] = cache_t[a][i][..., :3] +means = np.zeros(5) +for d in range(5): + means[d] = np.mean([colors[s][d][cores[s, d]].mean() for s in range(NS)]) +gains = means.mean() / means +print("direction gains", np.round(gains, 3), flush=True) + + +def vert_normals(X): + fn = np.cross(X[tris[:, 1]] - X[tris[:, 0]], X[tris[:, 2]] - X[tris[:, 0]]) + n = np.zeros_like(X) + for k in range(3): + np.add.at(n, tris[:, k], fn) + return n / np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12) + + +def gather(pass_mean=None, sigma=28.0): + acc = np.zeros((NT, 3)); wsum = np.zeros(NT) + for s in range(NS): + pp = {k: poses[k][s] for k in ("ball", "hinge", "trans")} + p, X = forward(delta, pp) + p = np.asarray(p); X = np.asarray(X) + nrm = vert_normals(X) + Pt = np.einsum("nk,nkd->nd", tb, X[tris[tt]]) + Nt = np.einsum("nk,nkd->nd", tb, nrm[tris[tt]]) + Nt /= np.maximum(np.linalg.norm(Nt, axis=1, keepdims=True), 1e-12) + for d in range(5): + f = np.asarray(FWD[d]); depth = X @ f + # z-buffer at SS x resolution + zb = np.full((H * SS, Wc * SS), -np.inf) + zt, zx, zy, zbc = raster_vec(p[d][tris] * SS, None, Wc * SS, H * SS) + np.maximum.at(zb, (zy, zx), np.einsum("nk,nk->n", zbc, depth[tris[zt]])) + sx = ANCHOR_X + PX_OFF + SC * (Pt @ np.asarray(RIGHT[d])) + sy = ANCHOR_Y - SC * (Pt @ np.asarray(UP[d])) + dz = Pt @ f + facing = Nt @ f + xi, yi = np.floor(sx).astype(int), np.floor(sy).astype(int) + zx_, zy_ = np.clip(np.floor(sx * SS).astype(int), 0, Wc * SS - 1), np.clip(np.floor(sy * SS).astype(int), 0, H * SS - 1) + ok = (xi >= 0) & (xi < Wc) & (yi >= 0) & (yi < H) & (facing > 0.2) + ok &= dz >= zb[zy_, zx_] - 0.015 + ok[ok] &= cores[s, d][yi[ok], xi[ok]] + if not ok.any(): + continue + col = colors[s][d][yi[ok], xi[ok]].astype(np.float64) * gains[d] + w = facing[ok] ** 2 + if pass_mean is not None: + diff = np.linalg.norm(col - pass_mean[ok], axis=1) + w = w * np.exp(-0.5 * (diff / sigma) ** 2) + acc[ok] += col * w[:, None]; wsum[ok] += w + if s % 40 == 0: + print(f" frame {s}/{NS} {time.time()-t0:.0f}s", flush=True) + mean = acc / np.maximum(wsum, 1e-9)[:, None] + return mean, wsum + + +m1, w1 = gather() +m2, w2 = gather(pass_mean=m1) +print("covered texels %.1f%%" % (100 * (w2 > 1e-6).mean()), flush=True) +tex = np.zeros((TEX, TEX, 3)); wt = np.zeros((TEX, TEX)) +tex[ty, tx] = np.clip(m2, 0, 255); wt[ty, tx] = (w2 > 1e-6) +pickle.dump(dict(tex=tex, wt=wt, cover=np.zeros((TEX, TEX), bool)), open("bake_all.pkl", "wb")) +from texbake import pull_push_fill +from PIL import Image +filled = pull_push_fill(tex, wt) +Image.fromarray(np.clip(filled, 0, 255).astype(np.uint8)).save("UO_Body_Texture_allframes.png") +print("saved texture", f"{time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/basemesh.py b/third_party/UO_Model3D_v13/pipeline/basemesh.py new file mode 100644 index 0000000..ce5097a --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/basemesh.py @@ -0,0 +1,221 @@ +"""Quad base mesh: Blender Skin modifier on the fitted skeleton, subdivided, then projected onto the body SDF.""" +import numpy as np +import bpy +from body import JI, ARM_REST_ANGLE +from sdfmesh import body_parts, body_sdf + + +def surface_dist(parts, p, d, tmax=0.6, iters=30): + """Distance from interior point p along unit direction d to the SDF surface (bisection).""" + if body_sdf(parts, p[None])[0][0] > 0: + return 0.01 + lo, hi = 0.0, tmax + for _ in range(iters): + mid = 0.5 * (lo + hi) + if body_sdf(parts, (p + d * mid)[None])[0][0] < 0: + lo = mid + else: + hi = mid + return lo + + +def measured_radius(parts, p, axis_dir): + """(r_u, r_v) half-extents of the cross-section at p, perpendicular to axis_dir (u ~ sideways, v ~ Y).""" + a = axis_dir / np.linalg.norm(axis_dir) + u = np.cross(a, [0.0, 1.0, 0.0]) + if np.linalg.norm(u) < 1e-6: + u = np.array([1.0, 0, 0]) + u /= np.linalg.norm(u) + v = np.cross(u, a) + ru = 0.5 * (surface_dist(parts, p, u) + surface_dist(parts, p, -u)) + rv = 0.5 * (surface_dist(parts, p, v) + surface_dist(parts, p, -v)) + # centre offsets (the skeleton may not be at the middle of the cross-section) + cu = 0.5 * (surface_dist(parts, p, u) - surface_dist(parts, p, -u)) + cv = 0.5 * (surface_dist(parts, p, v) - surface_dist(parts, p, -v)) + return ru, rv, p + u * cu + v * cv + + +def skin_graph(S, P, parts=None): + S = {k: np.asarray(v, np.float64) for k, v in S.items()} + sa, ca = np.sin(ARM_REST_ANGLE), np.cos(ARM_REST_ANGLE) + V, E, Rd = [], [], [] + + def add(p, r, parent=None): + V.append(np.asarray(p, float)); Rd.append(r) + i = len(V) - 1 + if parent is not None: + E.append((parent, i)) + return i + + pel, sp, ch, nk, hd = (P[JI[n]] for n in ("pelvis", "spine", "chest", "neck", "head")) + pr, ar, cr, hr = S["pelvis_r"], S["abd_r"], S["chest_r"], S["head_r"] + root = add(pel + np.array([0, 0, -0.03]), (pr[0] * 0.8, pr[1] * 0.8)) + i_p2 = add((pel + sp) / 2 + np.array([0, 0, 0.02]), (pr[0] * 0.8, pr[1] * 0.8), root) + i_sp = add(sp + np.array([0, 0, S["abd"] * 0.35]), (ar[0] * 0.85, ar[1] * 0.85), i_p2) + i_ch = add(ch + np.array([0, 0, 0.03]), (cr[0] * 0.8, cr[1] * 0.8), i_sp) + i_ct = add(ch + np.array([0, 0, S["chest_len"] * 0.8]), (cr[0] * 0.7, cr[1] * 0.7), i_ch) + i_nk = add(nk + np.array([0, 0, 0.03]), (S["neck_r"], S["neck_r"]), i_ct) + i_hd = add(hd + S["head_c"] * np.array([1, 1, 0.3]), (hr[0] * 0.9, hr[1] * 0.9), i_nk) + i_ht = add(hd + S["head_c"] + np.array([0, 0, hr[2] * 0.85]), (hr[0] * 0.6, hr[1] * 0.6), i_hd) + for side, sx in (("L", 1), ("R", -1)): + d = np.array([sx * sa, 0, -ca]) + sh, el, wr = P[JI["shoulder." + side]], P[JI["elbow." + side]], P[JI["wrist." + side]] + i_s = add(sh, (S["uarm_r"][0], S["uarm_r"][0]), i_ct) + i_m = add((sh + el) / 2, (S["uarm_r"].mean(), S["uarm_r"].mean()), i_s) + i_e = add(el, (S["uarm_r"][1], S["uarm_r"][1]), i_m) + i_f = add((el + wr) / 2, (S["farm_r"].mean(), S["farm_r"].mean()), i_e) + i_w = add(wr, (S["farm_r"][1], S["farm_r"][1]), i_f) + i_h = add(wr + d * S["hand"] * 0.9, (S["hand_r"][0] * 0.8, S["hand_r"][1] * 0.8), i_w) + hp, kn, an = P[JI["hip." + side]], P[JI["knee." + side]], P[JI["ankle." + side]] + i_hp = add(hp + np.array([0, 0, -0.02]), (S["thigh_r"][0], S["thigh_r"][0]), root) + i_tm = add((hp + kn) / 2, (S["thigh_r"].mean(), S["thigh_r"].mean()), i_hp) + i_k = add(kn, (S["thigh_r"][1], S["thigh_r"][1]), i_tm) + i_sm = add((kn + an) / 2, (S["shin_r"].mean(), S["shin_r"].mean()), i_k) + i_a = add(an, (S["shin_r"][1], S["shin_r"][1]), i_sm) + toe = an + np.array([0, -S["foot_len"] + S["heel_y"] + 0.02, -S["ankle_h"] + S["foot_r"][1]]) + add(toe, (S["foot_r"][1], S["foot_r"][1] * 0.8), i_a) + V = np.array(V) + if parts is not None: + # replace guessed radii by cross-sections measured on the fitted body surface + nb = {i: [] for i in range(len(V))} + for a_, b_ in E: + nb[a_].append(b_); nb[b_].append(a_) + centred = V.copy() + for i in range(len(V)): + axis = np.zeros(3) + for j in nb[i]: + dvec = V[j] - V[i] if j > i else V[i] - V[j] + axis += dvec / np.linalg.norm(dvec) + ru, rv, c = measured_radius(parts, V[i], axis) + if len(nb[i]) <= 1: # chain ends sit inside the tip; keep them small + ru, rv = ru * 0.6, rv * 0.6 + Rd[i] = (max(ru, 0.012), max(rv, 0.012)) + if len(nb[i]) == 2: + centred[i] = c + centred[:, 0] = np.where(np.abs(V[:, 0]) < 1e-9, 0.0, centred[:, 0]) + V = centred + return V, E, Rd, root + + +def make_skin_mesh(S, P, subdiv=2, parts=None): + V, E, Rd, root = skin_graph(S, P, parts) + me = bpy.data.meshes.new("SkinGraph") + me.from_pydata(V.tolist(), E, []) + ob = bpy.data.objects.new("SkinGraph", me) + bpy.context.scene.collection.objects.link(ob) + sk = ob.modifiers.new("Skin", "SKIN") + if len(me.skin_vertices) == 0: + me.skin_vertices.new() + sv = me.skin_vertices[0].data + for i, r in enumerate(Rd): + sv[i].radius = r + sv[i].use_root = (i == root) + sk.branch_smoothing = 0.5 + sk.use_x_symmetry = True + sub = ob.modifiers.new("Sub", "SUBSURF") + sub.levels = subdiv + sub.render_levels = subdiv + dg = bpy.context.evaluated_depsgraph_get() + ev = ob.evaluated_get(dg) + m = ev.to_mesh() + verts = np.array([v.co[:] for v in m.vertices]) + faces = [list(p.vertices) for p in m.polygons] + ev.to_mesh_clear() + bpy.data.objects.remove(ob) + bpy.data.meshes.remove(me) + return verts, faces + + +def sdf_grad(parts, p, h=1e-4): + g = np.zeros_like(p) + for i in range(3): + e = np.zeros(3); e[i] = h + g[:, i] = (body_sdf(parts, p + e)[0] - body_sdf(parts, p - e)[0]) / (2 * h) + return g + + +def project(parts, p, iters=6): + for _ in range(iters): + d, _ = body_sdf(parts, p) + g = sdf_grad(parts, p) + g /= np.maximum(np.linalg.norm(g, axis=1, keepdims=True), 1e-9) + p = p - d[:, None] * g + return p + + +def adjacency(nv, faces): + import scipy.sparse as sp + e = set() + for f in faces: + for a, b in zip(f, f[1:] + f[:1]): + e.add((min(a, b), max(a, b))) + e = np.array(sorted(e)) + A = sp.coo_matrix((np.ones(len(e) * 2), (np.r_[e[:, 0], e[:, 1]], np.r_[e[:, 1], e[:, 0]])), shape=(nv, nv)).tocsr() + deg = np.asarray(A.sum(1)).ravel() + return A, deg + + +def mesh_normals(v, faces): + n = np.zeros_like(v) + for f in faces: + for k in range(1, len(f) - 1): + a, b, c = v[f[0]], v[f[k]], v[f[k + 1]] + fn = np.cross(b - a, c - a) + for i in (f[0], f[k], f[k + 1]): + n[i] += fn + return n / np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12) + + +def project_along_normals(parts, v, n, reach=0.12, iters=25): + """Move each vertex along its normal to the SDF zero crossing (bisection); fallback: nearest point.""" + d0, _ = body_sdf(parts, v) + sgn = np.sign(d0) # outside -> search inward (-n), inside -> outward (+n) + dirn = -sgn[:, None] * n + far = v + dirn * reach + df, _ = body_sdf(parts, far) + ok = np.sign(df) != sgn + lo = np.zeros(len(v)); hi = np.full(len(v), reach) + for _ in range(iters): + mid = 0.5 * (lo + hi) + dm, _ = body_sdf(parts, v + dirn * mid[:, None]) + same = np.sign(dm) == sgn + lo = np.where(same, mid, lo); hi = np.where(same, hi, mid) + out = v + dirn * (0.5 * (lo + hi))[:, None] + out[~ok] = project(parts, v[~ok]) + return out + + +def relax_project(parts, v, faces, rounds=12, lam=0.5): + A, deg = adjacency(len(v), faces) + v = project_along_normals(parts, v, mesh_normals(v, faces)) + for _ in range(rounds): + avg = np.where(deg[:, None] > 0, (A @ v) / np.maximum(deg, 1)[:, None], v) + g = sdf_grad(parts, v) + g /= np.maximum(np.linalg.norm(g, axis=1, keepdims=True), 1e-9) + delta = avg - v + delta -= np.sum(delta * g, 1, keepdims=True) * g # tangential only + v = v + lam * delta + v = project(parts, v, iters=3) + return v + + +def symmetrize(v, tol=1e-3): + """Snap to exact X symmetry: find mirror partners and average.""" + from scipy.spatial import cKDTree + t = cKDTree(v) + m = v * np.array([-1, 1, 1]) + d, idx = t.query(m) + ok = d < 0.01 + out = v.copy() + out[ok] = 0.5 * (v[ok] + (v[idx[ok]] * np.array([-1, 1, 1]))) + center = np.abs(out[:, 0]) < tol + out[center, 0] = 0.0 + return out, idx, ok + + +def build_base_mesh(S, subdiv=2): + parts, P = body_parts(S) + verts, faces = make_skin_mesh(S, P, subdiv) + v = relax_project(parts, verts, faces) + v, _, _ = symmetrize(v) + return v, faces, parts, P diff --git a/third_party/UO_Model3D_v13/pipeline/below.py b/third_party/UO_Model3D_v13/pipeline/below.py new file mode 100644 index 0000000..40a95bc --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/below.py @@ -0,0 +1,13 @@ +import sys,pickle,numpy as np,jax.numpy as jnp +from posefit_mesh import * +from posefit_mesh import _posed_j +P=pickle.load(open(sys.argv[1],"rb")) +Wn=np.asarray(md["W"]); bones=md["bones"] +for a in [int(x) for x in sys.argv[2].split(",")]: + p=P[a]["poses"] + for i in range(p["trans"].shape[0]): + X=np.asarray(_posed_j({k:jnp.asarray(v[i]) for k,v in p.items()})) + b=X[:,2] express camera basis in character space (rotate by -yaw) + c, s = np.cos(-yaw), np.sin(-yaw) + Rz = jnp.array([[c, -s, 0], [s, c, 0], [0, 0, 1.0]], dtype=jnp.float32) + return Rz @ right_w, Rz @ up_w + + +_yy, _xx = np.mgrid[0:CANVAS_H, 0:CANVAS_W].astype(np.float32) +PIX = jnp.asarray(np.stack([_xx + 0.5 - ANCHOR_X, -(_yy + 0.5 - ANCHOR_Y)], -1)) # screen coords, y up, px + + +def render_sil(S, P, R, d, tau=0.45, return_parts=False, pix=None): + pix = PIX if pix is None else pix + oh, ow = pix.shape[:2] + (ec, eC), (ca, cb, ra, rb) = primitives(S, P, R) + right, up = camera(S, d) + B = jnp.stack([right, up]) * S["scale"] # 2x3 + q = pix.reshape(-1, 2) + # ellipsoids + c2 = ec @ B.T + C2 = jnp.einsum("ij,njk,lk->nil", B, eC, B) + M = jnp.linalg.inv(C2) + dq = q[None] - c2[:, None] + Mq = jnp.einsum("nij,npj->npi", M, dq) + rho = jnp.sqrt(jnp.sum(dq * Mq, -1) + 1e-9) + g = jnp.sqrt(jnp.sum(Mq * Mq, -1) + 1e-9) / rho + de = (rho - 1.0) / g + # cones (interpolated-disc approximation) + a2, b2 = ca @ B.T, cb @ B.T + ab = b2 - a2 + h = jnp.sum(ab * ab, -1) + 1e-6 + t = jnp.clip(jnp.einsum("npk,nk->np", q[None] - a2[:, None], ab) / h[:, None], 0.0, 1.0) + pt = a2[:, None] + t[..., None] * ab[:, None] + rr = (ra + (rb - ra) * t.T).T * S["scale"] + dc = jnp.sqrt(jnp.sum((q[None] - pt) ** 2, -1) + 1e-9) - rr + dist = jnp.concatenate([de, dc], 0) + occ_i = jax.nn.sigmoid(-dist / tau) + occ = 1.0 - jnp.prod(1.0 - occ_i, 0) + occ = occ.reshape(oh, ow) + if return_parts: + return occ, dist.reshape(-1, oh, ow) + return occ + + +def zero_pose(): + return dict(rot=jnp.zeros((NJ, 3), jnp.float32), trans=jnp.zeros(3, jnp.float32)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/bake13.py b/third_party/UO_Model3D_v13/pipeline/body13/bake13.py new file mode 100644 index 0000000..3e297e4 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/bake13.py @@ -0,0 +1,166 @@ +"""bake the v13 body textures from the original UO frames (MakeHuman UV layout): +albedo = sprite colour / UO lighting (ambient + diffuse * max(0, n.L), light fixed to the camera, uo_light.pkl), +robust weighted mean over every visible sample; one texture per UO direction + one from all directions. +usage: bake13.py shape.json poses.json outdir [--size 1024]""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, os, json, base64, zlib, pickle, time, numpy as np +from numba import njit +from PIL import Image +from shape13 import Shape, load_params +from skel13 import Skel13 +from posefit13 import Frame13 +from horse_sdf import depth_raster +from fk import rig_world +from mhlib import MH + +shape_fn, poses_fn, outdir = sys.argv[1:4] +TEX = int(sys.argv[sys.argv.index("--size") + 1]) if "--size" in sys.argv else 1024 +os.makedirs(outdir, exist_ok=True) +t0 = time.time() +r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]); P = json.load(open(poses_fn)) +S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params(shape_fn), full=True); V = Vf[S.used] +K = Skel13(S, r["R"], r["parent"], bones, Vf) +LIGHT = pickle.load(open(os.path.join(HERE, "..", "uo_light.pkl"), "rb")) +Lc = np.array(LIGHT["L_camera"]); AMB, DIF = LIGHT["ambient"], LIGHT["diffuse"] +ORIG = json.load(open(os.path.join(HERE, "..", "uo_original_frames.json")))["frames"] + + +def load_uv(): + VT, FT, grp = [], [], None + for line in open(MH + "base.obj"): + if line.startswith("vt "): VT.append([float(x) for x in line.split()[1:3]]) + elif line.startswith("g "): grp = line.split()[1] + elif line.startswith("f ") and grp == "body": FT.append([int(t.split("/")[1]) - 1 for t in line.split()[1:]]) + return np.array(VT), FT + + +VT, FT = load_uv() +tri_v, tri_t = [], [] +for f, ft in zip(S.faces, FT): + for j in range(1, len(f) - 1): + tri_v.append((f[0], f[j], f[j + 1])); tri_t.append((ft[0], ft[j], ft[j + 1])) +tri_v = np.array(tri_v, np.int32); tri_t = np.array(tri_t, np.int32) + + +@njit(cache=True) +def texel_map(UV, tri_t, size): + """texel centres inside UV triangles -> (y, x, tri, b0, b1, b2)""" + out = np.zeros((size * size, 6)); n = 0 + owner = np.full((size, size), -1, np.int64) + for t in range(tri_t.shape[0]): + a = UV[tri_t[t, 0]] * size; b = UV[tri_t[t, 1]] * size; c = UV[tri_t[t, 2]] * size + den = (b[1] - c[1]) * (a[0] - c[0]) + (c[0] - b[0]) * (a[1] - c[1]) + if abs(den) < 1e-12: continue + x0 = max(int(np.floor(min(a[0], b[0], c[0]))), 0); x1 = min(int(np.ceil(max(a[0], b[0], c[0]))), size - 1) + y0 = max(int(np.floor(min(a[1], b[1], c[1]))), 0); y1 = min(int(np.ceil(max(a[1], b[1], c[1]))), size - 1) + for y in range(y0, y1 + 1): + for x in range(x0, x1 + 1): + if owner[y, x] >= 0: continue + qx = x + 0.5; qy = y + 0.5 + l0 = ((b[1] - c[1]) * (qx - c[0]) + (c[0] - b[0]) * (qy - c[1])) / den + l1 = ((c[1] - a[1]) * (qx - c[0]) + (a[0] - c[0]) * (qy - c[1])) / den + l2 = 1 - l0 - l1 + if l0 < -1e-6 or l1 < -1e-6 or l2 < -1e-6: continue + owner[y, x] = t + out[n, 0] = y; out[n, 1] = x; out[n, 2] = t; out[n, 3] = l0; out[n, 4] = l1; out[n, 5] = l2; n += 1 + return out[:n] + + +TM = texel_map(VT, tri_t, TEX) +ty = TM[:, 0].astype(int); tx = TM[:, 1].astype(int); tt = TM[:, 2].astype(int); tb = TM[:, 3:6] +NT = len(TM); print("texels", NT, "%.0fs" % (time.time() - t0), flush=True) +TV = tri_v[tt] # (NT, 3) vertex ids per texel +F4 = np.array([f if len(f) == 4 else list(f) + [f[-1]] for f in S.faces]) + + +def normals(X): + a, b, c, e = X[F4[:, 0]], X[F4[:, 1]], X[F4[:, 2]], X[F4[:, 3]] + fn = np.cross(c - a, e - b); n = np.zeros_like(X) + for k in range(4): np.add.at(n, F4[:, k], fn) + return n / np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12) + + +def srgb2lin(c): + c = c / 255.0 + return np.where(c <= 0.04045, c / 12.92, ((c + 0.055) / 1.055) ** 2.4) + + +def lin2srgb(c): + c = np.clip(c, 0, 1) + return np.where(c <= 0.0031308, c * 12.92, 1.055 * c ** (1 / 2.4) - 0.055) * 255.0 + + +def pull_push_fill(tex, wt): + levels = [(tex * wt[..., None], wt.copy())] + while levels[-1][1].shape[0] > 1: + c, w = levels[-1]; h = c.shape[0] // 2 + levels.append((c[:2 * h, :2 * h].reshape(h, 2, h, 2, 3).sum((1, 3)), w[:2 * h, :2 * h].reshape(h, 2, h, 2).sum((1, 3)))) + col = levels[-1][0] / np.maximum(levels[-1][1], 1e-9)[..., None] + for c, w in reversed(levels[:-1]): + up = np.repeat(np.repeat(col, 2, 0), 2, 1)[: c.shape[0], : c.shape[1]] + own = c / np.maximum(w, 1e-9)[..., None]; a = np.clip(w, 0, 1)[..., None] + col = own * a + up * (1 - a) + return col + + +# per view samples ------------------------------------------------------------ +fk = {tuple(k): n for n, k in enumerate(r["keys"])} +Vh = np.c_[V, np.ones(len(V))] + + +def gather(): + """yields (d, texel idx, sprite colour (linear), shading, weight) for every view""" + cache = {} + for n, (a, i, d) in enumerate(v["keys"]): + key = "%d,%d" % (a, i) + if key not in P: continue + if (a, i) not in cache: + f = fk[(a, i)] + fr = Frame13(K, None, None, None, None, r["Brel"], None, None, [], r["loc"][f], r["quat"][f]) + Sk = fr.skin(np.array(P[key]["x"])) + X = np.einsum("nb,bij,nj->ni", K.SW, Sk, Vh)[:, :3] + cache = {(a, i): (X, normals(X))} + X, Nv = cache[(a, i)] + M = v["C"][n] @ rig_world(d) + h = np.c_[X, np.ones(len(X))] @ M.T + Sx = (h[:, 0] + 1) * 68.0; Sy = (1 - h[:, 1]) * 60.0; Z = h[:, 2].copy() + D = np.full((120, 136), np.inf); depth_raster(np.stack([Sx, Sy], 1), Z, tri_v, D) + Rc = M[:3, :3] / np.linalg.norm(M[:3, :3], axis=1, keepdims=True) + ncam = Nv @ Rc.T; ncam[:, 2] *= -1 + zs = np.linalg.norm(M[2, :3]) + px = np.einsum("nk,nk->n", tb, Sx[TV]); py = np.einsum("nk,nk->n", tb, Sy[TV]); pz = np.einsum("nk,nk->n", tb, Z[TV]) + nt = np.einsum("nk,nkd->nd", tb, ncam[TV]); nt /= np.maximum(np.linalg.norm(nt, axis=1, keepdims=True), 1e-12) + xi = np.floor(px).astype(int); yi = np.floor(py).astype(int) + ok = (xi >= 0) & (xi < 136) & (yi >= 0) & (yi < 120) & (nt[:, 2] > 0.2) + ok[ok] &= pz[ok] <= D[yi[ok], xi[ok]] + 0.015 * zs + o = np.frombuffer(zlib.decompress(base64.b64decode(ORIG["%d,%d,%d" % (a, i, d)])), np.uint8).reshape(120, 136, 4) + al = o[..., 3] > 0 + core = al.copy(); core[1:] &= al[:-1]; core[:-1] &= al[1:]; core[:, 1:] &= al[:, :-1]; core[:, :-1] &= al[:, 1:] + ok[ok] &= core[yi[ok], xi[ok]] + idx = np.nonzero(ok)[0] + col = srgb2lin(o[yi[idx], xi[idx], :3].astype(np.float64)) + sh = AMB + DIF * np.maximum(nt[idx] @ Lc, 0) + yield d, idx, col, sh, nt[idx, 2] ** 2 + + +def accumulate(prev=None, sigma=0.08): + """num / den per direction (robust against prev albedo per direction and for all directions)""" + num = np.zeros((6, NT, 3)); den = np.zeros((6, NT)) + for d, idx, col, sh, w in gather(): + for slot in (d, 5): + ww = w + if prev is not None: + diff = np.linalg.norm(prev[slot][idx] * sh[:, None] - col, axis=1); ww = w * np.exp(-0.5 * (diff / sigma) ** 2) + np.add.at(num[slot], idx, ww[:, None] * col * sh[:, None]); np.add.at(den[slot], idx, ww * sh * sh) + return num / np.maximum(den, 1e-9)[..., None], den + + +a1, _ = accumulate(); print("pass 1 %.0fs" % (time.time() - t0), flush=True) +a2, den = accumulate(a1); print("pass 2 %.0fs" % (time.time() - t0), flush=True) +for tag, slot in [("all", 5)] + [("dir%d" % d, d) for d in range(5)]: + tex = np.zeros((TEX, TEX, 3)); wt = np.zeros((TEX, TEX)) + tex[ty, tx] = lin2srgb(a2[slot]); wt[ty, tx] = np.clip(den[slot] / 0.5, 0, 1) + filled = pull_push_fill(tex, wt) + Image.fromarray(np.clip(filled, 0, 255).astype(np.uint8)[::-1]).save(os.path.join(outdir, "UO_Body_Albedo_%s.png" % tag)) + print(tag, "covered %.1f%%" % (100 * (den[slot] > 1e-9).mean()), flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/build_v13.py b/third_party/UO_Model3D_v13/pipeline/body13/build_v13.py new file mode 100644 index 0000000..ca2fbc8 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/build_v13.py @@ -0,0 +1,189 @@ +"""build the v13 .blend: MakeHuman-based UO_Body on the 55-bone UO_Rig, actions re-keyed with the refit poses. +usage: python build_v13.py src.blend shape.json poses.json out.blend +- the 19 UO bones keep their rest pose; new bones: upper_arm_twist / forearm_twist, 15 finger bones, toe (per side) +- forearm / hand / shin / foot do not inherit the parent's scale (the parent's scale X/Z is its girth) +- UO_Body (v12) is replaced by the v13 mesh (no corrective shape keys); the old one is removed +- every refit frame is keyed: bone rotations, pelvis location, girth scale, finger curl and toe""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import bpy, sys, os, json, numpy as np +from mathutils import Matrix, Quaternion, Vector +sys.path.insert(0, HERE) +from shape13 import Shape, load_params +from skel13 import Skel13, SIDES +from posefit13 import Frame13, Layout, GIRTH, NO_INHERIT, EXTRA0 +from posefit import rotvec +from fk import qmat + +pos = [a for a in sys.argv[1:] if not a.startswith("--")] +CLOTHS = [a.split("=", 1)[1] for a in sys.argv if a.startswith("--cloth=")] # e.g. --cloth=449:cloth_449.json +MOUNTED = [a.split("=", 1)[1] for a in sys.argv if a.startswith("--mounted=")] +TEXDIR = ([a.split("=", 1)[1] for a in sys.argv if a.startswith("--tex=")] or [None])[0] # baked albedo folder +src, shape_fn, poses_fn, out = pos[-4:] +bpy.ops.wm.open_mainfile(filepath=src) +rig = bpy.data.objects["UO_Rig"]; old = bpy.data.objects["UO_Body"] +v = np.load(os.path.join(HERE, "views_all.npz")) +r = np.load(os.path.join(HERE, "rig_poses.npz")) +bones = list(r["bones"]) +S = Shape(v["U"], v["BV"], v["BDOM"], bones) +Vf = S.build(load_params(shape_fn), full=True); V = Vf[S.used] +K = Skel13(S, r["R"], r["parent"], bones, Vf) +P = json.load(open(poses_fn)) if poses_fn != "-" else {} +for fn in MOUNTED: + P.update(json.load(open(fn))) + +# ------------------------------------------------------------------ rig +bpy.context.view_layer.objects.active = rig +for o in bpy.context.selected_objects: o.select_set(False) +rig.select_set(True) +bpy.ops.object.mode_set(mode="EDIT") +eb = rig.data.edit_bones +for i in range(19, len(K.names)): + n = K.names[i]; R = K.R[i] + b = eb.new(n); b.head = Vector(R[:3, 3]); b.tail = Vector(R[:3, 3] + R[:3, 1] * K.L[i]); b.align_roll(Vector(R[:3, 2])) + b.parent = eb[K.names[K.parent[i]]]; b.use_connect = False; b.use_deform = True +for n in NO_INHERIT: + eb[n].inherit_scale = "NONE" +bpy.ops.object.mode_set(mode="OBJECT") +err = max(np.abs(np.array(rig.data.bones[n].matrix_local) - K.R[i]).max() for i, n in enumerate(K.names)) +print("rig: %d bones, max rest matrix error %.2e" % (len(rig.data.bones), err)) +arm = rig.data +for cname, pred in (("Fingers", lambda n: n.startswith("finger")), ("Twist", lambda n: "twist" in n), ("Toes", lambda n: n.startswith("toe"))): + c = arm.collections.get(cname) or arm.collections.new(cname) + for n in K.names: + if pred(n): c.assign(arm.bones[n]) +for i in range(19, len(K.names)): + rig.pose.bones[K.names[i]].rotation_mode = "QUATERNION" + +# ------------------------------------------------------------------ body +mats = [m for m in old.data.materials] +old_name = old.name; old.name = "UO_Body_v12" +me = bpy.data.meshes.new("UO_Body") +me.from_pydata(V.tolist(), [], [list(f) for f in S.faces]); me.update() +for p in me.polygons: p.use_smooth = True +body = bpy.data.objects.new("UO_Body", me) +for c in old.users_collection: c.objects.link(body) +body.parent = rig; body.matrix_parent_inverse = rig.matrix_world.inverted(); body.matrix_world = Matrix(np.eye(4).tolist()) +for j, n in enumerate(K.names): + g = body.vertex_groups.new(name=n) + for vi in np.nonzero(K.SW[:, j] > 1e-4)[0]: + g.add([int(vi)], float(K.SW[vi, j]), "REPLACE") +m = body.modifiers.new("Armature", "ARMATURE"); m.object = rig +# UVs (MakeHuman layout) + the v12 material with the v13 textures baked from the original frames +VT, FT = [], []; grp = None +for line in open(os.path.join(HERE, "base.obj")): + if line.startswith("vt "): VT.append([float(x) for x in line.split()[1:3]]) + elif line.startswith("g "): grp = line.split()[1] + elif line.startswith("f ") and grp == "body": FT.append([int(t.split("/")[1]) - 1 for t in line.split()[1:]]) +uvl = me.uv_layers.new(name="UVMap") +for p, ft in zip(me.polygons, FT): + for li, t in zip(p.loop_indices, ft): + uvl.data[li].uv = VT[t] +if TEXDIR and mats: + skin = mats[0] + skin.name = "UO_Skin" + for nd in skin.node_tree.nodes: + if nd.type == "TEX_IMAGE" and nd.image and nd.image.name.startswith("UO_Body_"): + tag = "all" if nd.image.name == "UO_Body_Texture" else nd.image.name.split("_")[-1] + fn = os.path.join(TEXDIR, "UO_Body_Albedo_%s.png" % tag) + old_img = nd.image; nm = old_img.name + img = bpy.data.images.load(fn); img.colorspace_settings.name = old_img.colorspace_settings.name; img.pack() + nd.image = img; bpy.data.images.remove(old_img); img.name = nm + me.materials.append(skin) +else: + skin = bpy.data.materials.get("UO_Skin_v13") or bpy.data.materials.new("UO_Skin_v13") + skin.use_nodes = True; skin.node_tree.nodes["Principled BSDF"].inputs["Base Color"].default_value = (0.8, 0.62, 0.5, 1) + me.materials.append(skin) +bpy.data.objects.remove(old, do_unlink=True) +for o in [o for o in bpy.data.objects if o.name.startswith("UO_Body_v13")]: + bpy.data.objects.remove(o, do_unlink=True) + +# ------------------------------------------------------------------ actions +L = Layout(K.names); fr_keys = {tuple(k): n for n, k in enumerate(r["keys"])} +acts = {int(a["uo_action"]): a for a in bpy.data.actions if "uo_action" in a} +keyed = 0 +for key, rec in P.items(): + a, i = map(int, key.split(",")); act = acts[a]; f = fr_keys[(a, i)]; frame = 1 + 3 * i + x = np.array(rec["x"]); rr = x[:57].reshape(19, 3); dl = x[57:60]; g = x[L.o_g:L.o_e].reshape(-1, 2); e = x[L.o_e:] + rig.animation_data.action = act + for b in range(19): + pb = rig.pose.bones[bones[b]] + q = Matrix((qmat(r["quat"][f, b]) @ rotvec(rr[b])).tolist()).to_quaternion() + if q.dot(Quaternion(r["quat"][f, b])) < 0: q.negate() + pb.rotation_quaternion = q; pb.keyframe_insert("rotation_quaternion", frame=frame) + if b == 0: + pb.location = Vector(r["loc"][f, 0] + dl); pb.keyframe_insert("location", frame=frame) + for k, bn in enumerate(GIRTH): + pb = rig.pose.bones[bn]; pb.scale = (float(np.exp(g[k, 0])), 1.0, float(np.exp(g[k, 1]))) + pb.keyframe_insert("scale", frame=frame) + ext = K.extra_bases({".L": e[0], ".R": e[1]}, {".L": e[2], ".R": e[3]}, {".L": e[4], ".R": e[5]}) + for bn, M in ext.items(): + pb = rig.pose.bones[bn]; pb.rotation_quaternion = Matrix(M.tolist()).to_quaternion() + pb.keyframe_insert("rotation_quaternion", frame=frame) + keyed += 1 +# actions without refit frames (mounted, for now): fists, no girth +for a, act in acts.items(): + rig.animation_data.action = act + for i in range(int(act["uo_frames"])): + if "%d,%d" % (a, i) in P: continue + ext = K.extra_bases({".L": 1.0, ".R": 1.0}, {".L": 1.0, ".R": 1.0}, {".L": 0.0, ".R": 0.0}) + for bn, M in ext.items(): + pb = rig.pose.bones[bn]; pb.rotation_quaternion = Matrix(M.tolist()).to_quaternion() + pb.keyframe_insert("rotation_quaternion", frame=1 + 3 * i) +# ------------------------------------------------------------------ cloth chain rigs + templates +from cloth13 import make_cloth, KINDS +from mathutils import Matrix as _M +tcoll = bpy.data.collections.get("Templates") or bpy.data.collections.new("Templates") +if tcoll.name not in [c.name for c in bpy.context.scene.collection.children]: + bpy.context.scene.collection.children.link(tcoll) +for spec in CLOTHS: + anim, fn = spec.split(":"); anim = int(anim); CFIT = json.load(open(fn)) + kind, zt, zh = KINDS[anim] + crig, CV, CF, CW, top, par = make_cloth(K, V, kind, zt, zh, faces=S.faces) + bpy.context.view_layer.objects.active = rig; bpy.ops.object.mode_set(mode="EDIT"); eb = rig.data.edit_bones + for b, n in enumerate(crig.names): + if n in eb: eb.remove(eb[n]) + for b, n in enumerate(crig.names): + R = crig.R[b]; e = eb.new(n); e.head = Vector(R[:3, 3]); e.tail = Vector(R[:3, 3] + R[:3, 1] * crig.L[b]); e.align_roll(Vector(R[:3, 2])) + e.parent = eb[par] if isinstance(crig.par[b], str) else eb[crig.names[crig.par[b]]]; e.use_deform = True + bpy.ops.object.mode_set(mode="OBJECT") + c = arm.collections.get("Cloth") or arm.collections.new("Cloth") + for n in crig.names: + c.assign(arm.bones[n]); rig.pose.bones[n].rotation_mode = "QUATERNION" + tname = "UO_Template_" + ("Cloak" if kind == "cloak" else "Skirt") + if tname in bpy.data.objects: bpy.data.objects.remove(bpy.data.objects[tname], do_unlink=True) + tm = bpy.data.meshes.new(tname); tm.from_pydata(CV.tolist(), [], CF.tolist()); tm.update() + to = bpy.data.objects.new(tname, tm); tcoll.objects.link(to) + to.parent = rig; to.matrix_parent_inverse = rig.matrix_world.inverted() + for j, n in enumerate(crig.wnames): + if not (CW[:, j] > 1e-4).any(): continue + g = to.vertex_groups.new(name=n) + for vi in np.nonzero(CW[:, j] > 1e-4)[0]: g.add([int(vi)], float(CW[vi, j]), "REPLACE") + to.modifiers.new("Armature", "ARMATURE").object = rig + to.hide_render = True; to.display_type = "WIRE" + from cloth13 import rotxz + for key, rec in CFIT.items(): + a, i = map(int, key.split(",")); rig.animation_data.action = acts[a] + ang = np.array(rec["x"]).reshape(-1, 2) + for b, n in enumerate(crig.names): + pb = rig.pose.bones[n]; pb.rotation_quaternion = _M(rotxz(ang[b, 0], ang[b, 1]).tolist()).to_quaternion() + pb.keyframe_insert("rotation_quaternion", frame=1 + 3 * i) + print("cloth", tname, len(crig.names), "bones,", len(CFIT), "frames keyed") +# ------------------------------------------------------------------ user scripts (v13-aware versions) +PIPE = os.path.join(HERE, "..", "") +for tn in ("render_uo_layer.py", "uo_bind_item.py", "uo_fit_item.py", "uo_transfer_corrections.py"): + t = bpy.data.texts.get(tn) or bpy.data.texts.new(tn); t.from_string(open(PIPE + tn).read()) +# example shirt: drop the v12 corrections, push it out of the new skin and bind it again +shirt = bpy.data.objects.get("Example_Shirt") +if shirt is not None: + if shirt.data.shape_keys: + shirt.shape_key_clear() + rig.animation_data.action = None + for o in bpy.context.selected_objects: o.select_set(False) + shirt.select_set(True); bpy.context.view_layer.objects.active = shirt + exec(compile(bpy.data.texts["uo_fit_item.py"].as_string(), "uo_fit_item.py", "exec"), {"__name__": "__main__"}) + src_ = bpy.data.texts["uo_bind_item.py"].as_string().replace('PART = "all"', 'PART = "chest"', 1) + exec(compile(src_, "uo_bind_item.py", "exec"), {"__name__": "__main__"}) +rig.animation_data.action = acts[4] if 4 in acts else list(acts.values())[0] +bpy.ops.wm.save_as_mainfile(filepath=out, compress=True) +print("built", out, "| keyed frames", keyed, "| body verts", len(V)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/cloth13.py b/third_party/UO_Model3D_v13/pipeline/body13/cloth13.py new file mode 100644 index 0000000..751a261 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/cloth13.py @@ -0,0 +1,207 @@ +"""cloth chain rigs for v13: a skirt ring (chains around the pelvis) and a cloak (chains down the back). +Each chain is a string of bones; a bone swings about its local X (out / in, radial) and Z (sideways). +Template meshes are generated around the rest body and weighted to the chains (angle x height blend).""" +import numpy as np +from skel13 import frame_from + + +def rotxz(ax, az): + cx, sx, cz, sz = np.cos(ax), np.sin(ax), np.cos(az), np.sin(az) + Rx = np.array([[1, 0, 0], [0, cx, -sx], [0, sx, cx]]); Rz = np.array([[cz, -sz, 0], [sz, cz, 0], [0, 0, 1]]) + return Rx @ Rz + + +def section_radius(V, center, z, phis, slab=0.02, margin=0.012): + """max radius of the body around `center` at height z per direction (angular bins), smoothed""" + sel = np.abs(V[:, 2] - z) < slab + rel = V[sel, :2] - center[:2] + ang = np.arctan2(rel[:, 1], rel[:, 0]); rad = np.linalg.norm(rel, axis=1) + nb = 72; bins = ((ang + np.pi) / (2 * np.pi) * nb).astype(int) % nb + rmax = np.zeros(nb) + np.maximum.at(rmax, bins, rad) + # fill empty bins, smooth circularly + if (rmax > 0).any(): + idx = np.nonzero(rmax > 0)[0] + allb = np.arange(nb) + rmax = np.interp(allb, np.r_[idx - nb, idx, idx + nb], np.r_[rmax[idx], rmax[idx], rmax[idx]]) + k = np.array([1, 2, 3, 2, 1], float); k /= k.sum() + rmax = np.convolve(np.r_[rmax[-2:], rmax, rmax[:2]], k, "valid") + pb = ((np.asarray(phis) + np.pi) / (2 * np.pi) * nb) % nb + return np.interp(pb, np.arange(nb + 1), np.r_[rmax, rmax[0]]) + margin + + +class ChainRig: + """generic: chains[k] = list of rest points (S+1, 3), out[k] = outward hint per chain; parent bone name""" + def __init__(self, prefix, chains, outward, parent): + self.prefix, self.parent = prefix, parent + self.nc, self.ns = len(chains), len(chains[0]) - 1 + self.names, self.R, self.L, self.par = [], [], [], [] + for k, pts in enumerate(chains): + for s in range(self.ns): + M, ln = frame_from(pts[s], pts[s + 1], outward[k]) + self.names.append("%s_%d_%d" % (prefix, k, s + 1)); self.R.append(M); self.L.append(ln) + self.par.append(parent if s == 0 else len(self.names) - 2) + self.R = np.array(self.R); self.L = np.array(self.L); self.Rinv = np.linalg.inv(self.R) + self.chains = chains + + def bone(self, k, s): + return k * self.ns + s + + def pose(self, x, P_parent, R_parent): + """x: (nc*ns*2) swing angles -> skin matrices (armature space) of the chain bones""" + n = len(self.names); P = np.zeros((n, 4, 4)); a = x.reshape(n, 2) + base = P_parent @ np.linalg.inv(R_parent) + for b in range(n): + M = np.eye(4); M[:3, :3] = rotxz(a[b, 0], a[b, 1]) + p = self.par[b] + P[b] = (base if isinstance(p, str) else P[p] @ self.Rinv[p]) @ self.R[b] @ M + return P @ self.Rinv + + +def skirt(V, pelvis_head, z_top, z_hem, nc=8, ns=3, flare=0.03, cols_per=4, rows_per=4, margin=0.012, keep=None, + arc=None, prefix="skirt", parent="pelvis", center=None): + """cloth ring around the body from z_top down to z_hem (arc=None: closed skirt; arc=(a0, a1) radians: open, e.g. a + cloak around the back); returns rig, verts, faces, weights, top ring. + keep: body vertices used for the envelope (torso + legs, not the arms)""" + if keep is not None: + V = V[keep] + if center is None: + center = np.array([pelvis_head[0], np.median(V[np.abs(V[:, 2] - z_top) < 0.03, 1]), 0.0]) + zs = np.linspace(z_top, z_hem, ns + 1) + closed = arc is None + th = (-np.pi / 2 + 2 * np.pi * np.arange(nc) / nc) if closed else np.linspace(arc[0], arc[1], nc) + def rad_at(phis, z_list): + out = []; prev = None + for j, z in enumerate(z_list): + r = section_radius(V, center, z, phis, margin=margin) + if prev is not None: + r = np.maximum(r, prev) + r = r + flare * (z_top - z) / max(z_top - z_hem, 1e-6) + out.append(r); prev = r + return np.array(out) + rc = rad_at(th, zs) + chains = [np.array([[center[0] + rc[j, k] * np.cos(th[k]), center[1] + rc[j, k] * np.sin(th[k]), zs[j]] for j in range(ns + 1)]) for k in range(nc)] + outward = [np.array([np.cos(t), np.sin(t), 0.0]) for t in th] + rig = ChainRig(prefix, chains, outward, parent) + M_ = nc * cols_per if closed else (nc - 1) * cols_per + 1 + R_ = ns * rows_per + phis = (-np.pi / 2 + 2 * np.pi * np.arange(M_) / M_) if closed else np.linspace(arc[0], arc[1], M_) + zr = np.linspace(z_top, z_hem, R_ + 1) + rr = rad_at(phis, zr) + verts = np.array([[center[0] + rr[j, c] * np.cos(phis[c]), center[1] + rr[j, c] * np.sin(phis[c]), zr[j]] for j in range(R_ + 1) for c in range(M_)]) + cols = M_ if closed else M_ - 1 + faces = [[j * M_ + c, j * M_ + (c + 1) % M_, (j + 1) * M_ + (c + 1) % M_, (j + 1) * M_ + c] for j in range(R_) for c in range(cols)] + W = np.zeros((len(verts), len(rig.names))) + for j in range(R_ + 1): + t = j / rows_per + for c in range(M_): + u = c / cols_per; k0 = int(np.floor(u)) % nc if closed else min(int(np.floor(u)), nc - 2) + k1 = (k0 + 1) % nc; fu = u - k0 if not closed else u - np.floor(u) + for k, wk in ((k0, 1 - fu), (k1, fu)): + s = min(int(np.floor(t)), ns - 1); ft = t - s + if ft < 0.5 and s > 0: + a_ = 0.5 + ft; W[j * M_ + c, rig.bone(k, s)] += wk * a_; W[j * M_ + c, rig.bone(k, s - 1)] += wk * (1 - a_) + elif ft > 0.5 and s < ns - 1: + a_ = 1.5 - ft; W[j * M_ + c, rig.bone(k, s)] += wk * a_; W[j * M_ + c, rig.bone(k, s + 1)] += wk * (1 - a_) + else: + W[j * M_ + c, rig.bone(k, s)] += wk + return rig, verts, np.array(faces), W, np.arange(M_) + + +def cloak(V, R_chest, z_top, z_hem, x_half, nc=5, ns=4, cols_per=3, rows_per=3, margin=0.02): + """cloak down the back (+Y side of the body) from the shoulders (z_top) to z_hem, width 2*x_half at the top""" + xs = np.linspace(-x_half, x_half, nc) + zs = np.linspace(z_top, z_hem, ns + 1) + def back_y(x, z): + sel = (np.abs(V[:, 2] - z) < 0.03) & (np.abs(V[:, 0] - x) < 0.04) + return (V[sel, 1].max() if sel.any() else V[:, 1].max()) + margin + chains = [] + for x in xs: + pts = []; ymax = -np.inf + for j, z in enumerate(zs): + ymax = max(ymax, back_y(x, z)); pts.append([x * (1 + 0.25 * j / ns), ymax + 0.02 * j, z]) + chains.append(np.array(pts)) + outward = [np.array([0.0, 1.0, 0.0])] * nc + rig = ChainRig("cloak", chains, outward, "chest") + M_ = (nc - 1) * cols_per + 1; R_ = ns * rows_per + verts = []; W = [] + for j in range(R_ + 1): + t = j / rows_per + for c in range(M_): + u = c / cols_per; k0 = min(int(np.floor(u)), nc - 2); fu = u - k0 + s = min(int(np.floor(t)), ns - 1); ft = t - s + p0 = chains[k0][s] + (chains[k0][s + 1] - chains[k0][s]) * ft; p1 = chains[k0 + 1][s] + (chains[k0 + 1][s + 1] - chains[k0 + 1][s]) * ft + verts.append(p0 * (1 - fu) + p1 * fu) + w = np.zeros(len(rig.names)) + for k, wk in ((k0, 1 - fu), (k0 + 1, fu)): + if ft < 0.5 and s > 0: + a = 0.5 + ft; w[rig.bone(k, s)] += wk * a; w[rig.bone(k, s - 1)] += wk * (1 - a) + elif ft > 0.5 and s < ns - 1: + a = 1.5 - ft; w[rig.bone(k, s)] += wk * a; w[rig.bone(k, s + 1)] += wk * (1 - a) + else: + w[rig.bone(k, s)] += wk + W.append(w) + faces = [[j * M_ + c, j * M_ + c + 1, (j + 1) * M_ + c + 1, (j + 1) * M_ + c] for j in range(R_) for c in range(M_ - 1)] + return rig, np.array(verts), np.array(faces), np.array(W), np.arange(M_) + + +KINDS = {449: ("skirt", 0.12, 0.10), 455: ("skirt", 0.12, 0.50), 469: ("skirt", 0.12, 0.10), 447: ("skirt", 0.12, 0.10), + 448: ("skirt", 0.12, 0.10), 468: ("cloak", -0.02, 0.18)} + + +def body_shell(K, V, faces, keep, thick): + """part of the body skin (vertices `keep`), pushed out along the normals, with the body skin weights""" + F4 = np.array([f if len(f) == 4 else list(f) + [f[-1]] for f in faces]) + a, b, c, e = V[F4[:, 0]], V[F4[:, 1]], V[F4[:, 2]], V[F4[:, 3]] + fn = np.cross(c - a, e - b); n = np.zeros_like(V) + for k in range(4): np.add.at(n, F4[:, k], fn) + n /= np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12) + idx = np.nonzero(keep)[0]; remap = -np.ones(len(V), int); remap[idx] = np.arange(len(idx)) + SF = [[remap[i] for i in f] for f in faces if keep[list(f)].all()] + SF = [f if len(f) == 4 else f + [f[-1]] for f in SF] + return V[idx] + n[idx] * thick, np.array(SF), K.SW[idx] + + +import os as _os +CLOAK_ARC = tuple(float(x) for x in _os.environ.get("CLOAK_ARC", "0,180").split(",")) +CLOAK_MARGIN = float(_os.environ.get("CLOAK_MARGIN", "0.035")) + + +def make_cloth(K, V, kind, zt, zh, faces=None): + """cloth template: bone chains + (with faces) a top part that hugs the body (skirt: waistband, cloak: yoke over the + shoulders), weighted to the body bones. rig.wnames = weight columns (chain bones, then body bones)""" + arms = [K.ix[n] for n in K.names if n.startswith(("upper_arm", "forearm", "hand", "finger", "clavicle"))] + keep = K.SW[:, arms].sum(1) < 0.3 + ph = K.R[K.ix["pelvis"]][:3, 3]; sp = K.R[K.ix["spine"]][:3, 3] + dom = np.array([K.names[j] for j in K.SW.argmax(1)]) + if kind == "skirt": + z0 = sp[2] + zt + out = skirt(V, ph, z0, zh, keep=keep) + ("pelvis",) + sel = np.isin(dom, ["pelvis", "spine", "chest"]) & (V[:, 2] > z0 - 0.015) & (V[:, 2] < z0 + 0.07) + thick = 0.014 + else: + sh = K.R[K.ix["upper_arm.L"]][:3, 3] + keep_c = keep | ((K.SW[:, arms].sum(1) >= 0.3) & (V[:, 2] > sh[2] - 0.12)) + ctr = np.array([0.0, K.R[K.ix["neck"]][1, 3], 0.0]) + out = skirt(V, ph, sh[2] + zt, zh, nc=7, ns=4, keep=keep_c, arc=(np.radians(CLOAK_ARC[0]), np.radians(CLOAK_ARC[1])), + prefix="cloak", parent="chest", center=ctr, margin=CLOAK_MARGIN, flare=0.05) + ("chest",) + yn = K.R[K.ix["neck"]][1, 3]; zn = K.R[K.ix["neck"]][2, 3]; zh_ = K.R[K.ix["head"]][2, 3] + sel = np.isin(dom, ["chest", "clavicle.L", "clavicle.R", "neck", "spine", "upper_arm.L", "upper_arm.R", + "upper_arm_twist.L", "upper_arm_twist.R"]) & (V[:, 2] > sh[2] + zt - 0.03) & (V[:, 2] < zh_ - 0.015) + sel &= (V[:, 1] > -0.03) | (V[:, 2] > sh[2] + 0.03) + thick = 0.022 + rig, CV, CF, CW, top, par = out + rig.wnames = list(rig.names) + if faces is None: + return rig, CV, CF, CW, top, par + SV, SF, SW = body_shell(K, V, faces, sel, thick) + if len(SF) == 0: + return rig, CV, CF, CW, top, par + nc = len(rig.names) + W = np.zeros((len(CV) + len(SV), nc + len(K.names))) + W[:len(CV), :nc] = CW; W[len(CV):, nc:] = SW + rig.wnames = list(rig.names) + list(K.names) + CF4 = np.array([list(f) for f in CF]) + return rig, np.vstack([CV, SV]), np.vstack([CF4, SF + len(CV)]), W, top, par + + diff --git a/third_party/UO_Model3D_v13/pipeline/body13/cloth_449all.json 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a/third_party/UO_Model3D_v13/pipeline/body13/cloth_view.py b/third_party/UO_Model3D_v13/pipeline/body13/cloth_view.py new file mode 100644 index 0000000..84da3f1 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/cloth_view.py @@ -0,0 +1,35 @@ +"""visualise fitted cloth (json) vs item sprite for given frames: cloth_view.py anim fits.json out.png a,i a,i ...""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, json, numpy as np +sys.path.insert(0, HERE) +from PIL import Image +from itemframes import load, canvas +from shape13 import Shape, load_params +from skel13 import Skel13 +from posefit13 import Frame13 +from cloth13 import make_cloth, KINDS +from clothfit import ClothFrame +import fastr +ANIM, FITS, OUT = int(sys.argv[1]), sys.argv[2], sys.argv[3] +frames = [tuple(map(int, s.split(","))) for s in sys.argv[4:]] +r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]) +S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params("shape_r2.json"), full=True); V = Vf[S.used] +K = Skel13(S, r["R"], r["parent"], bones, Vf); T = fastr.tris_of(S.faces) +P = json.load(open("poses13_r3.json")); F = json.load(open(FITS)); it = load(ANIM) +kind, zt, zh = KINDS[ANIM]; rig, CV, CF, CW, top, par = make_cloth(K, V, kind, zt, zh, faces=S.faces) +fk = {tuple(int(x) for x in k): n for n, k in enumerate(r["keys"])}; vk = {tuple(int(x) for x in k): n for n, k in enumerate(v["keys"])} +rows = [] +for a, i in frames: + f = fk[(a, i)]; fr = Frame13(K, None, None, None, None, r["Brel"], None, None, [], r["loc"][f], r["quat"][f]) + Sb = fr.skin(np.array(P["%d,%d" % (a, i)]["x"])); vi = [vk[(a, i, d)] for d in range(5)] + masks = np.array([canvas(it.get((a, d)), i)[..., 3] > 0 for d in range(5)]) + cf = ClothFrame(rig, CV, CF, CW, Sb, K, V, T, v["C"][vi], list(range(5)), masks, par) + m = cf.masks_of(cf.verts(np.array(F["%d,%d" % (a, i)]["x"]))) + tiles = [] + for d in range(5): + img = np.zeros((120, 136, 3), np.uint8) + 20; img[np.isfinite(cf.BD[d])] = (70, 70, 70) + img[m[d] & masks[d]] = (170, 170, 170); img[m[d] & ~masks[d]] = (230, 60, 60); img[~m[d] & masks[d]] = (60, 120, 255) + tiles.append(np.pad(img[10:110, 23:113], ((1, 1), (1, 1), (0, 0)), constant_values=90)) + rows.append(np.concatenate(tiles, 1)) +im = Image.fromarray(np.concatenate(rows, 0)); im.resize((im.width * 2, im.height * 2), Image.NEAREST).save(OUT) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/clothfit.py b/third_party/UO_Model3D_v13/pipeline/body13/clothfit.py new file mode 100644 index 0000000..e160b27 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/clothfit.py @@ -0,0 +1,140 @@ +"""fit cloth chain rigs to the original item frames (anim.mul), body pose fixed. +The item is seen where it is in front of the body (or off the body); legs (capsules) must stay inside the skirt.""" +import numpy as np +from numba import njit +from horse_sdf import depth_raster +from fk import rig_world + + +def capsules(K, V, S_body, names=("thigh.L", "shin.L", "thigh.R", "shin.R", "pelvis")): + """(head, dir, length, radius) per bone in armature space for the posed body skin matrices S_body""" + out = [] + for n in names: + b = K.ix[n]; Pf = S_body[b] @ K.R[b] + child = {"thigh.L": "shin.L", "shin.L": "foot.L", "thigh.R": "shin.R", "shin.R": "foot.R", "pelvis": "spine"}[n] + L = np.linalg.norm(K.R[K.ix[child]][:3, 3] - K.R[b][:3, 3]) + # radius from the rest body: verts mostly on this bone + sel = K.SW[:, b] > 0.6 + rel = V[sel] - K.R[b][:3, 3]; ax = K.R[b][:3, 1] + t = rel @ ax; rad = np.linalg.norm(rel - np.outer(t, ax), axis=1) + r = np.percentile(rad[(t > 0.15 * L) & (t < 0.85 * L)], 60) if ((t > 0.15 * L) & (t < 0.85 * L)).sum() > 10 else 0.05 + out.append((Pf[:3, 3], Pf[:3, 1], L, r)) + return out + + +def penetration(X, caps, margin=-0.01): + pen = 0.0 + for h, d, L, r in caps: + rel = X - h; t = np.clip(rel @ d, 0, L); q = rel - np.outer(t, d) + dist = np.linalg.norm(q, axis=1) + pen += np.maximum(0, r + margin - dist).sum() + return pen + + +class ClothFrame: + def __init__(self, rig, CV, CF, CW, S_body, K, BV, body_T, C, dirs, masks, R_parent_name, prev=None, + w_pen=3.0, reg=0.002, smooth=0.01, temporal=0.01): + self.rig, self.CV, self.CW = rig, CV, CW + self.T = np.array([[f[0], f[1], f[2]] for f in CF] + [[f[0], f[2], f[3]] for f in CF], np.int32) + pb = K.ix[R_parent_name] + self.Ppar = S_body[pb] @ K.R[pb]; self.Rpar = K.R[pb] + self.C, self.dirs, self.masks = C, dirs, masks + self.RW = [rig_world(d) for d in dirs] + # body depth per view + Xb = np.einsum("nb,bij,nj->ni", K.SW, S_body, np.c_[BV, np.ones(len(BV))])[:, :3] + self.BD = [] + for k, d in enumerate(dirs): + M = C[k] @ self.RW[k]; h = np.c_[Xb, np.ones(len(Xb))] @ M.T + D = np.full((120, 136), np.inf) + depth_raster(np.stack([(h[:, 0] + 1) * 68.0, (1 - h[:, 1]) * 60.0], 1), h[:, 2].copy(), body_T, D) + self.BD.append(D) + self.caps = capsules(K, BV, S_body) + self.Sb = S_body + self.CVh = np.c_[CV, np.ones(len(CV))] + self.w_pen, self.reg, self.smooth, self.temporal = w_pen, reg, smooth, temporal + self.prev = prev + self.xref = None # regularise towards this (default: rest) + + def verts(self, x): + S = self.rig.pose(x, self.Ppar, self.Rpar) + if self.CW.shape[1] > len(S): + S = np.concatenate([S, self.Sb]) + return np.einsum("nb,bij,nj->ni", self.CW, S, self.CVh)[:, :3] + + def masks_of(self, X): + out = [] + for k in range(len(self.dirs)): + M = self.C[k] @ self.RW[k]; h = np.c_[X, np.ones(len(X))] @ M.T + D = np.full((120, 136), np.inf) + depth_raster(np.stack([(h[:, 0] + 1) * 68.0, (1 - h[:, 1]) * 60.0], 1), h[:, 2].copy(), self.T, D) + out.append(D < self.BD[k] - 0.003 * np.linalg.norm(M[2, :3])) # 3 mm in front of the skin + return np.array(out) + + def eval(self, x): + X = self.verts(x); m = self.masks_of(X); o = self.masks + inter = (m & o).sum((1, 2)); uni = (m | o).sum((1, 2)) + iou = (inter / np.maximum(uni, 1)).mean() + a = x.reshape(self.rig.nc, self.rig.ns, 2) + sm = np.sum((a - np.roll(a, 1, 0)) ** 2) if self.rig.prefix == "skirt" else np.sum(np.diff(a, axis=0) ** 2) + tp = np.sum((x - self.prev) ** 2) if self.prev is not None else 0.0 + pen = penetration(X, self.caps) + self.last = dict(iou=iou, pen=pen, out=(m & ~o).sum() / len(o), miss=(o & ~m).sum() / len(o)) + xr = x if self.xref is None else x - self.xref + return iou - self.w_pen * pen - self.reg * np.sum(xr ** 2) - self.smooth * sm - self.temporal * tp, iou + + def directions(self): + """search directions: single angles + grouped moves (level, chain, whole-cloth sway / flare)""" + rig = self.rig; nc, ns = rig.nc, rig.ns; D = [] + eye = np.eye(nc * ns * 2) + D += [eye[i] for i in range(nc * ns * 2)] + th = np.array([np.arctan2(rig.R[rig.bone(k, 0)][1, 2], rig.R[rig.bone(k, 0)][0, 2]) for k in range(nc)]) # outward angle + for s_ in range(ns): + for c in range(2): + v = np.zeros((nc, ns, 2)); v[:, s_, c] = 1; D.append(v.ravel()) + for k in range(nc): + for c in range(2): + v = np.zeros((nc, ns, 2)); v[k, :, c] = 1; D.append(v.ravel()) + for c in range(2): + v = np.zeros((nc, ns, 2)); v[:, :, c] = 1; D.append(v.ravel()) + for phi in np.linspace(0, 2 * np.pi, 8, endpoint=False): + v = np.zeros((nc, ns, 2)); v[:, :, 0] = np.cos(th - phi)[:, None]; v[:, :, 1] = np.sin(th - phi)[:, None] + D.append(v.ravel()) + return np.array(D) + + def fit(self, x0, steps=(0.24, 0.12, 0.06, 0.03), passes=3): + x = x0.copy(); f, _ = self.eval(x); D = self.directions() + for st in steps: + for _ in range(passes): + imp = False + for j in range(len(D)): + for sgn in (1, -1): + y = x + sgn * st * D[j] + fy, _ = self.eval(y) + if fy > f + 1e-6: + x, f = y, fy; imp = True + while True: + y = x + sgn * st * D[j]; fy, _ = self.eval(y) + if fy > f + 1e-6: x, f = y, fy + else: break + break + if not imp: break + self.eval(x) + return x + + +class MountedClothFrame(ClothFrame): + """mounted frames: the horse hides the cloth too, and the cloth must stay out of the horse proxy""" + def __init__(self, *a, HV=None, HT=None, sdf=None, lo=None, w_horse=3.0, tol=0.03, **k): + super().__init__(*a, **k) + from mounted import horse_depth + self.HD = horse_depth(HV, HT, self.C, self.dirs) + self.BD = [np.minimum(b, h) for b, h in zip(self.BD, self.HD)] + self.sdf, self.lo, self.w_horse, self.tol = sdf, lo, w_horse, tol + + def eval(self, x): + from horse_sdf import sample, H + f, iou = super().eval(x) + X = self.verts(x) + hp = np.maximum(0, -sample(self.sdf, self.lo, H, X) - self.tol).sum() + self.last["hpen"] = hp + return f - self.w_horse * hp, iou diff --git a/third_party/UO_Model3D_v13/pipeline/body13/compose.py b/third_party/UO_Model3D_v13/pipeline/body13/compose.py new file mode 100644 index 0000000..656fb56 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/compose.py @@ -0,0 +1,26 @@ +"""original body + rendered item layer, side by side for several renders. compose.py out.png dirA dirB ... -- act:frame:dir ...""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, os, json, base64, zlib, numpy as np +from PIL import Image +sep = sys.argv.index("--"); out = sys.argv[1]; dirs = sys.argv[2:sep]; views = sys.argv[sep + 1:] +ORIG = json.load(open(os.path.join(HERE, "..", "uo_original_frames.json")))["frames"] +rows = [] +for v in views: + act, i, d = v.split(":"); a = int(act[:2]) + o = np.frombuffer(zlib.decompress(base64.b64decode(ORIG["%d,%d,%d" % (a, int(i), int(d))])), np.uint8).reshape(120, 136, 4) + tiles = [np.where(o[..., 3:] > 0, o[..., :3], 40).astype(np.uint8)] + for dd in dirs: + it = np.array(Image.open("%s/clothing/frames/%s/dir%s/%02d.png" % (dd, act, d, int(i))).convert("RGBA")) + img = np.where(o[..., 3:] > 0, o[..., :3], 40).astype(np.uint8) + m = it[..., 3] > 0; img[m] = it[m, :3] + tiles.append(img) + rows.append(np.concatenate(tiles, 1)) +CROP = [int(c) for c in os.environ.get("CROP", "0,0,136,120").split(",")] +rows = [r_.reshape(120, -1, 136, 3)[:, :, :, :] if False else r_ for r_ in rows] +cr = [] +for r_ in rows: + tiles = [r_[:, k * 136:(k + 1) * 136][CROP[1]:CROP[3], CROP[0]:CROP[2]] for k in range(r_.shape[1] // 136)] + cr.append(np.concatenate([np.pad(t, ((1, 1), (1, 1), (0, 0)), constant_values=90) for t in tiles], 1)) +S_ = int(os.environ.get("SCALE", "3")) +im = Image.fromarray(np.concatenate(cr, 0)); im.resize((im.width * S_, im.height * S_), Image.NEAREST).save(out); print(out) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/dump_horse.py b/third_party/UO_Model3D_v13/pipeline/body13/dump_horse.py new file mode 100644 index 0000000..ee364b2 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/dump_horse.py @@ -0,0 +1,14 @@ +"""horse proxy meshes (rig space) per mounted frame -> horse.npz""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import bpy, numpy as np +bpy.ops.wm.open_mainfile(filepath=os.path.join(HERE, "..", "..", "model", "UO_Body_0x190.blend")) +rig = bpy.data.objects["UO_Rig"]; rig["uo_direction"] = 0; rig.update_tag(); bpy.context.view_layer.update() +out = {} +for o in bpy.data.objects: + if o.name.startswith("Horse_a"): + a, f = o.name[7:].split("_f"); M = np.array(rig.matrix_world.inverted() @ o.matrix_world) + co = np.array([M[:3, :3] @ np.array(v.co) + M[:3, 3] for v in o.data.vertices]) + o.data.calc_loop_triangles(); tri = np.array([t.vertices[:] for t in o.data.loop_triangles]) + out["v_%s_%s" % (a, f)] = co; out["t_%s_%s" % (a, f)] = tri +np.savez_compressed("horse.npz", **out); print(len(out) // 2, "horse meshes") diff --git a/third_party/UO_Model3D_v13/pipeline/body13/dump_poses.py b/third_party/UO_Model3D_v13/pipeline/body13/dump_poses.py new file mode 100644 index 0000000..668923b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/dump_poses.py @@ -0,0 +1,22 @@ +"""rest matrices of UO_Rig + per-frame pose channels of every action + body-in-rig matrix -> rig_poses.npz""" +import bpy, numpy as np, sys +bpy.ops.wm.open_mainfile(filepath=sys.argv[1]) +sc = bpy.context.scene; rig = bpy.data.objects["UO_Rig"]; body = bpy.data.objects["UO_Body"] +v13 = bpy.data.objects.get("UO_Body_v13") +bones = [b.name for b in rig.data.bones] +R = np.array([np.array(b.matrix_local) for b in rig.data.bones]) +par = np.array([bones.index(b.parent.name) if b.parent else -1 for b in rig.data.bones]) +rig["uo_direction"] = 0; rig.update_tag(); bpy.context.view_layer.update() +Brel = np.array(rig.matrix_world.inverted() @ (v13 or body).matrix_world) +rig.data.pose_position = "POSE" +keys, loc, quat, scl = [], [], [], [] +acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) +for act in acts: + rig.animation_data.action = act; a = int(act["uo_action"]) + for i in range(int(act["uo_frames"])): + sc.frame_set(1 + 3 * i) + keys.append((a, i)) + loc.append([list(rig.pose.bones[b].location) for b in bones]); quat.append([list(rig.pose.bones[b].rotation_quaternion) for b in bones]) + scl.append([list(rig.pose.bones[b].scale) for b in bones]) +np.savez(sys.argv[2], bones=np.array(bones), R=R, parent=par, Brel=Brel, keys=np.array(keys), loc=np.array(loc), quat=np.array(quat), scale=np.array(scl)) +print("frames", len(keys), "max |scale-1|", np.abs(np.array(scl) - 1).max(), "max |loc|", np.abs(np.array(loc)).max(axis=(0, 2))) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/dump_v12.py b/third_party/UO_Model3D_v13/pipeline/body13/dump_v12.py new file mode 100644 index 0000000..bcccf49 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/dump_v12.py @@ -0,0 +1,15 @@ +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import bpy, numpy as np +bpy.ops.wm.open_mainfile(filepath=os.path.join(HERE, "..", "..", "model", "UO_Body_0x190.blend")) +body = bpy.data.objects["UO_Body"]; rig = bpy.data.objects["UO_Rig"] +bones = [b.name for b in rig.data.bones] +names = [g.name for g in body.vertex_groups] +kb = body.data.shape_keys.key_blocks["Basis"]; BV = np.array([k.co[:] for k in kb.data]) +BW = np.zeros((len(BV), len(bones))) +for v in body.data.vertices: + for g in v.groups: + if names[g.group] in bones: BW[v.index, bones.index(names[g.group])] = g.weight +F = np.array([list(p.vertices) for p in body.data.polygons], dtype=object) +np.savez("v12_mesh.npz", BV=BV, BW=BW, faces=F, bones=np.array(bones), groups=np.array(names)) +print(len(BV), len(F), "groups", names) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/eval13.py b/third_party/UO_Model3D_v13/pipeline/body13/eval13.py new file mode 100644 index 0000000..6e3e251 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/eval13.py @@ -0,0 +1,26 @@ +"""IoU of UO_Body (v13 blend) vs original frames: eval13.py blend out.json [--frames a,i;a,i] [--mounted]""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import bpy, sys, json, base64, zlib, numpy as np +blend, out = sys.argv[1], sys.argv[2] +FR = [tuple(map(int, s.split(","))) for s in sys.argv[sys.argv.index("--frames") + 1].split(";")] if "--frames" in sys.argv else None +MOUNTED = "--mounted" in sys.argv +bpy.ops.wm.open_mainfile(filepath=blend) +exec(open(os.path.join(HERE, "eval_iou.py")).read().split("body = bpy.data.objects")[0].split("bpy.ops.wm.open_mainfile(filepath=blend)")[1]) +body = bpy.data.objects["UO_Body"] +res = {} +acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) +for act in acts: + a = int(act["uo_action"]) + if FR is None and (23 <= a <= 29) != MOUNTED: continue + rig.animation_data.action = act + for i in range(int(act["uo_frames"])): + if FR is not None and (a, i) not in FR: continue + sc.frame_set(1 + 3 * i) + for d in range(5): + rig["uo_direction"] = d; rig.update_tag(); bpy.context.view_layer.update() + dg = bpy.context.evaluated_depsgraph_get(); o = orig(a, i, d); m = raster(body, dg) + res["%d,%d,%d" % (a, i, d)] = [int((m & o).sum()), int((m | o).sum()), int((m & ~o).sum()), int((o & ~m).sum())] +json.dump(res, open(out, "w")) +vv = np.array(list(res.values())); iou = vv[:, 0] / np.maximum(vv[:, 1], 1) +print("views %d | IoU mean %.4f p10 %.4f min %.4f | outside %.1f missing %.1f" % (len(vv), iou.mean(), np.percentile(iou, 10), iou.min(), vv[:, 2].mean(), vv[:, 3].mean())) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/eval_iou.py b/third_party/UO_Model3D_v13/pipeline/body13/eval_iou.py new file mode 100644 index 0000000..96def7c --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/eval_iou.py @@ -0,0 +1,79 @@ +"""IoU of body meshes (posed by UO_Rig actions) against the original UO frames, all 5 directions. +usage: python eval_iou.py [--step N] [--mounted] +Bodies evaluated: UO_Body with corrections, UO_Body without corrections (shape keys muted), UO_Body_v13 (if present). +""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import bpy, sys, json, base64, zlib, numpy as np +blend, out = sys.argv[1], sys.argv[2] +STEP = int(sys.argv[sys.argv.index("--step") + 1]) if "--step" in sys.argv else 1 +MOUNTED = "--mounted" in sys.argv +bpy.ops.wm.open_mainfile(filepath=blend) +sc = bpy.context.scene +rig = bpy.data.objects["UO_Rig"]; rig.data.pose_position = "POSE" +cam = bpy.data.objects["UO_Camera"]; sc.camera = cam +ORIG = json.load(open(os.path.join(HERE, "..", "uo_original_frames.json")))["frames"] +def orig(a, i, d): + return np.frombuffer(zlib.decompress(base64.b64decode(ORIG["%d,%d,%d" % (a, i, d)])), np.uint8).reshape(120, 136, 4)[..., 3] > 0 + +def raster(ob, dg): + ev = ob.evaluated_get(dg); me = ev.to_mesh() + co = np.empty(len(me.vertices) * 3, np.float32); me.vertices.foreach_get("co", co); co = co.reshape(-1, 3) + me.calc_loop_triangles() + tri = np.empty(len(me.loop_triangles) * 3, np.int32); me.loop_triangles.foreach_get("vertices", tri); tri = tri.reshape(-1, 3) + Mw = np.array(ev.matrix_world); ev.to_mesh_clear() + c = cam.evaluated_get(dg) + Mc = np.array(c.calc_matrix_camera(dg, x=136, y=120)) @ np.array(c.matrix_world.inverted()) @ Mw + h = np.c_[co, np.ones(len(co))] @ Mc.T + ndc = h[:, :2] / h[:, 3:4] + P = np.stack([(ndc[:, 0] + 1) * 0.5 * 136, (1 - ndc[:, 1]) * 0.5 * 120], 1)[tri] + img = np.zeros((120, 136), bool) + mn = np.floor(P.min(1)).astype(int); mx = np.ceil(P.max(1)).astype(int) + A, B, C = P[:, 0], P[:, 1], P[:, 2] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + ok = np.abs(den) > 1e-12; size = np.clip(mx - mn, 0, 16) + for dy in range(int(size[:, 1].max(initial=0)) + 1): + for dx in range(int(size[:, 0].max(initial=0)) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px = mn[t, 0] + dx; py = mn[t, 1] + dy; cx, cy = px + 0.5, py + 0.5 + l0 = ((B[t, 1] - C[t, 1]) * (cx - C[t, 0]) + (C[t, 0] - B[t, 0]) * (cy - C[t, 1])) / den[t] + l1 = ((C[t, 1] - A[t, 1]) * (cx - C[t, 0]) + (A[t, 0] - C[t, 0]) * (cy - C[t, 1])) / den[t] + k = (l0 >= -1e-4) & (l1 >= -1e-4) & (1 - l0 - l1 >= -1e-4) & (px >= 0) & (py >= 0) & (px < 136) & (py < 120) + img[py[k], px[k]] = True + return img + +body = bpy.data.objects["UO_Body"] +v13 = bpy.data.objects.get("UO_Body_v13") +for o in bpy.data.objects: + if o.type == "MESH": + o.hide_viewport = False +keys = body.data.shape_keys.key_blocks +variants = [("v12_corr", body, False), ("v12_pure", body, True)] + ([("v13", v13, None)] if v13 else []) +res = {v[0]: {} for v in variants} +acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) +for act in acts: + a = int(act["uo_action"]) + if (23 <= a <= 29) != MOUNTED: + continue + rig.animation_data.action = act + for i in range(0, int(act["uo_frames"]), STEP): + sc.frame_set(1 + 3 * i) + for d in range(5): + rig["uo_direction"] = d; rig.update_tag(); bpy.context.view_layer.update() + dg = bpy.context.evaluated_depsgraph_get() + o = orig(a, i, d) + for name, ob, mute in variants: + if mute is not None: + for k in keys[1:]: + k.mute = mute + body.data.update(); bpy.context.view_layer.update(); dg = bpy.context.evaluated_depsgraph_get() + m = raster(ob, dg) + res[name]["%d,%d,%d" % (a, i, d)] = [int((m & o).sum()), int((m | o).sum()), int((m & ~o).sum()), int((o & ~m).sum())] +for k in keys[1:]: + k.mute = False +json.dump(res, open(out, "w")) +for name in res: + v = np.array(list(res[name].values())) + iou = v[:, 0] / np.maximum(v[:, 1], 1) + print("%-9s views %d | IoU mean %.3f p10 %.3f min %.3f | outside px/view %.1f missing px/view %.1f" + % (name, len(v), iou.mean(), np.percentile(iou, 10), iou.min(), v[:, 2].mean(), v[:, 3].mean()), flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/fastr.py b/third_party/UO_Model3D_v13/pipeline/body13/fastr.py new file mode 100644 index 0000000..09b0d67 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/fastr.py @@ -0,0 +1,98 @@ +"""fast linear blend skinning + silhouette raster (numba), same pixel rule as eval_iou.py""" +import numpy as np +from numba import njit, prange + +WIDTH, HEIGHT = 136, 120 + + +def sparse_weights(Wd, k=6): + """dense (N,B) weights -> (N,k) bone indices + weights (renormalised)""" + idx = np.argsort(-Wd, 1)[:, :k] + w = np.take_along_axis(Wd, idx, 1) + w /= np.maximum(w.sum(1, keepdims=True), 1e-9) + return idx.astype(np.int32), w.astype(np.float64) + + +@njit(parallel=True, cache=True) +def project(V, CW, idx, w): + """V (N,3) rest verts, CW (nv,B,4,4) camera@skin mats -> (nv,N,2) pixel coords""" + nv = CW.shape[0]; N = V.shape[0]; K = idx.shape[1] + out = np.empty((nv, N, 2)) + for v in prange(nv): + for n in range(N): + x = 0.0; y = 0.0; h = 0.0 + for k in range(K): + wk = w[n, k] + if wk == 0.0: + continue + M = CW[v, idx[n, k]] + x += wk * (M[0, 0] * V[n, 0] + M[0, 1] * V[n, 1] + M[0, 2] * V[n, 2] + M[0, 3]) + y += wk * (M[1, 0] * V[n, 0] + M[1, 1] * V[n, 1] + M[1, 2] * V[n, 2] + M[1, 3]) + h += wk * (M[3, 0] * V[n, 0] + M[3, 1] * V[n, 1] + M[3, 2] * V[n, 2] + M[3, 3]) + out[v, n, 0] = (x / h + 1.0) * 0.5 * 136.0 + out[v, n, 1] = (1.0 - y / h) * 0.5 * 120.0 + return out + + +@njit(cache=True) +def raster_one(S, T, img): + for t in range(T.shape[0]): + ax = S[T[t, 0], 0]; ay = S[T[t, 0], 1]; bx = S[T[t, 1], 0]; by = S[T[t, 1], 1]; cx = S[T[t, 2], 0]; cy = S[T[t, 2], 1] + den = (by - cy) * (ax - cx) + (cx - bx) * (ay - cy) + if abs(den) <= 1e-12: + continue + x0 = int(np.floor(min(ax, bx, cx))); x1 = int(np.ceil(max(ax, bx, cx))) + y0 = int(np.floor(min(ay, by, cy))); y1 = int(np.ceil(max(ay, by, cy))) + if x0 < 0: x0 = 0 + if y0 < 0: y0 = 0 + if x1 > 135: x1 = 135 + if y1 > 119: y1 = 119 + for py in range(y0, y1 + 1): + qy = py + 0.5 + for px in range(x0, x1 + 1): + qx = px + 0.5 + l0 = ((by - cy) * (qx - cx) + (cx - bx) * (qy - cy)) / den + if l0 < -1e-4: continue + l1 = ((cy - ay) * (qx - cx) + (ax - cx) * (qy - cy)) / den + if l1 < -1e-4: continue + if 1.0 - l0 - l1 < -1e-4: continue + img[py, px] = True + + +@njit(parallel=True, cache=True) +def raster(S, T): + nv = S.shape[0] + out = np.zeros((nv, 120, 136), np.bool_) + for v in prange(nv): + raster_one(S[v], T, out[v]) + return out + + +@njit(parallel=True, cache=True) +def score(S, T, masks): + """per view: intersection, union, outside, missing""" + nv = S.shape[0] + res = np.zeros((nv, 4), np.int64) + for v in prange(nv): + img = np.zeros((120, 136), np.bool_) + raster_one(S[v], T, img) + o = masks[v] + a = 0; u = 0; out = 0; mis = 0 + for y in range(120): + for x in range(136): + m = img[y, x]; g = o[y, x] + if m and g: a += 1 + if m or g: u += 1 + if m and not g: out += 1 + if g and not m: mis += 1 + res[v, 0] = a; res[v, 1] = u; res[v, 2] = out; res[v, 3] = mis + return res + + +def tris_of(faces): + T = [] + for f in faces: + f = list(f) + for j in range(1, len(f) - 1): + T.append((f[0], f[j], f[j + 1])) + return np.array(T, np.int32) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/fit_shape2.py b/third_party/UO_Model3D_v13/pipeline/body13/fit_shape2.py new file mode 100644 index 0000000..fc2f410 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/fit_shape2.py @@ -0,0 +1,90 @@ +"""regularised shape fit (keeps a natural anatomy): search along parameter axes and along grouped directions +(whole limb girth, limb taper, whole torso width / depth); penalties on limb taper / anisotropy changes and on +deviation from the measured proportions. +usage: python fit_shape2.py views.npz out.json [--init p.json] [--passes N] [--skin skel] [--sub K]""" +import sys, json, time, numpy as np +from shape13 import Shape, default_params, flat, unflat, PARTS, load_params, save_params, LIMBS +import fastr + +views, out = sys.argv[1], sys.argv[2] +arg = lambda k, d: type(d)(sys.argv[sys.argv.index(k) + 1]) if k in sys.argv else d +PASSES = arg("--passes", 8); SUB = arg("--sub", 1); REG = arg("--reg", 0.03) +d = np.load(views); bones = list(d["bones"]); sel = np.arange(0, len(d["keys"]), SUB) +S = Shape(d["U"], d["BV"], d["BDOM"], bones) +if "--skin" in sys.argv: # 55-bone skin weights (views npz holds 55 matrices per view) + from skel13 import Skel13 + r = np.load("rig_poses.npz") + K = Skel13(S, r["R"], r["parent"], bones, S.build(load_params(arg("--init", "")) if "--init" in sys.argv else None, full=True)); Wd = K.SW +else: + PWu = S.PW[S.used]; Wd = np.zeros((len(PWu), len(bones))) + for j, p in enumerate(PARTS): Wd[:, bones.index(p)] = PWu[:, j] +idx, w = fastr.sparse_weights(Wd) +CW = np.einsum("vij,vbjk->vbik", d["C"][sel], d["W"][sel]); T = fastr.tris_of(S.faces); masks = d["masks"][sel] +like = default_params() +p0 = load_params(arg("--init", "")) if "--init" in sys.argv else default_params() +x = flat(p0) +names = [] +for k in sorted(like): + names += ["%s[%d]" % (k, i) for i in range(np.size(like[k]))] +names = np.array(names) +lo = np.array([-0.05 if n.startswith("tc") else 0.6 for n in names]); hi = np.array([0.05 if n.startswith("tc") else 1.7 for n in names]) +# directions: axes + groups +D = [np.eye(len(x))[i] * (0.01 if names[i].startswith("tc") else 0.06) for i in range(len(x))] +def grp(prefix, vec): + v = np.zeros(len(x)); ii = [i for i, n in enumerate(names) if n.startswith(prefix + "[")] + v[ii] = vec; return v +for l in LIMBS: + D.append(grp(l, np.array([1, 1, 1, 1]) * 0.05)) # whole girth + D.append(grp(l, np.array([-1, 1, -1, 1]) * 0.05)) # taper + D.append(grp(l, np.array([1, 1, -1, -1]) * 0.05)) # side vs front +D.append(grp("tw", np.ones(7) * 0.04)); D.append(grp("td", np.ones(7) * 0.04)); D.append(grp("tc", np.ones(7) * 0.006)) +D.append(grp("head3", np.array([1, 1, 0]) * 0.04)) +D = np.array(D) + + +def penalty(p): + pen = 0.0 + for l in LIMBS: + g = p[l] + pen += (g[0] - g[1]) ** 2 + (g[2] - g[3]) ** 2 # taper change + pen += 0.5 * ((g[0] - g[2]) ** 2 + (g[1] - g[3]) ** 2) # anisotropy change + pen += 0.2 * np.sum((g - 1) ** 2) + pen += 5 * sum(np.sum(np.diff(p[k], 2) ** 2) for k in ("tw", "td")) + 500 * np.sum(np.diff(p["tc"], 2) ** 2) + pen += 0.2 * (np.sum((p["tw"] - 1) ** 2) + np.sum((p["td"] - 1) ** 2)) + pen += np.sum((p["neck"] - 1) ** 2) + np.sum((p["head3"] - 1) ** 2) + (p["head"][0] - 1) ** 2 + (p["footl"][0] - 1) ** 2 + return pen + + +def cost(x): + p = unflat(x) + r = fastr.score(fastr.project(S.build(p), CW, idx, w), T, masks) + iou = (r[:, 0] / np.maximum(r[:, 1], 1)).mean() + return -(iou - REG * penalty(p)), iou, r + + +f, iou, r = cost(x) +print("start IoU %.4f outside %.1f missing %.1f pen %.3f (views %d)" % (iou, r[:, 2].mean(), r[:, 3].mean(), penalty(unflat(x)), len(sel)), flush=True) +scale = 1.0; t0 = time.time() +for ps in range(PASSES): + improved = 0 + for j in np.random.RandomState(ps).permutation(len(D)): + for sgn in (1, -1): + y = np.clip(x + sgn * scale * D[j], lo, hi) + fy, iy, ry = cost(y) + if fy < f - 1e-7: + x, f, iou, r = y, fy, iy, ry; improved += 1 + while True: + y = np.clip(x + sgn * scale * D[j], lo, hi) + fy, iy, ry = cost(y) + if fy < f - 1e-7: x, f, iou, r = y, fy, iy, ry + else: break + break + print("pass %d IoU %.4f outside %.1f missing %.1f pen %.3f improved %d scale %.2f %.0fs" + % (ps, iou, r[:, 2].mean(), r[:, 3].mean(), penalty(unflat(x)), improved, scale, time.time() - t0), flush=True) + save_params(out, unflat(x), iou=float(iou)) + if improved < 4: + scale *= 0.5 + if scale < 0.1: break +p = unflat(x) +for k in sorted(p): + print("%-10s" % k, np.round(p[k], 3)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/fk.py b/third_party/UO_Model3D_v13/pipeline/body13/fk.py new file mode 100644 index 0000000..f5469db --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/fk.py @@ -0,0 +1,29 @@ +"""numpy forward kinematics matching Blender pose bones (quaternion rotation, location, full inherit)""" +import numpy as np + +def qmat(q): + w, x, y, z = q / np.linalg.norm(q) + return np.array([[1 - 2 * (y * y + z * z), 2 * (x * y - w * z), 2 * (x * z + w * y)], + [2 * (x * y + w * z), 1 - 2 * (x * x + z * z), 2 * (y * z - w * x)], + [2 * (x * z - w * y), 2 * (y * z + w * x), 1 - 2 * (x * x + y * y)]]) + +def basis(loc, rot3, scale=None): + M = np.eye(4); M[:3, :3] = rot3 if scale is None else rot3 * scale; M[:3, 3] = loc + return M + +def pose_mats(R, parent, bases): + """R (B,4,4) rest (armature space), parent idx (B,), bases (B,4,4) -> pose matrices (B,4,4) armature space""" + B = len(R); P = np.zeros((B, 4, 4)); Rinv = np.linalg.inv(R) + for b in range(B): # bones are ordered parents first + p = parent[b] + P[b] = (R[b] if p < 0 else P[p] @ Rinv[p] @ R[b]) @ bases[b] + return P + +def rig_world(d): + a = -d * np.pi / 4; c, s = np.cos(a), np.sin(a) + M = np.eye(4); M[:2, :2] = [[c, -s], [s, c]] + return M + +def skin_mats(R, parent, bases, d, Brel): + P = pose_mats(R, parent, bases) + return rig_world(d) @ P @ np.linalg.inv(R) @ Brel diff --git a/third_party/UO_Model3D_v13/pipeline/body13/gen_items.py b/third_party/UO_Model3D_v13/pipeline/body13/gen_items.py new file mode 100644 index 0000000..437236e --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/gen_items.py @@ -0,0 +1,196 @@ +"""random outfit on the v13 body: procedural items built from the body skin (shells), the cloth templates and simple +props, each fitted + bound with the user scripts (uo_fit_item / uo_bind_item presets), then rendered. +usage: gen_items.py v13.blend out_dir seed actions(comma names) [--layers] + --layers: also render every item as its own UO layer (clothing), else only the preview (LAYER = "all")""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import bpy, bmesh, sys, os, json, random, re +import numpy as np +from mathutils import Vector, Matrix + +args = [a for a in sys.argv[sys.argv.index("--") + 1:]] if "--" in sys.argv else sys.argv[-4:] +blend, out_dir, seed, only = args[0], os.path.abspath(args[1]), int(args[2]), args[3].split(",") +LAYERS = "--layers" in sys.argv +os.makedirs(out_dir, exist_ok=True) +rnd = random.Random(seed) +bpy.ops.wm.open_mainfile(filepath=blend) +sc = bpy.context.scene; rig = bpy.data.objects["UO_Rig"]; body = bpy.data.objects["UO_Body"] +rig.animation_data.action = None; rig["uo_direction"] = 0; rig.data.pose_position = "REST"; bpy.context.view_layer.update() +cl = bpy.data.collections["Clothing"] +for o in list(cl.objects): + cl.objects.unlink(o) + if not o.users_collection: sc.collection.objects.link(o) + o.hide_render = True; o.hide_viewport = True + +SUB = {"upper_arm_twist": "upper_arm", "forearm_twist": "forearm", "toe": "foot"} +def group_of(n): + s = n[-2:] if n.endswith((".L", ".R")) else "" + b = n[:-2] if s else n + return ("hand" if b.startswith("finger") else SUB.get(b, b)), s + +me = body.data +gnames = [g.name for g in body.vertex_groups] +W = np.zeros((len(me.vertices), len(gnames))) +for v in me.vertices: + for g in v.groups: W[v.index, g.group] = g.weight +dom_base = np.array([group_of(gnames[j])[0] for j in W.argmax(1)]) +dom_side = np.array([group_of(gnames[j])[1] for j in W.argmax(1)]) +CO = np.array([v.co[:] for v in me.vertices]); NO = np.array([v.normal[:] for v in me.vertices]) +bone = lambda n: rig.data.bones[n] +def bone_t(name, X): + b = bone(name); h = np.array(b.head_local); t = np.array(b.tail_local) + return ((X - h) @ (t - h)) / ((t - h) @ (t - h)) + +def uo_material(name, rgb, metal=False): + m = bpy.data.materials.new(name); m.use_nodes = True + nt = m.node_tree; out = next(n for n in nt.nodes if n.type == "OUTPUT_MATERIAL") + for n in [n for n in nt.nodes if n.type != "OUTPUT_MATERIAL"]: nt.nodes.remove(n) + grp = nt.nodes.new("ShaderNodeGroup"); grp.node_tree = bpy.data.node_groups["UO_Look"] + alb = next((i for i in grp.inputs if i.name.lower().startswith("albedo")), grp.inputs[0]) + alb.default_value = (*rgb, 1.0) + nt.links.new(grp.outputs[0], out.inputs["Surface"]) + return m + +def shell(name, keep, thick, rgb): + """item from the body skin: faces whose vertices are all kept, pushed out along the normals""" + idx = np.nonzero(keep)[0]; remap = -np.ones(len(CO), int); remap[idx] = np.arange(len(idx)) + faces = [[remap[i] for i in p.vertices] for p in me.polygons if keep[list(p.vertices)].all()] + V = CO[idx] + NO[idx] * thick + m = bpy.data.meshes.new(name); m.from_pydata(V.tolist(), [], faces); m.update() + for p in m.polygons: p.use_smooth = True + ob = bpy.data.objects.new(name, m); cl.objects.link(ob); m.materials.append(uo_material(name + "_mat", rgb)) + return ob + +def part(*bases, side=None): + k = np.isin(dom_base, bases) + if side: k &= dom_side == side + return k + +def fit_bind(ob, PART, fit=True): + for o in bpy.context.selected_objects: o.select_set(False) + ob.select_set(True); bpy.context.view_layer.objects.active = ob + if fit: + exec(compile(bpy.data.texts["uo_fit_item.py"].as_string(), "uo_fit_item.py", "exec"), {"__name__": "__main__"}) + src = bpy.data.texts["uo_bind_item.py"].as_string().replace('PART = "all"', 'PART = %r' % PART, 1) + exec(compile(src, "uo_bind_item.py", "exec"), {"__name__": "__main__"}) + +PAL = {"steel": (0.62, 0.64, 0.68), "dark": (0.22, 0.22, 0.25), "gold": (0.78, 0.6, 0.25), "red": (0.55, 0.12, 0.1), + "green": (0.18, 0.38, 0.18), "blue": (0.15, 0.25, 0.55), "leather": (0.42, 0.27, 0.15), "cloth": (0.75, 0.7, 0.58), + "purple": (0.4, 0.18, 0.45), "black": (0.08, 0.08, 0.09)} +pick = lambda *k: PAL[rnd.choice(k)] +items = [] + +# ---------------------------------------------------------------- torso +if rnd.random() < 0.6: + k = part("pelvis", "spine", "chest", "clavicle", "neck") & (CO[:, 2] < 1.62) + ob = shell("Item_ChestPlate", k, 0.03, pick("steel", "dark", "gold")); fit_bind(ob, "chest", fit=False); items.append(ob) + for s in (".L", ".R"): # pauldrons + h = np.array(bone("upper_arm" + s).head_local) + bpy.ops.mesh.primitive_uv_sphere_add(radius=0.11, location=Vector(h + np.array([0, 0, 0.03]))) + pd = bpy.context.active_object; pd.name = "Item_Pauldron" + s; pd.scale = (1.15, 1.0, 0.75) + for c in pd.users_collection: c.objects.unlink(pd) + cl.objects.link(pd); pd.data.materials.append(ob.data.materials[0]) + bpy.ops.object.select_all(action="DESELECT"); pd.select_set(True); bpy.context.view_layer.objects.active = pd + bpy.ops.object.transform_apply(location=False, rotation=False, scale=True) + fit_bind(pd, "shoulders"); items.append(pd) +else: + sleeve = rnd.choice(["short", "elbow", "long"]) + k = part("pelvis", "spine", "chest", "clavicle", "neck") & (CO[:, 2] < 1.6) + ka = np.zeros(len(CO), bool) + for s in (".L", ".R"): + ua = (dom_side == s) & (dom_base == "upper_arm"); fa = (dom_side == s) & (dom_base == "forearm") + ka |= ua & (bone_t("upper_arm" + s, CO) < (0.55 if sleeve == "short" else 2)) + if sleeve == "long": ka |= fa & (bone_t("forearm" + s, CO) < 0.85) + ob = shell("Item_Shirt", k | ka, 0.012, pick("cloth", "red", "green", "blue", "purple")); fit_bind(ob, "chest", fit=False); items.append(ob) +# ---------------------------------------------------------------- legs +lower = rnd.choice(["pants", "pants", "skirt"]) +if lower == "pants": + k = part("pelvis", "thigh", "shin") & (CO[:, 2] < 1.08) + ob = shell("Item_Pants", k, 0.012, pick("leather", "cloth", "dark", "blue")); fit_bind(ob, "legs", fit=False); items.append(ob) +else: + tpl = bpy.data.objects["UO_Template_Skirt"] + ob = bpy.data.objects.new("Item_Skirt", tpl.data.copy()); cl.objects.link(ob); ob.matrix_world = tpl.matrix_world.copy() + ob.vertex_groups.clear(); ob.data.materials.clear(); ob.data.materials.append(uo_material("skirt_mat", pick("red", "green", "blue", "purple"))) + fit_bind(ob, "skirt", fit=False); items.append(ob) +# ---------------------------------------------------------------- boots, gloves +tb = np.zeros(len(CO), bool) +for s in (".L", ".R"): + tb |= (dom_side == s) & (((dom_base == "shin") & (bone_t("shin" + s, CO) > 0.45)) | (dom_base == "foot")) +ob = shell("Item_Boots", tb, 0.015, pick("leather", "dark", "black")); fit_bind(ob, "boots", fit=False); items.append(ob) +if rnd.random() < 0.6: + tg = np.zeros(len(CO), bool) + for s in (".L", ".R"): + tg |= (dom_side == s) & (((dom_base == "forearm") & (bone_t("forearm" + s, CO) > 0.55)) | (dom_base == "hand")) + ob = shell("Item_Gloves", tg, 0.01, pick("leather", "dark", "steel")); fit_bind(ob, "gloves", fit=False); items.append(ob) +# ---------------------------------------------------------------- head: helmet or hair (+ beard) +top = CO[:, 2].max() +if rnd.random() < 0.5: + k = part("head") & (CO[:, 2] > top - 0.13) + ob = shell("Item_Helm", k, 0.022, pick("steel", "dark", "gold")); fit_bind(ob, "helm", fit=False); items.append(ob) +else: + face = (CO[:, 1] < np.percentile(CO[part("head"), 1], 35)) & (CO[:, 2] < top - 0.05) + long_ = rnd.random() < 0.5 + k = part("head") & (CO[:, 2] > top - (0.2 if long_ else 0.11)) & ~face + if long_: k |= part("neck") & (CO[:, 1] > np.median(CO[part("neck"), 1])) + ob = shell("Item_Hair", k, 0.02, pick("black", "leather", "gold")); fit_bind(ob, "hair", fit=False); items.append(ob) +# ---------------------------------------------------------------- cloak +if rnd.random() < 0.5: + tpl = bpy.data.objects["UO_Template_Cloak"] + ob = bpy.data.objects.new("Item_Cloak", tpl.data.copy()); cl.objects.link(ob); ob.matrix_world = tpl.matrix_world.copy() + ob.vertex_groups.clear(); ob.data.materials.clear(); ob.data.materials.append(uo_material("cloak_mat", pick("red", "green", "blue", "black", "purple"))) + fit_bind(ob, "cloak", fit=False); items.append(ob) +# ---------------------------------------------------------------- weapon + shield (rigid) +if rnd.random() < 0.8: + g = json.load(open(os.path.join(HERE, "grip_katana2.json"))) # grip calibrated on the UO katana frames + Mb = np.array(bone(g["bone"]).matrix_local) + grip = (Mb @ np.r_[g["grip"], 1])[:3]; ax = Mb[:3, :3] @ np.array(g["dir"]); ax /= np.linalg.norm(ax) + pz = np.cross(ax, Mb[:3, 0]); pz /= np.linalg.norm(pz) + L = rnd.choice([0.7, 0.85, 1.0]) + bm = bmesh.new() + def box(c, size, R): + vs = [] + for dx in (-0.5, 0.5): + for dy in (-0.5, 0.5): + for dz in (-0.5, 0.5): + vs.append(bm.verts.new(Vector(c + R @ (np.array([dx, dy, dz]) * size)))) + for f in ((0, 1, 3, 2), (4, 6, 7, 5), (0, 4, 5, 1), (2, 3, 7, 6), (0, 2, 6, 4), (1, 5, 7, 3)): + bm.faces.new([vs[i] for i in f]) + y = np.cross(pz, ax); R = np.stack([ax, y, pz], 1) + box(grip + ax * (0.12 + L / 2), np.array([L, 0.05, 0.012]), R) # blade + box(grip + ax * 0.1, np.array([0.03, 0.22, 0.035]), R) # cross guard + box(grip + ax * 0.02, np.array([0.16, 0.035, 0.035]), R) # grip + m = bpy.data.meshes.new("Item_Sword"); bm.to_mesh(m); bm.free() + ob = bpy.data.objects.new("Item_Sword", m); cl.objects.link(ob); m.materials.append(uo_material("sword_mat", PAL["steel"])) + fit_bind(ob, "weapon", fit=False); items.append(ob) + if rnd.random() < 0.6: + sh_ = json.load(open(os.path.join(HERE, "shield_heater.json"))) # calibrated on the UO heater shield frames + Mf = np.array(bone(sh_["bone"]).matrix_local) + c = (Mf @ np.r_[sh_["centre"], 1])[:3]; nrm = Mf[:3, :3] @ np.array(sh_["normal"]); nrm /= np.linalg.norm(nrm) + bpy.ops.mesh.primitive_cylinder_add(radius=sh_["radius"] * rnd.choice([0.8, 0.95]), depth=0.03, vertices=24, location=Vector(c)) + sh = bpy.context.active_object; sh.name = "Item_Shield" + sh.rotation_mode = "QUATERNION"; sh.rotation_quaternion = Vector((0, 0, 1)).rotation_difference(Vector(nrm)) + for cc in sh.users_collection: cc.objects.unlink(sh) + cl.objects.link(sh); sh.data.materials.append(uo_material("shield_mat", pick("red", "blue", "gold", "leather"))) + bpy.ops.object.select_all(action="DESELECT"); sh.select_set(True); bpy.context.view_layer.objects.active = sh + bpy.ops.object.transform_apply(location=True, rotation=True, scale=True) + fit_bind(sh, "shield", fit=False); items.append(sh) + +rig.data.pose_position = "POSE" +print("ITEMS", [o.name for o in items]) +bpy.ops.wm.save_as_mainfile(filepath=os.path.join(out_dir, "outfit_%d.blend" % seed), compress=True) + +def render(layer, sub, objs=None): + if objs is not None: + for o in cl.objects: o.hide_render = o not in objs + r = bpy.data.texts["render_uo_layer.py"].as_string() + r = re.sub(r'(?m)^LAYER = "clothing"', 'LAYER = %r' % layer, r, count=1) + r = re.sub(r'(?m)^ONLY = \[\]', 'ONLY = %r' % only, r, count=1) + r = r.replace('OUT_DIR = "//uo_render/"', 'OUT_DIR = %r' % (os.path.join(out_dir, sub) + "/"), 1) + r = r.replace('VD_FILE = "//uo_render/%s.vd"', 'VD_FILE = %r' % (os.path.join(out_dir, sub, "%s.vd")), 1) + exec(compile(r, "render_uo_layer.py", "exec"), {"__name__": "__main__"}) + +render("all", "preview") +if LAYERS: + for o in items: + render("clothing", "layer_" + o.name[5:], [o]) +print("GEN_DONE") diff --git a/third_party/UO_Model3D_v13/pipeline/body13/grip_katana2.json b/third_party/UO_Model3D_v13/pipeline/body13/grip_katana2.json new file mode 100644 index 0000000..c555128 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/grip_katana2.json @@ -0,0 +1,16 @@ +{ + "anim": 627, + "bone": "hand.R", + "grip": [ + -0.0067245818397671, + 0.0718225675494025, + -0.034678647474940344 + ], + "dir": [ + 0.24207559893716227, + -0.03946323640421321, + 0.9694545153702258 + ], + "length": 0.5696000000000001, + "iou": -0.8590767562676578 +} \ No newline at end of file diff --git a/third_party/UO_Model3D_v13/pipeline/body13/handfit.py b/third_party/UO_Model3D_v13/pipeline/body13/handfit.py new file mode 100644 index 0000000..90ee445 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/handfit.py @@ -0,0 +1,90 @@ +"""refine the hand rotation per frame from the original weapon / shield frames (the body silhouette cannot tell how +the fist is turned): the calibrated stick (grip json) must follow the weapon sprite (chamfer), the body silhouette +must not get worse. usage: handfit.py poses_in.json grip.json poses_out.json [--w_body 40]""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, json, numpy as np +from multiprocessing import Pool +POS_IN, GRIP, POS_OUT = sys.argv[1:4] +W_BODY = float(sys.argv[sys.argv.index("--w_body") + 1]) if "--w_body" in sys.argv else 40.0 +G = {} + + +def setup(): + sys.path.insert(0, HERE) + from itemframes import load + from shape13 import Shape, load_params + from skel13 import Skel13 + import fastr + r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]) + S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params("shape_r2.json"), full=True); V = Vf[S.used] + K = Skel13(S, r["R"], r["parent"], bones, Vf) + idx, w = fastr.sparse_weights(K.SW) + g = json.load(open(GRIP)) + G.update(r=r, v=v, K=K, V=V, idx=idx, w=w, T=fastr.tris_of(S.faces), it=load(g["anim"]), g=g, P=json.load(open(POS_IN)), + vk={tuple(int(x) for x in k): n for n, k in enumerate(v["keys"])}, fk={tuple(int(x) for x in k): n for n, k in enumerate(r["keys"])}) + + +def chamfer(M, dt, pix, p0, u, L, ns=40): + a = M @ np.r_[p0, 1]; b = M @ np.r_[p0 + u * L, 1] + A = np.array([(a[0] + 1) * 68, (1 - a[1]) * 60]); B = np.array([(b[0] + 1) * 68, (1 - b[1]) * 60]) + t = np.linspace(0, 1, ns + 1)[:, None]; Q = A + (B - A) * t + qi = np.clip(Q.astype(int), [0, 0], [135, 119]) + d1 = np.minimum(dt[qi[:, 1], qi[:, 0]], 15).mean() + e = B - A; ll = e @ e + 1e-9; tt = np.clip(((pix - A) @ e) / ll, 0, 1) + d2 = np.minimum(np.linalg.norm(A + np.outer(tt, e) - pix, axis=1), 15).mean() + return 0.5 * (d1 + d2) + + +def work(key): + from scipy.ndimage import distance_transform_edt + from itemframes import canvas + from posefit13 import Frame13 + from posefit import score_views + from fk import rig_world + r, v, K, g = G["r"], G["v"], G["K"], G["g"] + a, i = map(int, key.split(",")); x0 = np.array(G["P"][key]["x"]) + bh = K.ix[g["bone"]]; p0 = np.array(g["grip"]); u = np.array(g["dir"]); L = g["length"] + f = G["fk"][(a, i)]; vi = [G["vk"][(a, i, d)] for d in range(5)] + wm = [canvas(G["it"].get((a, d)), i)[..., 3] > 0 for d in range(5)] + dirs = [d for d in range(5) if wm[d].any()] + if not dirs: + return key, dict(G["P"][key], hand_fit=None) + DT = {d: distance_transform_edt(~wm[d]) for d in dirs}; PIX = {d: np.argwhere(wm[d])[:, ::-1] + 0.5 for d in dirs} + fr = Frame13(K, G["V"], G["idx"], G["w"], G["T"], r["Brel"], v["C"][vi], v["masks"][vi], list(range(5)), r["loc"][f], r["quat"][f]) + j0 = 3 * bh # hand rotation slots in x + def cost(x): + Sk = fr.skin(x); Ph = Sk[bh] @ K.R[bh] + ch = np.mean([chamfer(v["C"][vi[d]] @ rig_world(d) @ Ph, DT[d], PIX[d], p0, u, L) for d in dirs]) + res = score_views(fr.V, np.array([fr.C[k] @ fr.RW[k] @ Sk for k in range(5)]), fr.idx, fr.w, fr.T, fr.masks) + iou = (res[:, 0] / np.maximum(res[:, 1], 1)).mean() + return ch - W_BODY * iou, ch, iou + x = x0.copy(); f0, ch0, iou0 = cost(x); fb = f0 + for st in (0.4, 0.2, 0.1, 0.05, 0.025): + for _ in range(3): + imp = False + for jj in list(range(j0, j0 + 3)) + [3 * K.ix[g["bone"].replace("hand", "forearm")] + k for k in range(3)]: + for sg in (1, -1): + y = x.copy(); y[jj] += sg * st + fy, _, _ = cost(y) + if fy < fb - 1e-4: x, fb = y, fy; imp = True; break + if not imp: break + _, ch1, iou1 = cost(x) + rec = dict(G["P"][key]); rec["x"] = list(map(float, x)); rec["iou"] = float(iou1) + rec["hand_fit"] = dict(chamfer0=float(ch0), chamfer=float(ch1), iou0=float(iou0)) + return key, rec + + +if __name__ == "__main__": + P = json.load(open(POS_IN)); out = {} + with Pool(4, initializer=setup) as pool: + for n, (k, rec) in enumerate(pool.imap_unordered(work, sorted(P))): + out[k] = rec + if n % 30 == 0: + hf = [o["hand_fit"] for o in out.values() if o.get("hand_fit")] + if hf: print("%d/%d chamfer %.2f -> %.2f px body IoU %.4f -> %.4f" % (n + 1, len(P), np.mean([h["chamfer0"] for h in hf]), np.mean([h["chamfer"] for h in hf]), + np.mean([h["iou0"] for h in hf]), np.mean([o["iou"] for o in out.values() if o.get("hand_fit")])), flush=True) + json.dump(out, open(POS_OUT, "w")) + hf = [o["hand_fit"] for o in out.values() if o.get("hand_fit")] + print("done: chamfer %.2f -> %.2f px, body IoU %.4f -> %.4f" % (np.mean([h["chamfer0"] for h in hf]), np.mean([h["chamfer"] for h in hf]), + np.mean([h["iou0"] for h in hf]), np.mean([o["iou"] for o in out.values() if o.get("hand_fit")]))) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/horse_sdf.py b/third_party/UO_Model3D_v13/pipeline/body13/horse_sdf.py new file mode 100644 index 0000000..fb8e3b9 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/horse_sdf.py @@ -0,0 +1,103 @@ +"""signed distance grids (m, < 0 inside) of the horse proxies (rig space) -> horse_sdf.npz ++ depth-raster helpers for mounted fitting (the horse hides the rider's far side)""" +import numpy as np +from numba import njit +from scipy.ndimage import distance_transform_edt + +H = 0.02 # voxel size + + +@njit(cache=True) +def column_crossings(V, T, x0, y0, nx, ny, h, maxc): + zc = np.zeros((nx, ny, maxc)); nc = np.zeros((nx, ny), np.int32) + for t in range(T.shape[0]): + a = V[T[t, 0]]; b = V[T[t, 1]]; c = V[T[t, 2]] + den = (b[1] - c[1]) * (a[0] - c[0]) + (c[0] - b[0]) * (a[1] - c[1]) + if abs(den) < 1e-14: + continue + i0 = int(np.ceil((min(a[0], b[0], c[0]) - x0) / h - 0.5)); i1 = int(np.floor((max(a[0], b[0], c[0]) - x0) / h - 0.5)) + j0 = int(np.ceil((min(a[1], b[1], c[1]) - y0) / h - 0.5)); j1 = int(np.floor((max(a[1], b[1], c[1]) - y0) / h - 0.5)) + for i in range(max(i0, 0), min(i1, nx - 1) + 1): + px = x0 + (i + 0.5) * h + for j in range(max(j0, 0), min(j1, ny - 1) + 1): + py = y0 + (j + 0.5) * h + l0 = ((b[1] - c[1]) * (px - c[0]) + (c[0] - b[0]) * (py - c[1])) / den + l1 = ((c[1] - a[1]) * (px - c[0]) + (a[0] - c[0]) * (py - c[1])) / den + l2 = 1 - l0 - l1 + if l0 < 0 or l1 < 0 or l2 < 0: + continue + if nc[i, j] < maxc: + zc[i, j, nc[i, j]] = l0 * a[2] + l1 * b[2] + l2 * c[2]; nc[i, j] += 1 + return zc, nc + + +def sdf_grid(V, T): + lo = V.min(0) - 0.1; hi = V.max(0) + 0.1 + n = np.ceil((hi - lo) / H).astype(int) + zc, nc = column_crossings(V, T.astype(np.int64), lo[0], lo[1], n[0], n[1], H, 64) + inside = np.zeros(n, bool) + zs = lo[2] + (np.arange(n[2]) + 0.5) * H + for i in range(n[0]): + for j in range(n[1]): + k = nc[i, j] + if k < 2: + continue + z = np.sort(zc[i, j, :k]) + cnt = np.searchsorted(z, zs) # crossings below each voxel centre + inside[i, j] = cnt % 2 == 1 + d_out = distance_transform_edt(~inside) * H; d_in = distance_transform_edt(inside) * H + return lo, (d_out - d_in).astype(np.float32) + + +@njit(cache=True) +def sample(sdf, lo, h, P): + out = np.empty(P.shape[0]); nx, ny, nz = sdf.shape + for n in range(P.shape[0]): + fx = (P[n, 0] - lo[0]) / h - 0.5; fy = (P[n, 1] - lo[1]) / h - 0.5; fz = (P[n, 2] - lo[2]) / h - 0.5 + i = int(np.floor(fx)); j = int(np.floor(fy)); k = int(np.floor(fz)) + if i < 0 or j < 0 or k < 0 or i >= nx - 1 or j >= ny - 1 or k >= nz - 1: + out[n] = 1.0; continue + tx = fx - i; ty = fy - j; tz = fz - k + s = 0.0 + for di in range(2): + for dj in range(2): + for dk in range(2): + wgt = (tx if di else 1 - tx) * (ty if dj else 1 - ty) * (tz if dk else 1 - tz) + s += wgt * sdf[i + di, j + dj, k + dk] + out[n] = s + return out + + +@njit(cache=True) +def depth_raster(S, Z, T, D): + """min depth per pixel (pixel-centre rule); D preset to inf""" + for t in range(T.shape[0]): + ax = S[T[t, 0], 0]; ay = S[T[t, 0], 1]; bx = S[T[t, 1], 0]; by = S[T[t, 1], 1]; cx = S[T[t, 2], 0]; cy = S[T[t, 2], 1] + den = (by - cy) * (ax - cx) + (cx - bx) * (ay - cy) + if abs(den) <= 1e-12: + continue + x0 = max(int(np.floor(min(ax, bx, cx))), 0); x1 = min(int(np.ceil(max(ax, bx, cx))), 135) + y0 = max(int(np.floor(min(ay, by, cy))), 0); y1 = min(int(np.ceil(max(ay, by, cy))), 119) + for py in range(y0, y1 + 1): + qy = py + 0.5 + for px in range(x0, x1 + 1): + qx = px + 0.5 + l0 = ((by - cy) * (qx - cx) + (cx - bx) * (qy - cy)) / den + if l0 < -1e-4: continue + l1 = ((cy - ay) * (qx - cx) + (ax - cx) * (qy - cy)) / den + if l1 < -1e-4: continue + l2 = 1.0 - l0 - l1 + if l2 < -1e-4: continue + z = l0 * Z[T[t, 0]] + l1 * Z[T[t, 1]] + l2 * Z[T[t, 2]] + if z < D[py, px]: + D[py, px] = z + + +if __name__ == "__main__": + h = np.load("horse.npz"); out = {} + for k in h.files: + if k.startswith("v_"): + tag = k[2:]; lo, g = sdf_grid(h[k], h["t_" + tag]) + out["lo_" + tag] = lo; out["g_" + tag] = g + print(tag, g.shape, "inside voxels", (g < 0).sum(), flush=True) + np.savez_compressed("horse_sdf.npz", **out) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/itemframes.py b/third_party/UO_Model3D_v13/pipeline/body13/itemframes.py new file mode 100644 index 0000000..b401755 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/itemframes.py @@ -0,0 +1,25 @@ +"""item / body frames from the extracted .vd files on the 136x120 UO canvas (anchor 68,86) used by the originals""" +import os, sys, numpy as np +HERE = os.path.dirname(os.path.abspath(__file__)) +sys.path.insert(0, os.path.join(HERE, "..", "..", "vdtool")) +import vdtool +VD = os.path.join(HERE, "mul", "anim_%04d.vd") + + +def load(anim): + _, blocks = vdtool.read_vd(VD % anim) + return {(b["action"], b["dir"]): b for b in blocks} + + +def canvas(blk, i, anchor=(68, 86), size=(136, 120)): + img = np.zeros((size[1], size[0], 4), np.uint8) + if blk is None or not blk["frames"] or i >= len(blk["frames"]): + return img + f = blk["frames"][i] + rgba = vdtool.frame_rgba(f, blk["palette"]) + h, w = rgba.shape[:2] + x0, y0 = anchor[0] - f["cx"], anchor[1] - f["cy"] - f["h"] + ys, xs = slice(max(y0, 0), min(y0 + h, size[1])), slice(max(x0, 0), min(x0 + w, size[0])) + if ys.stop > ys.start and xs.stop > xs.start: + img[ys, xs] = rgba[ys.start - y0:ys.stop - y0, xs.start - x0:xs.stop - x0] + return img diff --git a/third_party/UO_Model3D_v13/pipeline/body13/itemval.py b/third_party/UO_Model3D_v13/pipeline/body13/itemval.py new file mode 100644 index 0000000..f5e0dd5 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/itemval.py @@ -0,0 +1,136 @@ +"""item-level validation: body-hugging shell items (offset of the body skin, same weights) rendered like +render_uo_layer (limbs / head hide the item when > MARGIN in front, EXACT_BODY: only on the original body pixels) +and compared with the real UO item sprites from anim.mul. +usage: itemval.py model(v13|v12|v12c) [--items shirt,pants,...] [--out json] [--img png] [--shape s.json --poses p.json]""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, json, base64, zlib, time, numpy as np +sys.path.insert(0, HERE) +from itemframes import load, canvas +from horse_sdf import depth_raster +from fk import rig_world +import fastr + +MODEL = sys.argv[1] +arg = lambda k, d: sys.argv[sys.argv.index(k) + 1] if k in sys.argv else d +ITEMS = { # name: (anim id, parts (UO bones, no side), thickness m, cut (bone, keep t > t0)) + "shirt": (434, ["pelvis", "spine", "chest", "clavicle", "upper_arm", "neck"], 0.012, None), + "plate": (527, ["pelvis", "spine", "chest", "clavicle", "neck"], 0.03, None), + "arms": (528, ["upper_arm", "forearm", "clavicle"], 0.025, None), + "pants": (431, ["pelvis", "thigh", "shin"], 0.012, None), + "legs": (529, ["pelvis", "thigh", "shin"], 0.03, None), + "boots": (477, ["shin", "foot"], 0.015, ("shin", 0.35)), + "gloves": (530, ["hand", "forearm"], 0.015, ("forearm", 0.55)), + "helm": (563, ["head"], 0.02, None), +} +SEL = arg("--items", ",".join(ITEMS)).split(",") +OCC = {"head", "upper_arm", "forearm", "hand", "thigh", "shin", "foot"} +MARGIN = 0.01 +ORIG = json.load(open(os.path.join(HERE, "..", "uo_original_frames.json")))["frames"] +v = np.load("views_all.npz"); keys = [tuple(int(x) for x in k) for k in v["keys"]] +SUB = {"upper_arm_twist": "upper_arm", "forearm_twist": "forearm", "toe": "foot"} + + +def base_of(n): + b = n[:-2] if n.endswith((".L", ".R")) else n + return "hand" if b.startswith("finger") else SUB.get(b, b) + + +def normals(V, F4): + a, b, c, e = V[F4[:, 0]], V[F4[:, 1]], V[F4[:, 2]], V[F4[:, 3]] + fn = np.cross(c - a, e - b); n = np.zeros_like(V) + for k in range(4): np.add.at(n, F4[:, k], fn) + return n / np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12) + + +if MODEL == "v13": + from shape13 import Shape, load_params + from skel13 import Skel13 + from posefit13 import Frame13 + r = np.load("rig_poses.npz"); bones = list(r["bones"]) + S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params(arg("--shape", "shape_r2.json")), full=True); V = Vf[S.used] + K = Skel13(S, r["R"], r["parent"], bones, Vf); P = json.load(open(arg("--poses", "poses13_r3.json"))) + names, SW, faces, R = K.names, K.SW, S.faces, K.R + fk = {tuple(int(x) for x in k): n for n, k in enumerate(r["keys"])} + def skin(n, a, i, d): + if "%d,%d" % (a, i) not in P: return None + f = fk[(a, i)] + fr = Frame13(K, None, None, None, None, r["Brel"], None, None, [], r["loc"][f], r["quat"][f]) + return fr.skin(np.array(P["%d,%d" % (a, i)]["x"])) +else: + m = np.load("v12_mesh.npz", allow_pickle=True); V = m["BV"]; SW = m["BW"] / np.maximum(m["BW"].sum(1, keepdims=True), 1e-9) + names = list(m["bones"]); faces = [list(f) for f in m["faces"]]; R = np.load("rig_poses.npz")["R"] + CORR = np.load("v12_corr.npz")["V"] if MODEL == "v12c" else None + def skin(n, a, i, d): + return np.linalg.inv(rig_world(d)) @ v["W"][n] + +F4 = np.array([f if len(f) == 4 else list(f) + [f[-1]] for f in faces]) +T = fastr.tris_of(faces) +dom = np.array([base_of(names[j]) for j in SW.argmax(1)]) +side = np.array([names[j][-2:] for j in SW.argmax(1)]) +occ_tri = T[np.isin(dom[T[:, 0]], list(OCC))] +idx, w = fastr.sparse_weights(SW) + + +def item_tris(parts, filt, Vr): + keep = np.isin(dom, parts) + if filt is not None: + bname, t0 = filt + for s in (".L", ".R"): + j = names.index(bname + s); h = R[j][:3, 3]; ax = R[j][:3, 1] + child = {"shin": "foot", "forearm": "hand"}[bname] + s + L = np.linalg.norm(R[names.index(child)][:3, 3] - h) + t = ((Vr - h) @ ax) / L + keep &= ~((dom == bname) & (side == s) & (t < t0)) + return T[keep[T].all(1)] + + +def lbs(Sk, X, Nr): + M = Sk[idx] # (N, k, 4, 4) + Mw = np.einsum("nk,nkij->nij", w, M) + Xp = np.einsum("nij,nj->ni", Mw[:, :3, :3], X) + Mw[:, :3, 3] + Np = np.einsum("nij,nj->ni", Mw[:, :3, :3], Nr) + return Xp, Np + + +def depth(Xw, Tt, C): + h = np.c_[Xw, np.ones(len(Xw))] @ C.T + D = np.full((120, 136), np.inf) + depth_raster(np.stack([(h[:, 0] + 1) * 68.0, (1 - h[:, 1]) * 60.0], 1), h[:, 2].copy(), Tt.astype(np.int32), D) + return D + + +its = {nm: load(ITEMS[nm][0]) for nm in SEL} +N0 = normals(V, F4); TR0 = {nm: item_tris(ITEMS[nm][1], ITEMS[nm][3], V) for nm in SEL} +stats = {nm: [] for nm in SEL}; imgs = {}; t0 = time.time() +for n, (a, i, d) in enumerate(keys): + Sk = skin(n, a, i, d) + if Sk is None: continue + Vr = CORR[n].astype(np.float64) if MODEL == "v12c" else V + Nr = N0 if MODEL != "v12c" else normals(Vr, F4) + Xb, Nb = lbs(Sk, Vr, Nr) + C = v["C"][n] @ rig_world(d); zs = np.linalg.norm(C[2, :3]) + Do = depth(Xb, occ_tri, C) + o = np.frombuffer(zlib.decompress(base64.b64decode(ORIG["%d,%d,%d" % (a, i, d)])), np.uint8).reshape(120, 136, 4)[..., 3] > 0 + for nm in SEL: + gt = canvas(its[nm].get((a, d)), i)[..., 3] > 0 + if not gt.any(): continue + Xi = Xb + Nb * ITEMS[nm][2] + Di = depth(Xi, TR0[nm] if MODEL != "v12c" else item_tris(ITEMS[nm][1], ITEMS[nm][3], Vr), C) + vis = np.isfinite(Di) & ~((Do < Di - MARGIN * zs) & o) + stats[nm].append(((vis & gt).sum(), (vis | gt).sum(), (vis & ~gt).sum(), (gt & ~vis).sum())) + if "--img" in sys.argv and (a, i, d) in ((9, 2, 1), (9, 3, 3), (16, 3, 0), (12, 3, 2), (0, 3, 1)): + img = np.zeros((120, 136, 3), np.uint8) + 25; img[o] = 80 + img[vis & gt] = (190, 190, 190); img[vis & ~gt] = (230, 60, 60); img[gt & ~vis] = (60, 120, 255) + imgs.setdefault(nm, []).append(np.pad(img[18:100, 34:104], ((1, 1), (1, 1), (0, 0)), constant_values=90)) + if n % 200 == 0: print("view %d/%d %.0fs" % (n, len(keys), time.time() - t0), flush=True) +res = {} +for nm in SEL: + s = np.array(stats[nm], float); iou = s[:, 0] / np.maximum(s[:, 1], 1) + res[nm] = dict(iou=float(iou.mean()), out=float(s[:, 2].mean()), miss=float(s[:, 3].mean()), n=len(s)) + print("%-7s %-4s IoU %.3f outside %.1f missing %.1f (%d views)" % (nm, MODEL, iou.mean(), s[:, 2].mean(), s[:, 3].mean(), len(s)), flush=True) +json.dump(res, open(arg("--out", "itemval_%s.json" % MODEL), "w"), indent=1) +if imgs: + from PIL import Image + big = np.concatenate([np.concatenate(r_, 1) for r_ in imgs.values()], 0) + Image.fromarray(big).resize((big.shape[1] * 2, big.shape[0] * 2), Image.NEAREST).save(arg("--img", "itemval.png")) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/make_gif.py b/third_party/UO_Model3D_v13/pipeline/body13/make_gif.py new file mode 100644 index 0000000..ac117d3 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/make_gif.py @@ -0,0 +1,43 @@ +"""animated preview: rendered item layers composited over the ORIGINAL UO body frames (and the original horse in the +mounted actions), 5 directions side by side, drawn like the client: horse, body, then the equipment layers. +usage: make_gif.py out.gif action_name layer_dir [layer_dir ...] [--scale 3] [--ms 120]""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, os, json, base64, zlib, numpy as np +from PIL import Image +args = [a for a in sys.argv[1:] if not a.startswith("--")] +opt = lambda k, d: type(d)(sys.argv[sys.argv.index(k) + 1]) if k in sys.argv else d +out, act, layers = args[0], args[1], [a for a in args[2:] if not a.replace(".", "").isdigit()] +SC = opt("--scale", 3); MS = opt("--ms", 120) +ORIG = json.load(open(os.path.join(HERE, "..", "uo_original_frames.json")))["frames"] +HORSE = os.path.join(HERE, "..", "..", "client", "horse_0xC8_frames", "frames") +HORSE_OF = {23: 0, 24: 1, 25: 2, 26: 2, 27: 2, 28: 2, 29: 2} +CW, CH, AX, AY = 182, 153, 93, 106 # horse canvas; the body canvas (136x120, anchor 68,86) sits at +25,+20 +OX, OY = AX - 68, AY - 86 +a = int(act[:2]); frames = [] +i = 0 +while "%d,%d,0" % (a, i) in ORIG: + tiles = [] + for d in range(5): + img = np.zeros((CH, CW, 3), np.uint8) + 36 + if a in HORSE_OF: + ha = HORSE_OF[a]; hf = i if ha in (0, 1) else 0 + fn = os.path.join(HORSE, "%02d_action" % ha, "dir%d" % d, "%02d.png" % hf) + if os.path.exists(fn): + h = np.array(Image.open(fn).convert("RGBA")); m = h[..., 3] > 0; img[m] = h[m, :3] + o = np.frombuffer(zlib.decompress(base64.b64decode(ORIG["%d,%d,%d" % (a, i, d)])), np.uint8).reshape(120, 136, 4) + sub_ = img[OY:OY + 120, OX:OX + 136] + m = o[..., 3] > 0; sub_[m] = o[m, :3] + order = [L for L in layers if "Cloak" not in L] + cloak = [L for L in layers if "Cloak" in L] + order = (order + cloak) if d >= 3 else (cloak + order) # the cloak is behind the body facing the camera + for L in order: + for sub in ("clothing", "all"): + fn = os.path.join(L, sub, "frames", act, "dir%d" % d, "%02d.png" % i) + if os.path.exists(fn): + it = np.array(Image.open(fn).convert("RGBA")); m = it[..., 3] > 0; sub_[m] = it[m, :3]; break + tiles.append(img[8:150, 20:162]) + frames.append(Image.fromarray(np.concatenate(tiles, 1)).resize((142 * 5 * SC, 142 * SC), Image.NEAREST)) + i += 1 +frames[0].save(out, save_all=True, append_images=frames[1:], duration=MS, loop=0, optimize=True) +print(out, len(frames), "frames") diff --git a/third_party/UO_Model3D_v13/pipeline/body13/mh/base.obj b/third_party/UO_Model3D_v13/pipeline/body13/mh/base.obj new file mode 100644 index 0000000..d26635e --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/mh/base.obj @@ -0,0 +1,59167 @@ +# This is a mesh file for MakeHuman +# +# This asset was explicitly released as CC0 in september 2020. The license +# text for CC0 can be found in the root of this repository. +# +# The copyright holders at the point of the release to CC0 were: +# +# Copyright (C) 2020 Data Collection AB, https://www.datacollection.se +# Copyright (C) 2020 Joel Palmius +# Copyright (C) 2020 Jonas Hauquier +# +# The primary legal contact for MakeHuman is Data Collection AB. +# +# For more information, see homepage at http://www.makehumancommunity.org +# +# basemesh hm08 +v -0.3492 7.3299 1.4076 +v -0.3110 7.3315 1.4107 +v -0.3481 7.3465 1.4062 +v -0.3095 7.3456 1.4117 +v -0.3487 7.3574 1.4039 +v -0.3080 7.3566 1.4103 +v -0.3835 7.3242 1.4009 +v -0.3849 7.3413 1.3972 +v -0.3886 7.3508 1.3930 +v -0.4099 7.3169 1.3895 +v -0.4154 7.3310 1.3850 +v -0.4230 7.3390 1.3777 +v -0.4279 7.3066 1.3788 +v -0.4363 7.3188 1.3727 +v -0.4462 7.3246 1.3650 +v -0.4337 7.3008 1.3734 +v -0.4473 7.3085 1.3624 +v -0.4582 7.3114 1.3514 +v -0.4385 7.2937 1.3653 +v -0.4521 7.2991 1.3548 +v -0.4638 7.3001 1.3420 +v -0.4394 7.2874 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13897/17893 13898/17894 +f 13902/17895 13901/17896 13900/17884 13899/17883 +g joint-l-finger-3-3 +f 13907/17897 13908/17898 13904/17899 13903/17900 +f 13908/17898 13909/17901 13905/17902 13904/17899 +f 13909/17901 13910/17903 13906/17904 13905/17902 +f 13910/17903 13907/17905 13903/17906 13906/17904 +f 13903/17900 13904/17899 13905/17907 13906/17908 +f 13910/17909 13909/17910 13908/17898 13907/17897 +g joint-l-finger-2-3 +f 13915/17911 13916/17912 13912/17913 13911/17914 +f 13916/17912 13917/17915 13913/17916 13912/17913 +f 13917/17915 13918/17917 13914/17918 13913/17916 +f 13918/17917 13915/17919 13911/17920 13914/17918 +f 13911/17914 13912/17913 13913/17921 13914/17922 +f 13918/17923 13917/17924 13916/17912 13915/17911 +g joint-l-finger-2-2 +f 13923/17925 13924/17926 13920/17927 13919/17928 +f 13924/17926 13925/17929 13921/17930 13920/17927 +f 13925/17929 13926/17931 13922/17932 13921/17930 +f 13926/17931 13923/17933 13919/17934 13922/17932 +f 13919/17928 13920/17927 13921/17935 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13973/18022 13972/18010 13971/18009 +g joint-l-finger-2-1 +f 13979/18023 13980/18024 13976/18025 13975/18026 +f 13980/18024 13981/18027 13977/18028 13976/18025 +f 13981/18027 13982/18029 13978/18030 13977/18028 +f 13982/18029 13979/18031 13975/18032 13978/18030 +f 13975/18026 13976/18025 13977/18033 13978/18034 +f 13982/18035 13981/18036 13980/18024 13979/18023 +g joint-l-finger-1-4 +f 13987/18037 13988/18038 13984/18039 13983/18040 +f 13988/18038 13989/18041 13985/18042 13984/18039 +f 13989/18041 13990/18043 13986/18044 13985/18042 +f 13990/18043 13987/18045 13983/18046 13986/18044 +f 13983/18040 13984/18039 13985/18047 13986/18048 +f 13990/18049 13989/18050 13988/18038 13987/18037 +g joint-l-finger-1-3 +f 13995/18051 13996/18052 13992/18053 13991/18054 +f 13996/18052 13997/18055 13993/18056 13992/18053 +f 13997/18055 13998/18057 13994/18058 13993/18056 +f 13998/18057 13995/18059 13991/18060 13994/18058 +f 13991/18054 13992/18053 13993/18061 13994/18062 +f 13998/18063 13997/18064 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14072/18193 14071/18194 +f 14076/18192 14077/18195 14073/18196 14072/18193 +f 14077/18195 14078/18197 14074/18198 14073/18196 +f 14078/18197 14075/18199 14071/18200 14074/18198 +f 14071/18194 14072/18193 14073/18201 14074/18202 +f 14078/18203 14077/18204 14076/18192 14075/18191 +g joint-l-lowerlid +f 14083/18205 14084/18206 14080/18207 14079/18208 +f 14084/18206 14085/18209 14081/18210 14080/18207 +f 14085/18209 14086/18211 14082/18212 14081/18210 +f 14086/18211 14083/18213 14079/18214 14082/18212 +f 14079/18208 14080/18207 14081/18215 14082/18216 +f 14086/18217 14085/18218 14084/18206 14083/18205 +g joint-l-eye-target +f 14091/18219 14092/18220 14088/18221 14087/18222 +f 14092/18220 14093/18223 14089/18224 14088/18221 +f 14093/18223 14094/18225 14090/18226 14089/18224 +f 14094/18225 14091/18227 14087/18228 14090/18226 +f 14087/18222 14088/18221 14089/18229 14090/18230 +f 14094/18231 14093/18232 14092/18220 14091/18219 +g joint-l-upperlid +f 14099/18233 14100/18234 14096/18235 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14120/18279 14121/18280 14125/18277 +f 14125/18279 14121/18281 14122/18282 14126/18280 +f 14126/18281 14122/18283 14119/18284 14123/18282 +f 14119/18278 14122/18277 14121/18285 14120/18286 +f 14126/18287 14123/18288 14124/18276 14125/18275 +g joint-r-toe-5-4 +f 14131/18289 14127/18290 14128/18291 14132/18292 +f 14132/18290 14128/18293 14129/18294 14133/18291 +f 14133/18293 14129/18295 14130/18296 14134/18294 +f 14134/18295 14130/18297 14127/18298 14131/18296 +f 14127/18292 14130/18291 14129/18299 14128/18300 +f 14134/18301 14131/18302 14132/18290 14133/18289 +g joint-r-toe-4-3 +f 14139/18303 14135/18304 14136/18305 14140/18306 +f 14140/18304 14136/18307 14137/18308 14141/18305 +f 14141/18307 14137/18309 14138/18310 14142/18308 +f 14142/18309 14138/18311 14135/18312 14139/18310 +f 14135/18306 14138/18305 14137/18313 14136/18314 +f 14142/18315 14139/18316 14140/18304 14141/18303 +g joint-r-toe-4-4 +f 14147/18317 14143/18318 14144/18319 14148/18320 +f 14148/18318 14144/18321 14145/18322 14149/18319 +f 14149/18321 14145/18323 14146/18324 14150/18322 +f 14150/18323 14146/18325 14143/18326 14147/18324 +f 14143/18320 14146/18319 14145/18327 14144/18328 +f 14150/18329 14147/18330 14148/18318 14149/18317 +g joint-r-toe-3-3 +f 14155/18331 14151/18332 14152/18333 14156/18334 +f 14156/18332 14152/18335 14153/18336 14157/18333 +f 14157/18335 14153/18337 14154/18338 14158/18336 +f 14158/18337 14154/18339 14151/18340 14155/18338 +f 14151/18334 14154/18333 14153/18341 14152/18342 +f 14158/18343 14155/18344 14156/18332 14157/18331 +g joint-r-toe-3-4 +f 14163/18345 14159/18346 14160/18347 14164/18348 +f 14164/18346 14160/18349 14161/18350 14165/18347 +f 14165/18349 14161/18351 14162/18352 14166/18350 +f 14166/18351 14162/18353 14159/18354 14163/18352 +f 14159/18348 14162/18347 14161/18355 14160/18356 +f 14166/18357 14163/18358 14164/18346 14165/18345 +g joint-r-toe-2-4 +f 14171/18359 14167/18360 14168/18361 14172/18362 +f 14172/18360 14168/18363 14169/18364 14173/18361 +f 14173/18363 14169/18365 14170/18366 14174/18364 +f 14174/18365 14170/18367 14167/18368 14171/18366 +f 14167/18362 14170/18361 14169/18369 14168/18370 +f 14174/18371 14171/18372 14172/18360 14173/18359 +g joint-r-toe-2-3 +f 14179/18373 14175/18374 14176/18375 14180/18376 +f 14180/18374 14176/18377 14177/18378 14181/18375 +f 14181/18377 14177/18379 14178/18380 14182/18378 +f 14182/18379 14178/18381 14175/18382 14179/18380 +f 14175/18376 14178/18375 14177/18383 14176/18384 +f 14182/18385 14179/18386 14180/18374 14181/18373 +g joint-r-toe-2-2 +f 14187/18387 14183/18388 14184/18389 14188/18390 +f 14188/18388 14184/18391 14185/18392 14189/18389 +f 14189/18391 14185/18393 14186/18394 14190/18392 +f 14190/18393 14186/18395 14183/18396 14187/18394 +f 14183/18390 14186/18389 14185/18397 14184/18398 +f 14190/18399 14187/18400 14188/18388 14189/18387 +g joint-r-toe-3-2 +f 14195/18401 14191/18402 14192/18403 14196/18404 +f 14196/18402 14192/18405 14193/18406 14197/18403 +f 14197/18405 14193/18407 14194/18408 14198/18406 +f 14198/18407 14194/18409 14191/18410 14195/18408 +f 14191/18404 14194/18403 14193/18411 14192/18412 +f 14198/18413 14195/18414 14196/18402 14197/18401 +g joint-r-toe-4-2 +f 14203/18415 14199/18416 14200/18417 14204/18418 +f 14204/18416 14200/18419 14201/18420 14205/18417 +f 14205/18419 14201/18421 14202/18422 14206/18420 +f 14206/18421 14202/18423 14199/18424 14203/18422 +f 14199/18418 14202/18417 14201/18425 14200/18426 +f 14206/18427 14203/18428 14204/18416 14205/18415 +g joint-r-toe-5-2 +f 14211/18429 14207/18430 14208/18431 14212/18432 +f 14212/18430 14208/18433 14209/18434 14213/18431 +f 14213/18433 14209/18435 14210/18436 14214/18434 +f 14214/18435 14210/18437 14207/18438 14211/18436 +f 14207/18432 14210/18431 14209/18439 14208/18440 +f 14214/18441 14211/18442 14212/18430 14213/18429 +g joint-r-toe-5-1 +f 14219/18443 14215/18444 14216/18445 14220/18446 +f 14220/18444 14216/18447 14217/18448 14221/18445 +f 14221/18447 14217/18449 14218/18450 14222/18448 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15182/20448 +f 15163/20498 15183/20452 15161/20455 15135/20499 +f 15133/20442 15149/20441 15183/20452 15163/20498 +f 15149/20441 15131/20484 15162/20453 15183/20452 +f 15262/20500 15184/20501 15153/20479 15240/20478 +f 15239/20502 15155/20503 15184/20501 15262/20500 +f 15155/20503 15134/20504 15164/20505 15184/20501 +f 15219/20506 15185/20507 15170/20508 15216/20509 +f 15215/20510 15168/20511 15185/20507 15219/20506 +f 15168/20511 15129/20512 15150/20513 15185/20507 +f 15167/20514 15186/20456 15166/20459 15141/20515 +f 15140/20516 15165/20517 15186/20456 15167/20514 +f 15165/20517 15142/20518 15169/20457 15186/20456 +f 15220/20519 15187/20460 15171/20463 15217/20520 +f 15220/20519 15172/20521 15195/20522 15223/20523 +f 15155/20524 15193/20525 15228/20526 15134/20527 +f 15236/20528 15188/20464 15173/20467 15254/20529 +f 15244/20530 15172/20521 15188/20464 15236/20528 +f 15172/20521 15145/20531 15174/20465 15188/20464 +f 15166/20459 15189/20468 15176/20471 15141/20515 +f 15143/20458 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15225/20562 +f 15316/20585 15311/20586 15202/20587 15255/20588 +f 15232/20589 15247/20568 15213/20567 15250/20590 +f 15231/20591 15230/20592 15214/20593 15227/20565 +f 15255/20588 15202/20587 15210/20594 15234/20595 +f 15224/20545 15204/20544 15212/20596 15226/20597 +f 15233/20576 15206/20575 15214/20593 15230/20592 +f 15259/20572 15199/20571 15207/20598 15248/20599 +f 15258/20555 15201/20600 15209/20601 15250/20590 +f 15256/20580 15200/20579 15208/20602 15235/20603 +f 15144/20548 15218/20489 15222/20490 15192/20549 +f 15169/20457 15219/20506 15216/20509 15143/20458 +f 15142/20518 15215/20510 15219/20506 15169/20457 +f 15172/20521 15220/20519 15217/20520 15145/20531 +f 15187/20460 15220/20519 15223/20523 15198/20552 +f 15144/20533 15177/20532 15221/20539 15218/20538 +f 15177/20532 15143/20458 15216/20509 15221/20539 +f 15305/20578 15312/20542 15224/20545 15200/20579 +f 15206/20575 15225/20562 15227/20565 15214/20593 +f 15306/20604 15313/20583 15225/20562 15206/20575 +f 15235/20603 15231/20591 15227/20565 15211/20564 +f 15200/20579 15224/20545 15226/20597 15208/20602 +f 15311/20586 15318/20581 15249/20566 15202/20587 +f 15158/20493 15251/20491 15260/20561 15194/20546 +f 15135/20558 15161/20605 15229/20496 15242/20495 +f 15161/20605 15138/20606 15243/20497 15229/20496 +f 15307/20570 15316/20585 15255/20588 15199/20571 +f 15204/20544 15233/20576 15230/20592 15212/20596 +f 15258/20555 15246/20554 15245/20607 15201/20600 +f 15248/20599 15232/20589 15250/20590 15209/20601 +f 15202/20587 15249/20566 15247/20568 15210/20594 +f 15155/20524 15239/20557 15261/20560 15193/20525 +f 15201/20600 15259/20572 15248/20599 15209/20601 +f 15135/20499 15239/20502 15262/20500 15163/20498 +f 15234/20595 15210/20594 15247/20568 15232/20589 +f 15207/20598 15234/20595 15232/20589 15248/20599 +f 15308/20608 15317/20569 15259/20572 15201/20600 +f 15163/20498 15262/20500 15240/20478 15133/20442 +f 15154/20443 15133/20442 15240/20478 15252/20477 +f 15246/20573 15233/20576 15204/20544 15245/20609 +f 15208/20602 15226/20597 15231/20591 15235/20603 +f 15315/20610 15263/20553 15205/20556 15309/20582 +f 15205/20556 15258/20555 15250/20590 15213/20567 +f 15158/20493 15137/20494 15253/20492 15251/20491 +f 15135/20558 15242/20495 15237/20547 15191/20559 +f 15132/20481 15154/20443 15252/20477 15241/20476 +f 15304/20543 15314/20611 15245/20609 15204/20544 +f 15314/20612 15308/20608 15201/20600 15245/20607 +f 15315/20613 15257/20551 15198/20552 15306/20604 +f 15144/20548 15244/20530 15236/20528 15175/20614 +f 15199/20571 15255/20588 15234/20595 15207/20598 +f 15226/20597 15212/20596 15230/20592 15231/20591 +f 15175/20614 15236/20528 15254/20529 15146/20615 +f 15203/20563 15256/20580 15235/20603 15211/20564 +f 15172/20521 15244/20530 15238/20550 15195/20522 +f 15310/20584 15319/20577 15256/20580 15203/20563 +f 15164/20536 15190/20535 15271/20616 15266/20617 +f 15170/20508 15185/20507 15270/20618 15267/20619 +f 15190/20535 15170/20508 15267/20619 15271/20616 +f 15185/20507 15150/20513 15264/20620 15270/20618 +f 15153/20479 15184/20501 15269/20621 15265/20622 +f 15150/20474 15179/20473 15268/20623 15264/20624 +f 15184/20501 15164/20505 15266/20625 15269/20621 +f 15179/20473 15153/20479 15265/20622 15268/20623 +f 15270/20618 15264/20620 15272/20626 15278/20627 +f 15268/20623 15265/20622 15273/20628 15276/20629 +f 15267/20619 15270/20618 15278/20627 15275/20630 +f 15271/20616 15267/20619 15275/20630 15279/20631 +f 15264/20624 15268/20623 15276/20629 15272/20632 +f 15269/20621 15266/20625 15274/20633 15277/20634 +f 15266/20617 15271/20616 15279/20631 15274/20635 +f 15265/20622 15269/20621 15277/20634 15273/20628 +f 15274/20635 15279/20631 15287/20636 15282/20637 +f 15273/20628 15277/20634 15285/20638 15281/20639 +f 15278/20627 15272/20626 15280/20640 15286/20641 +f 15276/20629 15273/20628 15281/20639 15284/20642 +f 15275/20630 15278/20627 15286/20641 15283/20643 +f 15279/20631 15275/20630 15283/20643 15287/20636 +f 15272/20632 15276/20629 15284/20642 15280/20644 +f 15277/20634 15274/20633 15282/20645 15285/20638 +f 15322/20646 15321/20647 15291/20648 15295/20649 +f 15324/20650 15323/20651 15292/20652 15288/20653 +f 15326/20654 15325/20655 15290/20656 15293/20657 +f 15325/20658 15322/20646 15295/20649 15290/20659 +f 15327/20660 15326/20654 15293/20657 15289/20661 +f 15328/20662 15324/20663 15288/20664 15294/20665 +f 15323/20651 15327/20660 15289/20661 15292/20652 +f 15321/20647 15328/20662 15294/20665 15291/20648 +f 15292/20652 15289/20661 15297/20666 15300/20667 +f 15291/20648 15294/20665 15302/20668 15299/20669 +f 15295/20649 15291/20648 15299/20669 15303/20670 +f 15288/20653 15292/20652 15300/20667 15296/20671 +f 15293/20657 15290/20656 15298/20672 15301/20673 +f 15290/20659 15295/20649 15303/20670 15298/20674 +f 15289/20661 15293/20657 15301/20673 15297/20666 +f 15294/20665 15288/20664 15296/20675 15302/20668 +f 15222/20490 15196/20485 15304/20543 15312/20542 +f 15261/20560 15191/20559 15307/20570 15317/20569 +f 15238/20550 15192/20549 15305/20578 15319/20577 +f 15260/20561 15197/20540 15309/20582 15318/20581 +f 15223/20523 15195/20522 15310/20584 15313/20583 +f 15237/20547 15194/20546 15311/20586 15316/20585 +f 15192/20549 15222/20490 15312/20542 15305/20578 +f 15198/20552 15223/20523 15313/20583 15306/20604 +f 15194/20546 15260/20561 15318/20581 15311/20586 +f 15191/20559 15237/20547 15316/20585 15307/20570 +f 15193/20525 15261/20560 15317/20569 15308/20608 +f 15257/20541 15315/20610 15309/20582 15197/20540 +f 15196/20485 15228/20488 15314/20611 15304/20543 +f 15228/20526 15193/20525 15308/20608 15314/20612 +f 15263/20574 15315/20613 15306/20604 15206/20575 +f 15195/20522 15238/20550 15319/20577 15310/20584 +f 15302/20668 15296/20675 15320/20676 15299/20669 +f 15300/20667 15297/20666 15320/20677 15296/20671 +f 15303/20670 15299/20669 15320/20676 15298/20674 +f 15301/20673 15298/20672 15320/20677 15297/20666 +f 15287/20636 15283/20643 15321/20647 15322/20678 +f 15280/20644 15284/20642 15323/20651 15324/20650 +f 15285/20638 15282/20645 15325/20679 15326/20680 +f 15282/20637 15287/20636 15322/20678 15325/20681 +f 15281/20639 15285/20638 15326/20680 15327/20660 +f 15286/20641 15280/20640 15324/20663 15328/20662 +f 15284/20642 15281/20639 15327/20660 15323/20651 +f 15283/20643 15286/20641 15328/20662 15321/20647 +g helper-upper-teeth +f 15080/20682 15076/20683 15061/20684 15062/20685 +f 15076/20683 15087/20686 15072/20687 15075/20688 +f 15075/20688 15072/20687 15071/20689 15074/20690 +f 15074/20690 15071/20689 15086/20691 15073/20692 +f 15073/20692 15086/20691 15079/20693 15085/20694 +f 15085/20694 15079/20693 15078/20695 15084/20696 +f 15084/20696 15078/20695 15077/20697 15083/20698 +f 15083/20698 15077/20697 15081/20699 15082/20700 +f 15070/20701 15087/20686 15076/20683 15080/20682 +f 15063/20702 15075/20688 15074/20690 15064/20703 +f 15065/20704 15073/20692 15085/20694 15066/20705 +f 15061/20684 15076/20683 15075/20688 15063/20702 +f 15067/20706 15084/20696 15083/20698 15068/20707 +f 15064/20703 15074/20690 15073/20692 15065/20704 +f 15066/20705 15085/20694 15084/20696 15067/20706 +f 15068/20707 15083/20698 15082/20700 15069/20708 +f 15087/20686 15070/20701 15088/20709 15096/20710 +f 15086/20691 15071/20689 15089/20711 15095/20712 +f 15081/20699 15077/20697 15091/20713 15094/20714 +f 15071/20689 15072/20687 15090/20715 15089/20711 +f 15079/20693 15086/20691 15095/20712 15093/20716 +f 15078/20695 15079/20693 15093/20716 15092/20717 +f 15077/20697 15078/20695 15092/20717 15091/20713 +f 15072/20687 15087/20686 15096/20710 15090/20715 +f 15110/20718 15109/20719 15106/20720 15120/20721 +f 15109/20719 15108/20722 15105/20723 15106/20720 +f 15108/20722 15107/20724 15119/20725 15105/20723 +f 15107/20724 15118/20726 15113/20727 15119/20725 +f 15118/20726 15117/20728 15112/20729 15113/20727 +f 15117/20728 15116/20730 15111/20731 15112/20729 +f 15116/20730 15115/20732 15114/20733 15111/20731 +f 15098/20734 15099/20735 15108/20722 15109/20719 +f 15100/20736 15101/20737 15118/20726 15107/20724 +f 15097/20738 15098/20734 15109/20719 15110/20718 +f 15102/20739 15103/20740 15116/20730 15117/20728 +f 15099/20735 15100/20736 15107/20724 15108/20722 +f 15101/20737 15102/20739 15117/20728 15118/20726 +f 15103/20740 15104/20741 15115/20732 15116/20730 +f 15119/20725 15127/20742 15121/20743 15105/20723 +f 15114/20733 15126/20744 15123/20745 15111/20731 +f 15105/20723 15121/20743 15122/20746 15106/20720 +f 15113/20727 15125/20747 15127/20742 15119/20725 +f 15112/20729 15124/20748 15125/20747 15113/20727 +f 15111/20731 15123/20745 15124/20748 15112/20729 +f 15106/20720 15122/20746 15128/20749 15120/20721 +f 15120/20721 15128/20749 15088/20709 15070/20701 +f 15070/20701 15080/20682 15110/20718 15120/20721 +f 15080/20682 15062/20685 15097/20738 15110/20718 +g helper-lower-teeth +f 15014/20750 14993/20751 14995/20752 15015/20753 +f 15015/20753 14995/20752 14996/20754 15016/20755 +f 15016/20755 14996/20754 14997/20756 15012/20757 +f 15012/20757 14997/20756 14998/20758 15017/20759 +f 15017/20759 14998/20758 14999/20760 15018/20761 +f 15018/20761 14999/20760 15000/20762 15019/20763 +f 15019/20763 15000/20762 15001/20764 15010/20765 +f 15013/20766 15014/20750 15002/20767 15011/20768 +f 15004/20769 15016/20755 15012/20757 15005/20770 +f 15002/20767 15014/20750 15015/20753 15003/20771 +f 14994/20772 14993/20751 15014/20750 15013/20766 +f 15007/20773 15018/20761 15019/20763 15008/20774 +f 15006/20775 15017/20759 15018/20761 15007/20773 +f 15003/20771 15015/20753 15016/20755 15004/20769 +f 15008/20774 15019/20763 15010/20765 15009/20776 +f 15005/20770 15012/20757 15017/20759 15006/20775 +f 15005/20770 15006/20775 15024/20777 15023/20778 +f 15008/20774 15009/20776 15027/20779 15026/20780 +f 15004/20769 15005/20770 15023/20778 15022/20781 +f 15007/20773 15008/20774 15026/20780 15025/20782 +f 15011/20768 15002/20767 15020/20783 15028/20784 +f 15003/20771 15004/20769 15022/20781 15021/20785 +f 15006/20775 15007/20773 15025/20782 15024/20777 +f 15002/20767 15003/20771 15021/20785 15020/20783 +f 15047/20786 15048/20787 15030/20788 15029/20789 +f 15048/20787 15049/20790 15031/20791 15030/20788 +f 15049/20790 15046/20792 15032/20793 15031/20791 +f 15046/20792 15050/20794 15033/20795 15032/20793 +f 15050/20794 15051/20796 15034/20797 15033/20795 +f 15051/20796 15052/20798 15035/20799 15034/20797 +f 15052/20798 15045/20800 15036/20801 15035/20799 +f 15013/20766 15011/20768 15037/20802 15047/20786 +f 15039/20803 15040/20804 15046/20792 15049/20790 +f 15011/20768 15028/20784 15053/20805 15037/20802 +f 15037/20802 15038/20806 15048/20787 15047/20786 +f 15042/20807 15043/20808 15052/20798 15051/20796 +f 15041/20809 15042/20807 15051/20796 15050/20794 +f 15038/20806 15039/20803 15049/20790 15048/20787 +f 15043/20808 15044/20810 15045/20800 15052/20798 +f 15040/20804 15041/20809 15050/20794 15046/20792 +f 14994/20772 15013/20766 15047/20786 15029/20789 +f 15040/20804 15056/20811 15057/20812 15041/20809 +f 15043/20808 15059/20813 15060/20814 15044/20810 +f 15039/20803 15055/20815 15056/20811 15040/20804 +f 15042/20807 15058/20816 15059/20813 15043/20808 +f 15038/20806 15054/20817 15055/20815 15039/20803 +f 15041/20809 15057/20812 15058/20816 15042/20807 +f 15037/20802 15053/20805 15054/20817 15038/20806 +g helper-l-eyelashes-2 +f 14743/20818 14796/20819 14795/20820 14744/20821 +f 14788/20822 14787/20823 14798/20824 14799/20825 +g helper-l-eyelashes-1 +f 14766/20826 14771/20827 14777/20828 14760/20829 +g helper-l-eyelashes-2 +f 14761/20830 14744/20821 14795/20820 14776/20831 +g helper-l-eyelashes-1 +f 14754/20832 14755/20833 14782/20834 14783/20835 +f 14794/20836 14768/20837 14778/20838 14759/20839 +g helper-l-eyelashes-2 +f 14748/20840 14749/20841 14788/20822 14789/20842 +f 14767/20843 14763/20844 14774/20845 14770/20846 +g helper-l-eyelashes-1 +f 14756/20847 14781/20848 14782/20834 14755/20833 +f 14757/20849 14758/20850 14779/20851 14780/20852 +g helper-l-eyelashes-2 +f 14749/20841 14750/20853 14787/20823 14788/20822 +f 14743/20818 14745/20854 14792/20855 14796/20819 +f 14762/20856 14761/20830 14776/20831 14775/20857 +g helper-l-eyelashes-1 +f 14757/20849 14780/20852 14781/20848 14756/20847 +f 14758/20850 14759/20839 14778/20838 14779/20851 +g helper-l-eyelashes-2 +f 14792/20855 14791/20858 14802/20859 14803/20860 +f 14745/20854 14746/20861 14791/20858 14792/20855 +f 14767/20843 14770/20846 14773/20862 14764/20863 +f 14770/20846 14774/20845 14772/20864 14786/20865 +g helper-l-eyelashes-1 +f 14794/20836 14760/20829 14777/20828 14768/20837 +g helper-l-eyelashes-2 +f 14791/20858 14790/20866 14801/20867 14802/20859 +f 14746/20861 14747/20868 14790/20866 14791/20858 +g helper-l-eyelashes-1 +f 14753/20869 14754/20832 14783/20835 14784/20870 +g helper-l-eyelashes-2 +f 14763/20844 14762/20856 14775/20857 14774/20845 +g helper-l-eyelashes-1 +f 14793/20871 14753/20869 14784/20870 14769/20872 +f 14793/20871 14769/20872 14785/20873 14752/20874 +g helper-l-eyelashes-2 +f 14747/20868 14748/20840 14789/20842 14790/20866 +f 14774/20845 14775/20857 14765/20875 14772/20864 +f 14796/20819 14792/20855 14803/20860 14805/20876 +f 14789/20842 14788/20822 14799/20825 14800/20877 +f 14775/20857 14776/20831 14797/20878 14765/20875 +f 14770/20846 14786/20865 14751/20879 14773/20862 +f 14796/20819 14805/20876 14804/20880 14795/20820 +f 14790/20866 14789/20842 14800/20877 14801/20867 +f 14776/20831 14795/20820 14804/20880 14797/20878 +f 14853/20881 14809/20882 14806/20883 14854/20884 +f 14851/20885 14852/20886 14812/20887 14813/20888 +f 14849/20889 14850/20890 14816/20891 14818/20892 +f 14852/20886 14848/20893 14811/20894 14812/20887 +f 14849/20889 14818/20892 14817/20895 14847/20896 +f 14846/20897 14851/20885 14813/20888 14814/20898 +f 14850/20890 14845/20899 14815/20900 14816/20891 +f 14843/20901 14844/20902 14807/20903 14808/20904 +f 14845/20899 14846/20897 14814/20898 14815/20900 +f 14855/20905 14847/20896 14817/20895 14810/20906 +f 14853/20881 14843/20901 14808/20904 14809/20882 +f 14844/20902 14855/20905 14810/20906 14807/20903 +g helper-l-eyelashes-1 +f 14768/20837 14777/20828 14822/20907 14819/20908 +f 14781/20848 14826/20909 14827/20910 14782/20834 +f 14779/20851 14778/20838 14823/20911 14824/20912 +f 14768/20837 14819/20908 14823/20911 14778/20838 +f 14780/20852 14779/20851 14824/20912 14825/20913 +f 14769/20872 14820/20914 14830/20915 14785/20873 +f 14783/20835 14782/20834 14827/20910 14828/20916 +f 14784/20870 14783/20835 14828/20916 14829/20917 +f 14769/20872 14784/20870 14829/20917 14820/20914 +f 14771/20827 14821/20918 14822/20907 14777/20828 +f 14780/20852 14825/20913 14826/20909 14781/20848 +f 14858/20919 14859/20920 14836/20921 14837/20922 +f 14856/20923 14831/20924 14835/20925 14857/20926 +f 14866/20927 14867/20928 14839/20929 14840/20930 +f 14864/20931 14832/20932 14842/20933 14865/20934 +f 14864/20931 14863/20935 14841/20936 14832/20932 +f 14863/20935 14866/20927 14840/20930 14841/20936 +f 14862/20937 14833/20938 14834/20939 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+19147 0 .073 .005 +19148 0 .186 .012 +19149 0 .195 .013 diff --git a/third_party/UO_Model3D_v13/pipeline/body13/mhlib.py b/third_party/UO_Model3D_v13/pipeline/body13/mhlib.py new file mode 100644 index 0000000..c37bef1 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/mhlib.py @@ -0,0 +1,23 @@ +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import json, numpy as np +MH = os.path.join(HERE, "mh", "") +def load_mh(muscle=0.6, male=1.0): + V, F, grp = [], [], None + for line in open(MH + "base.obj"): + if line.startswith("v "): V.append([float(x) for x in line.split()[1:4]]) + elif line.startswith("g "): grp = line.split()[1] + elif line.startswith("f ") and grp == "body": F.append([int(t.split("/")[0]) - 1 for t in line.split()[1:]]) + V = np.array(V) + def target(fn, w): + for line in open(MH + fn): + if line[0].isdigit(): + p = line.split(); V[int(p[0])] += w * np.array([float(x) for x in p[1:4]]) + target("male.target", male) + if muscle: target("universal-male-young-maxmuscle-averageweight.target", muscle) + P = V[:, [0, 2, 1]] * np.array([1.0, -1.0, 1.0]) * 0.1 # MH: Y up, dm, faces +Z -> Blender Z up, m, faces -Y + sk = json.load(open(MH + "default.mhskel")) + J = {k: P[v].mean(0) for k, v in sk["joints"].items()} + bones = {b: (J[d["head"]], J[d["tail"]], d["parent"]) for b, d in sk["bones"].items()} + W = json.load(open(MH + "default_weights.mhw"))["weights"] + return P, F, bones, W diff --git a/third_party/UO_Model3D_v13/pipeline/body13/mounted.py b/third_party/UO_Model3D_v13/pipeline/body13/mounted.py new file mode 100644 index 0000000..4187dce --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/mounted.py @@ -0,0 +1,79 @@ +"""mounted frames: the rider is seen only where it is in front of the horse (or off the horse); the body must stay out +of the horse proxy (penalty on skin inside it, deeper than a small tolerance - the proxy is a visual hull, a bit fat).""" +import numpy as np +from numba import njit +import fastr +from fastr import raster_one +from posefit13 import Frame13, EXTRA0 +from horse_sdf import sample, depth_raster, H +from fk import rig_world + +TOL = 0.04 # m of the proxy the skin may enter (visual hull is conservative) +W_PEN = 0.3 # IoU per metre of summed penetration (per vertex) + + +@njit(cache=True) +def score_occ(V, CW, idx, w, T, masks, HD): + nv = CW.shape[0]; N = V.shape[0]; K = idx.shape[1] + S = np.empty((N, 2)); Z = np.empty(N) + res = np.zeros((nv, 4)) + for v in range(nv): + for n in range(N): + x = 0.0; y = 0.0; z = 0.0 + for k in range(K): + wk = w[n, k] + if wk == 0.0: continue + M = CW[v, idx[n, k]] + x += wk * (M[0, 0] * V[n, 0] + M[0, 1] * V[n, 1] + M[0, 2] * V[n, 2] + M[0, 3]) + y += wk * (M[1, 0] * V[n, 0] + M[1, 1] * V[n, 1] + M[1, 2] * V[n, 2] + M[1, 3]) + z += wk * (M[2, 0] * V[n, 0] + M[2, 1] * V[n, 1] + M[2, 2] * V[n, 2] + M[2, 3]) + S[n, 0] = (x + 1.0) * 68.0; S[n, 1] = (1.0 - y) * 60.0; Z[n] = z + D = np.full((120, 136), np.inf) + depth_raster(S, Z, T, D) + o = masks[v]; hd = HD[v] + a = 0; u = 0; out = 0; mis = 0 + for yy in range(120): + for xx in range(136): + m = D[yy, xx] < hd[yy, xx] + g = o[yy, xx] + if m and g: a += 1 + if m or g: u += 1 + if m and not g: out += 1 + if g and not m: mis += 1 + res[v, 0] = a; res[v, 1] = u; res[v, 2] = out; res[v, 3] = mis + return res + + +def horse_depth(HV, HT, C, dirs): + out = np.full((len(dirs), 120, 136), np.inf) + for k, d in enumerate(dirs): + M = C[k] @ rig_world(d) + h = np.c_[HV, np.ones(len(HV))] @ M.T + S = np.stack([(h[:, 0] + 1) * 68.0, (1 - h[:, 1]) * 60.0], 1); Z = h[:, 2].copy() + depth_raster(S, Z, HT.astype(np.int32), out[k]) + return out + + +class MountedFrame(Frame13): + def __init__(self, *a, HV=None, HT=None, sdf=None, lo=None, pen_sel=None, **k): + super().__init__(*a, **k) + self.HD = horse_depth(HV, HT, self.C, self.dirs) + self.sdf, self.lo = sdf, lo + self.pen_sel = pen_sel # vertices tested for penetration (legs, pelvis) + + def penetration(self, S): + idx, w = self.idx[self.pen_sel], self.w[self.pen_sel]; V = self.V[self.pen_sel] + Vh = np.c_[V, np.ones(len(V))] + X = np.einsum("nk,nkij,nj->ni", w, S[idx], Vh)[:, :3] + d = sample(self.sdf, self.lo, H, X) + return np.maximum(0, -d - TOL).sum() + + def eval(self, x): + S = self.skin(x) + mats = np.array([self.C[k] @ self.RW[k] @ S for k in range(len(self.dirs))]) + res = score_occ(self.V, mats, self.idx, self.w, self.T, self.masks, self.HD) + iou = (res[:, 0] / np.maximum(res[:, 1], 1)).mean() + L = self.L + pen = self.reg_rot * np.sum(x[:60] ** 2) + self.reg_g * np.sum(x[L.o_g:L.o_e] ** 2) + 0.002 * np.sum((x[L.o_e:] - EXTRA0) ** 2) + self.last_pen = self.penetration(S) + return iou - pen - W_PEN * self.last_pen, iou, res diff --git a/third_party/UO_Model3D_v13/pipeline/body13/posefit.py b/third_party/UO_Model3D_v13/pipeline/body13/posefit.py new file mode 100644 index 0000000..f07a417 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/posefit.py @@ -0,0 +1,106 @@ +"""per-frame pose refit against the original frames (all 5 directions share one pose). +Parameters per frame: rotation vector increment per bone (on top of the start pose) + pelvis location. +Coordinate search with shrinking steps on mean IoU of the 5 views, small pull towards the start pose.""" +import numpy as np +from numba import njit +import fastr +from fastr import raster_one +from fk import qmat, rig_world + + +def rotvec(r): + th = np.linalg.norm(r) + if th < 1e-12: + return np.eye(3) + k = r / th; K = np.array([[0, -k[2], k[1]], [k[2], 0, -k[0]], [-k[1], k[0], 0]]) + return np.eye(3) + np.sin(th) * K + (1 - np.cos(th)) * K @ K + + +@njit(cache=True) +def score_views(V, CW, idx, w, T, masks): + nv = CW.shape[0]; N = V.shape[0]; K = idx.shape[1] + S = np.empty((N, 2)) + tot = 0.0 + res = np.zeros((nv, 4)) + for v in range(nv): + for n in range(N): + x = 0.0; y = 0.0 + for k in range(K): + wk = w[n, k] + if wk == 0.0: + continue + M = CW[v, idx[n, k]] + x += wk * (M[0, 0] * V[n, 0] + M[0, 1] * V[n, 1] + M[0, 2] * V[n, 2] + M[0, 3]) + y += wk * (M[1, 0] * V[n, 0] + M[1, 1] * V[n, 1] + M[1, 2] * V[n, 2] + M[1, 3]) + S[n, 0] = (x + 1.0) * 68.0; S[n, 1] = (1.0 - y) * 60.0 + img = np.zeros((120, 136), np.bool_) + raster_one(S, T, img) + o = masks[v] + a = 0; u = 0; out = 0; mis = 0 + for yy in range(120): + for xx in range(136): + m = img[yy, xx]; g = o[yy, xx] + if m and g: a += 1 + if m or g: u += 1 + if m and not g: out += 1 + if g and not m: mis += 1 + res[v, 0] = a; res[v, 1] = u; res[v, 2] = out; res[v, 3] = mis + return res + + +class Frame: + def __init__(self, V, idx, w, T, R, parent, Brel, C, masks, dirs, loc0, quat0, movable, reg=0.002): + self.V, self.idx, self.w, self.T = V, idx, w, T + self.R, self.parent, self.Brel = R, parent, Brel + self.Rinv = np.linalg.inv(R) + self.C, self.masks, self.dirs = C, masks, dirs + self.loc0, self.rot0 = loc0.copy(), np.array([qmat(q) for q in quat0]) + self.movable = movable; self.reg = reg + self.RW = [rig_world(d) for d in dirs] + self.girth_ok = [True] * len(R) + + def mats(self, x): + B = len(self.R); P = np.zeros((B, 4, 4)) + r = x[:3 * B].reshape(B, 3); dl = x[3 * B:3 * B + 3] + g = x[3 * B + 3:].reshape(B, 2) if len(x) > 3 * B + 3 else np.zeros((B, 2)) + for b in range(B): + M = np.eye(4); M[:3, :3] = self.rot0[b] @ rotvec(r[b]); M[:3, 3] = self.loc0[b] + (dl if b == 0 else 0) + p = self.parent[b] + P[b] = (self.R[b] if p < 0 else P[p] @ self.Rinv[p] @ self.R[b]) @ M + G = np.tile(np.eye(4), (B, 1, 1)); G[:, 0, 0] = np.exp(g[:, 0]); G[:, 2, 2] = np.exp(g[:, 1]) + S = P @ G @ self.Rinv @ self.Brel + return np.array([self.C[k] @ self.RW[k] @ S for k in range(len(self.dirs))]) + + def eval(self, x): + res = score_views(self.V, self.mats(x), self.idx, self.w, self.T, self.masks) + iou = (res[:, 0] / np.maximum(res[:, 1], 1)).mean() + return iou - self.reg * np.sum(x ** 2), iou, res + + def fit(self, steps=(0.12, 0.06, 0.03, 0.015, 0.008), loc_scale=0.05, passes=2, girth=False, x0=None): + B = len(self.R); x = np.zeros(3 * B + 3 + (2 * B if girth else 0)) + if x0 is not None: + x[:len(x0)] = x0 + f, iou0, _ = self.eval(x); f0 = f + free = [3 * b + k for b in range(B) if self.movable[b] for k in range(3)] + [3 * B, 3 * B + 1, 3 * B + 2] + if girth: + free += [3 * B + 3 + 2 * b + k for b in range(B) if self.girth_ok[b] for k in range(2)] + for st in steps: + for _ in range(passes): + imp = False + for i in free: + s = st * (loc_scale if 3 * B <= i < 3 * B + 3 else 1.0) + for sgn in (1, -1): + y = x.copy(); y[i] += sgn * s + fy = self.eval(y)[0] + if fy > f + 1e-6: + x, f = y, fy; imp = True + while True: + y = x.copy(); y[i] += sgn * s + fy = self.eval(y)[0] + if fy > f + 1e-6: x, f = y, fy + else: break + break + if not imp: + break + _, iou1, res = self.eval(x) + return x, iou0, iou1, res diff --git a/third_party/UO_Model3D_v13/pipeline/body13/posefit13.py b/third_party/UO_Model3D_v13/pipeline/body13/posefit13.py new file mode 100644 index 0000000..ec7799b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/posefit13.py @@ -0,0 +1,99 @@ +"""per-frame pose refit on the 55-bone v13 skeleton (5 directions share one pose). +x = [19x3 rotation increments of the UO bones | pelvis location | girth (log scale x, z) of GIRTH bones | curl.L curl.R thumb.L thumb.R toe.L toe.R] +Girth is a bone scale on local X / Z; the next bone of the chain does not inherit it (Blender: Inherit Scale = None), +leaf bones (twist, fingers, toe) do.""" +import numpy as np +from posefit import rotvec, score_views +from fk import qmat, rig_world +from skel13 import SIDES + +GIRTH = ["upper_arm.L", "forearm.L", "hand.L", "upper_arm.R", "forearm.R", "hand.R", "thigh.L", "shin.L", "foot.L", + "thigh.R", "shin.R", "foot.R", "head"] +NO_INHERIT = {"forearm.L", "hand.L", "forearm.R", "hand.R", "shin.L", "foot.L", "shin.R", "foot.R"} +EXTRA = ["curl.L", "curl.R", "thumb.L", "thumb.R", "toe.L", "toe.R"] +EXTRA0 = np.array([1.0, 1.0, 1.0, 1.0, 0.0, 0.0]) + + +class Layout: + def __init__(self, names): + self.names = names; self.n19 = 19 + self.gi = [names.index(b) for b in GIRTH] + self.o_loc = 57; self.o_g = 60; self.o_e = 60 + 2 * len(GIRTH); self.size = self.o_e + len(EXTRA) + + def zero(self): + x = np.zeros(self.size); x[self.o_e:] = EXTRA0; return x + + +class Frame13: + def __init__(self, K, V, idx, w, T, Brel, C, masks, dirs, loc0, quat0, reg_rot=0.002, reg_g=0.02): + self.K, self.V, self.idx, self.w, self.T, self.Brel = K, V, idx, w, T, Brel + self.R, self.parent = K.R, K.parent; self.Rinv = np.linalg.inv(K.R) + self.C, self.masks, self.dirs = C, masks, dirs + self.RW = [rig_world(d) for d in dirs] + self.loc0 = loc0; self.rot0 = np.array([qmat(q) for q in quat0]) + self.L = Layout(K.names); self.reg_rot, self.reg_g = reg_rot, reg_g + self.noinh = np.array([n in NO_INHERIT for n in K.names]) + + def skin(self, x): + L = self.L; K = self.K; B = len(K.names) + r = x[:57].reshape(19, 3); dl = x[57:60]; g = x[L.o_g:L.o_e].reshape(-1, 2); e = x[L.o_e:] + ext = K.extra_bases({".L": e[0], ".R": e[1]}, {".L": e[2], ".R": e[3]}, {".L": e[4], ".R": e[5]}) + G = np.tile(np.eye(4), (B, 1, 1)) + for k, b in enumerate(L.gi): + G[b, 0, 0] = np.exp(g[k, 0]); G[b, 2, 2] = np.exp(g[k, 1]) + Pn = np.zeros((B, 4, 4)); Pf = np.zeros((B, 4, 4)) + for b in range(B): + M = np.eye(4) + if b < 19: + M[:3, :3] = self.rot0[b] @ rotvec(r[b]); M[:3, 3] = self.loc0[b] + (dl if b == 0 else 0) + else: + M[:3, :3] = ext[K.names[b]] + p = self.parent[b] + if p < 0: + Pn[b] = self.R[b] @ M + else: + Pn[b] = (Pn[p] if self.noinh[b] else Pf[p]) @ self.Rinv[p] @ self.R[b] @ M + Pf[b] = Pn[b] @ G[b] + return Pf @ self.Rinv @ self.Brel + + def mats(self, x): + S = self.skin(x) + return np.array([self.C[k] @ self.RW[k] @ S for k in range(len(self.dirs))]) + + def eval(self, x): + res = score_views(self.V, self.mats(x), self.idx, self.w, self.T, self.masks) + iou = (res[:, 0] / np.maximum(res[:, 1], 1)).mean() + L = self.L + pen = self.reg_rot * np.sum(x[:60] ** 2) + self.reg_g * np.sum(x[L.o_g:L.o_e] ** 2) + 0.002 * np.sum((x[L.o_e:] - EXTRA0) ** 2) + return iou - pen, iou, res + + def fit(self, x0=None, steps=(0.12, 0.06, 0.03, 0.015, 0.008), passes=2, fix_extra=False): + L = self.L; x = L.zero() if x0 is None else x0.copy() + f, iou0, _ = self.eval(x) + free = list(range(60)) + list(range(L.o_g, L.o_e)) + ([] if fix_extra else list(range(L.o_e, L.size))) + mult = np.ones(L.size); mult[57:60] = 0.05; mult[L.o_g:L.o_e] = 0.5; mult[L.o_e:] = 2.0 + lo = np.full(L.size, -np.inf); hi = np.full(L.size, np.inf) + lo[L.o_g:L.o_e] = -0.35; hi[L.o_g:L.o_e] = 0.35 + lo[L.o_e:L.o_e + 4] = -0.2; hi[L.o_e:L.o_e + 4] = 1.2; lo[L.o_e + 4:] = -0.6; hi[L.o_e + 4:] = 0.8 + for st in steps: + for _ in range(passes): + imp = False + for i in free: + s = st * mult[i] + for sgn in (1, -1): + y = x.copy(); y[i] = np.clip(y[i] + sgn * s, lo[i], hi[i]) + if y[i] == x[i]: continue + fy = self.eval(y)[0] + if fy > f + 1e-6: + x, f = y, fy; imp = True + while True: + y = x.copy(); y[i] = np.clip(y[i] + sgn * s, lo[i], hi[i]) + if y[i] == x[i]: break + fy = self.eval(y)[0] + if fy > f + 1e-6: x, f = y, fy + else: break + break + if not imp: + break + _, iou1, res = self.eval(x) + return x, iou0, iou1, res diff --git a/third_party/UO_Model3D_v13/pipeline/body13/poses13_m3.json b/third_party/UO_Model3D_v13/pipeline/body13/poses13_m3.json new file mode 100644 index 0000000..05e0e8b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/poses13_m3.json @@ -0,0 +1 @@ +{"23,3": {"x": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.12, 0.0, 0.12, 0.052, 0.0, -0.03, -0.11199999999999999, -0.03, -0.12, 0.0, 0.0, 0.0, -0.11199999999999999, 0.0, 0.03, 0.03, 0.0, 0.0, 0.0, 0.0, -0.12, 0.12, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.12, 0.105, 0.12, 0.0, 0.0, 0.0, 0.12, 0.0, 0.0, 0.0, -0.12, 0.0, 0.06, -0.12, 0.0, -0.12, -0.21, 0.0, 0.0, 0.27, 0.24, 0.0, -0.018000000000000002, -0.006, -0.011, -0.03, 0.0, -0.135, 0.0, 0.0, 0.22099999999999997, 0.0, 0.026, 0.0, 0.0, 0.0, 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/dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/prep_views.py @@ -0,0 +1,43 @@ +"""from stage1_bound.blend: UO reference (v12 skeleton + mesh) and per-view skinning matrices / camera / original masks""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import bpy, sys, json, base64, zlib, numpy as np +bpy.ops.wm.open_mainfile(filepath=sys.argv[1]); out = sys.argv[2] +ACTS = [int(x) for x in sys.argv[3].split(",")]; STEP = int(sys.argv[4]) +sc = bpy.context.scene; rig = bpy.data.objects["UO_Rig"]; body = bpy.data.objects["UO_Body"]; v13 = bpy.data.objects["UO_Body_v13"] +cam = bpy.data.objects["UO_Camera"]; sc.camera = cam +ORIG = json.load(open(os.path.join(HERE, "..", "uo_original_frames.json")))["frames"] +bones = [b.name for b in rig.data.bones] +# reference data (rest) +rig.data.pose_position = "REST"; bpy.context.view_layer.update() +M = body.matrix_world.inverted() @ rig.matrix_world +U = np.array([[np.array(M @ b.head_local), np.array(M @ b.tail_local)] for b in rig.data.bones]) +kb = body.data.shape_keys.key_blocks["Basis"]; BV = np.array([k.co[:] for k in kb.data]) +names = [g.name for g in body.vertex_groups]; BW = np.zeros((len(BV), len(names))) +for v in body.data.vertices: + for g in v.groups: BW[v.index, g.group] = g.weight +BDOM = np.array([names[i] for i in BW.argmax(1)]) +rig.data.pose_position = "POSE" +Wm, Cm, masks, keys = [], [], [], [] +acts = {int(a["uo_action"]): a for a in bpy.data.actions if "uo_action" in a} +for a in ACTS: + if a not in acts: continue + act = acts[a]; rig.animation_data.action = act + for i in range(0, int(act["uo_frames"]), STEP): + sc.frame_set(1 + 3 * i) + for d in range(5): + rig["uo_direction"] = d; rig.update_tag(); bpy.context.view_layer.update() + dg = bpy.context.evaluated_depsgraph_get() + re = rig.evaluated_get(dg); rmw = re.matrix_world; bmw = v13.evaluated_get(dg).matrix_world + mats = [] + for bn in bones: + pb = re.pose.bones[bn]; bone = re.data.bones[bn] + mats.append(np.array(rmw @ pb.matrix @ bone.matrix_local.inverted() @ rmw.inverted() @ bmw)) + Wm.append(mats) + c = cam.evaluated_get(dg) + Cm.append(np.array(c.calc_matrix_camera(dg, x=136, y=120)) @ np.array(c.matrix_world.inverted())) + masks.append(np.frombuffer(zlib.decompress(base64.b64decode(ORIG["%d,%d,%d" % (a, i, d)])), np.uint8).reshape(120, 136, 4)[..., 3] > 0) + keys.append((a, i, d)) +np.savez_compressed(out, W=np.array(Wm), C=np.array(Cm), masks=np.array(masks), keys=np.array(keys), bones=np.array(bones), + U=U, BV=BV, BDOM=BDOM, v13_mw=np.array(v13.matrix_world)) +print("views", len(keys)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/rig_poses.npz b/third_party/UO_Model3D_v13/pipeline/body13/rig_poses.npz new file mode 100644 index 0000000..61084e1 Binary files /dev/null and b/third_party/UO_Model3D_v13/pipeline/body13/rig_poses.npz differ diff --git a/third_party/UO_Model3D_v13/pipeline/body13/run_cloth.py b/third_party/UO_Model3D_v13/pipeline/body13/run_cloth.py new file mode 100644 index 0000000..efadaa8 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/run_cloth.py @@ -0,0 +1,55 @@ +"""fit a cloth chain rig to an item animation for every non-mounted frame (actions in parallel, frames in order, +each frame starts from the previous one). usage: run_cloth.py shape.json poses.json ANIM out.json""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, json, time, numpy as np +from multiprocessing import Pool +sys.path.insert(0, HERE) +SHAPE, POSES, ANIM, OUT = sys.argv[1], sys.argv[2], int(sys.argv[3]), sys.argv[4] +G = {} +from cloth13 import make_cloth, KINDS + + +def setup(): + from shape13 import Shape, load_params + from skel13 import Skel13 + import fastr + from itemframes import load + r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]) + S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params(SHAPE), full=True); V = Vf[S.used] + K = Skel13(S, r["R"], r["parent"], bones, Vf) + kind, zt, zh = KINDS[ANIM] + rig, CV, CF, CW, top, par = make_cloth(K, V, kind, zt, zh, faces=S.faces) + G.update(r=r, v=v, V=V, K=K, T=fastr.tris_of(S.faces), rig=rig, CV=CV, CF=CF, CW=CW, par=par, it=load(ANIM), + P=json.load(open(POSES)), vk={tuple(k): n for n, k in enumerate(v["keys"])}, fk={tuple(k): n for n, k in enumerate(r["keys"])}) + + +def work(a): + from posefit13 import Frame13 + from clothfit import ClothFrame + from itemframes import canvas + r, v = G["r"], G["v"]; out = {}; x = np.zeros(len(G["rig"].names) * 2) + i = 0 + while "%d,%d" % (a, i) in G["P"]: + f = G["fk"][(a, i)] + fr = Frame13(G["K"], None, None, None, None, r["Brel"], None, None, [], r["loc"][f], r["quat"][f]) + Sb = fr.skin(np.array(G["P"]["%d,%d" % (a, i)]["x"])) + vi = [G["vk"][(a, i, d)] for d in range(5)] + masks = np.array([canvas(G["it"].get((a, d)), i)[..., 3] > 0 for d in range(5)]) + cf = ClothFrame(G["rig"], G["CV"], G["CF"], G["CW"], Sb, G["K"], G["V"], G["T"], v["C"][vi], list(range(5)), masks, G["par"], + prev=x.copy() if i > 0 else None) + x = cf.fit(x) + out["%d,%d" % (a, i)] = {"x": list(map(float, x)), "iou": float(cf.last["iou"]), "pen": float(cf.last["pen"])} + i += 1 + return out + + +if __name__ == "__main__": + P = json.load(open(POSES)); acts = sorted({int(k.split(",")[0]) for k in P}) + res = {}; t = time.time() + with Pool(4, initializer=setup) as pool: + for o in pool.imap_unordered(work, acts): + res.update(o) + print("%d frames mean IoU %.4f pen %.3f %.0fs" % (len(res), np.mean([q["iou"] for q in res.values()]), np.mean([q["pen"] for q in res.values()]), time.time() - t), flush=True) + json.dump(res, open(OUT, "w")) + print("done", ANIM, len(res), "frames mean IoU %.4f" % np.mean([q["iou"] for q in res.values()])) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/run_cloth_mounted.py b/third_party/UO_Model3D_v13/pipeline/body13/run_cloth_mounted.py new file mode 100644 index 0000000..6485f0b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/run_cloth_mounted.py @@ -0,0 +1,86 @@ +"""fit the cloth chains in the mounted actions (23-29): horse occlusion + no penetration of the horse proxy. +usage: run_cloth_mounted.py shape.json poses_mounted.json ANIM out.json""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, json, time, numpy as np +from multiprocessing import Pool +sys.path.insert(0, HERE) +SHAPE, POSES, ANIM, OUT = sys.argv[1], sys.argv[2], int(sys.argv[3]), sys.argv[4] +from cloth13 import make_cloth, KINDS +G = {} +W_PEN_M = float(sys.argv[sys.argv.index("--w_pen") + 1]) if "--w_pen" in sys.argv else 3.0 # leg penetration weight +W_HORSE_M = float(sys.argv[sys.argv.index("--w_horse") + 1]) if "--w_horse" in sys.argv else 3.0 +REG_M = float(sys.argv[sys.argv.index("--reg") + 1]) if "--reg" in sys.argv else 0.002 # pull to the thigh start + + +def setup(): + from shape13 import Shape, load_params + from skel13 import Skel13 + import fastr + from itemframes import load + r = np.load("rig_poses.npz"); v = np.load("views_mounted.npz"); bones = list(r["bones"]) + S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params(SHAPE), full=True); V = Vf[S.used] + K = Skel13(S, r["R"], r["parent"], bones, Vf) + rig, CV, CF, CW, top, par = make_cloth(K, V, *KINDS[ANIM], faces=S.faces) + G.update(r=r, v=v, V=V, K=K, T=fastr.tris_of(S.faces), rig=rig, CV=CV, CF=CF, CW=CW, par=par, it=load(ANIM), + P=json.load(open(POSES)), hs=np.load("horse_sdf.npz"), hm=np.load("horse.npz"), + vk={tuple(int(x) for x in k): n for n, k in enumerate(v["keys"])}, fk={tuple(int(x) for x in k): n for n, k in enumerate(r["keys"])}) + + +def thigh_init(rig, K, Sb): + """skirt on horseback: front / side chains start along the thigh of their side, the back ones hang down""" + from cloth13 import rotxz + if rig.prefix != "skirt": + return np.zeros(len(rig.names) * 2) + x = np.zeros((rig.nc, rig.ns, 2)) + pb = K.ix["pelvis"]; Ppel = Sb[pb] @ K.R[pb]; base = Ppel @ np.linalg.inv(K.R[pb]) + for k in range(rig.nc): + b0 = rig.bone(k, 0); R0 = base @ rig.R[b0] + out = rig.R[b0][:3, 2] # outward (rest) + if out[1] > 0.5: # back of the skirt: hang down + continue + side = ".L" if out[0] >= 0 else ".R" + th = K.ix["thigh" + side]; d = (Sb[th] @ K.R[th])[:3, 1] + if abs(out[0]) < 0.3: # front middle: between both thighs + d = d + (Sb[K.ix["thigh.R" if side == ".L" else "thigh.L"]] @ K.R[K.ix["thigh.R" if side == ".L" else "thigh.L"]])[:3, 1] + t = np.linalg.inv(R0[:3, :3]) @ (d / np.linalg.norm(d)) + az = np.arcsin(np.clip(-t[0], -1, 1)); ax = np.arctan2(t[2], t[1]) + x[k, 0] = (ax, az) + return x.ravel() + + +def work(a): + from posefit13 import Frame13 + from clothfit import MountedClothFrame + from itemframes import canvas + r, v = G["r"], G["v"]; out = {}; x = np.zeros(len(G["rig"].names) * 2) + i = 0 + while "%d,%d" % (a, i) in G["P"]: + f = G["fk"][(a, i)]; tag = "%d_%d" % (a, i) + fr = Frame13(G["K"], None, None, None, None, r["Brel"], None, None, [], r["loc"][f], r["quat"][f]) + Sb = fr.skin(np.array(G["P"]["%d,%d" % (a, i)]["x"])) + vi = [G["vk"][(a, i, d)] for d in range(5)] + masks = np.array([canvas(G["it"].get((a, d)), i)[..., 3] > 0 for d in range(5)]) + cf = MountedClothFrame(G["rig"], G["CV"], G["CF"], G["CW"], Sb, G["K"], G["V"], G["T"], v["C"][vi], list(range(5)), masks, G["par"], + prev=x.copy() if i > 0 else None, HV=G["hm"]["v_" + tag], HT=G["hm"]["t_" + tag], + sdf=G["hs"]["g_" + tag], lo=G["hs"]["lo_" + tag], w_pen=W_PEN_M, w_horse=W_HORSE_M) + xi = thigh_init(G["rig"], G["K"], Sb) + if G["rig"].prefix == "skirt": + cf.xref = xi; cf.reg = REG_M + cands = [xi] + ([x] if i > 0 else []) + x = max(cands, key=lambda c: cf.eval(c)[0]) + x = cf.fit(x) + out["%d,%d" % (a, i)] = {"x": list(map(float, x)), "iou": float(cf.last["iou"]), "pen": float(cf.last["pen"]), "hpen": float(cf.last["hpen"])} + i += 1 + return out + + +if __name__ == "__main__": + P = json.load(open(POSES)); acts = sorted({int(k.split(",")[0]) for k in P}) + res = {}; t = time.time() + with Pool(4, initializer=setup) as pool: + for o in pool.imap_unordered(work, acts): + res.update(o) + print("%d frames mean IoU %.4f horse pen %.3f %.0fs" % (len(res), np.mean([q["iou"] for q in res.values()]), np.mean([q["hpen"] for q in res.values()]), time.time() - t), flush=True) + json.dump(res, open(OUT, "w")) + print("done", ANIM, len(res), "frames mean IoU %.4f" % np.mean([q["iou"] for q in res.values()])) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/run_mounted13.py b/third_party/UO_Model3D_v13/pipeline/body13/run_mounted13.py new file mode 100644 index 0000000..868f4ff --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/run_mounted13.py @@ -0,0 +1,48 @@ +"""refit every mounted frame (actions 23-29) on the 55-bone rig with horse occlusion + no-penetration. +usage: run_mounted13.py shape.json out.json [--init poses.json]""" +import sys, json, time, numpy as np +from multiprocessing import Pool +SHAPE, OUT = sys.argv[1], sys.argv[2] +INIT = sys.argv[sys.argv.index("--init") + 1] if "--init" in sys.argv else None +G = {} + +def setup(): + from shape13 import Shape, load_params + from skel13 import Skel13 + import fastr + r = np.load("rig_poses.npz"); v = np.load("views_mounted.npz"); bones = list(r["bones"]) + S = Shape(v["U"], v["BV"], v["BDOM"], bones) + Vf = S.build(load_params(SHAPE), full=True); V = Vf[S.used] + K = Skel13(S, r["R"], r["parent"], bones, Vf) + idx, w = fastr.sparse_weights(K.SW); T = fastr.tris_of(S.faces) + legs = [K.ix[n] for n in K.names if n.startswith(("thigh", "shin", "foot", "toe", "pelvis"))] + G.update(r=r, v=v, V=V, K=K, idx=idx, w=w, T=T, vk={tuple(k): n for n, k in enumerate(v["keys"])}, + pen_sel=np.nonzero(K.SW[:, legs].sum(1) > 0.5)[0], hs=np.load("horse_sdf.npz"), hm=np.load("horse.npz"), + init=json.load(open(INIT)) if INIT else {}) + +def work(key): + from mounted import MountedFrame + a, i = key; r, v = G["r"], G["v"] + f = [n for n, k in enumerate(r["keys"]) if tuple(k) == (a, i)][0] + vi = [G["vk"][(a, i, d)] for d in range(5)]; tag = "%d_%d" % (a, i) + fr = MountedFrame(G["K"], G["V"], G["idx"], G["w"], G["T"], r["Brel"], v["C"][vi], v["masks"][vi], list(range(5)), r["loc"][f], r["quat"][f], + HV=G["hm"]["v_" + tag], HT=G["hm"]["t_" + tag], sdf=G["hs"]["g_" + tag], lo=G["hs"]["lo_" + tag], pen_sel=G["pen_sel"]) + k = "%d,%d" % (a, i) + x0 = np.array(G["init"][k]["x"]) if k in G["init"] else None + fr.eval(fr.L.zero() if x0 is None else x0); p0 = fr.last_pen + x, i0, i1, res = fr.fit(x0=x0); fr.eval(x) + return k, {"x": list(map(float, x)), "iou0": float(i0), "iou": float(i1), "res": res.tolist(), "pen0": float(p0), "pen": float(fr.last_pen)} + +if __name__ == "__main__": + v = np.load("views_mounted.npz") + keys = sorted({(int(a), int(i)) for a, i, d in v["keys"]}) + out = {}; t = time.time() + with Pool(4, initializer=setup) as pool: + for n, (k, rr) in enumerate(pool.imap_unordered(work, keys)): + out[k] = rr + if n % 10 == 0: + print("%d/%d mean IoU %.4f -> %.4f pen %.3f -> %.3f %.0fs" % (n + 1, len(keys), np.mean([o["iou0"] for o in out.values()]), + np.mean([o["iou"] for o in out.values()]), np.mean([o["pen0"] for o in out.values()]), np.mean([o["pen"] for o in out.values()]), time.time() - t), flush=True) + json.dump(out, open(OUT, "w")) + print("done %d frames mean IoU %.4f -> %.4f pen %.3f -> %.3f %.0fs" % (len(out), np.mean([o["iou0"] for o in out.values()]), np.mean([o["iou"] for o in out.values()]), + np.mean([o["pen0"] for o in out.values()]), np.mean([o["pen"] for o in out.values()]), time.time() - t)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/run_poses.py b/third_party/UO_Model3D_v13/pipeline/body13/run_poses.py new file mode 100644 index 0000000..8bfa5ca --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/run_poses.py @@ -0,0 +1,43 @@ +"""refit the pose of every non-mounted frame (multiprocessing). usage: run_poses.py shape.json out.json [--init poses.json] [--girth]""" +import sys, json, time, numpy as np +from multiprocessing import Pool +SHAPE, OUT = sys.argv[1], sys.argv[2] +INIT = sys.argv[sys.argv.index("--init") + 1] if "--init" in sys.argv else None +GIRTH = "--girth" in sys.argv +G = {} + +def setup(): + from shape13 import Shape, PARTS, unflat, load_params + import fastr + r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]) + S = Shape(v["U"], v["BV"], v["BDOM"], bones) + V = np.load(SHAPE)["V"] if SHAPE.endswith(".npz") else S.build(load_params(SHAPE)) + W13 = np.zeros((len(V), len(bones))) + for j, q in enumerate(PARTS): W13[:, bones.index(q)] = S.PW[S.used][:, j] + idx, w = fastr.sparse_weights(W13); T = fastr.tris_of(S.faces) + G.update(r=r, v=v, V=V, idx=idx, w=w, T=T, vk={tuple(k): n for n, k in enumerate(v["keys"])}, + init=json.load(open(INIT)) if INIT else {}) + +def work(key): + from posefit import Frame + a, i = key; r, v = G["r"], G["v"] + f = [n for n, k in enumerate(r["keys"]) if tuple(k) == (a, i)][0] + vi = [G["vk"][(a, i, d)] for d in range(5)] + fr = Frame(G["V"], G["idx"], G["w"], G["T"], r["R"], r["parent"], r["Brel"], v["C"][vi], v["masks"][vi], list(range(5)), + r["loc"][f], r["quat"][f], movable=[True] * len(r["bones"])) + x0 = np.array(G["init"]["%d,%d" % (a, i)]["x"]) if "%d,%d" % (a, i) in G["init"] else None + t = time.time(); x, i0, i1, res = fr.fit(girth=GIRTH, x0=x0) + return "%d,%d" % (a, i), {"x": list(map(float, x)), "iou0": float(i0), "iou": float(i1), "res": res.tolist()} + +if __name__ == "__main__": + v = np.load("views_all.npz") + keys = sorted({(int(a), int(i)) for a, i, d in v["keys"]}) + out = {}; t = time.time() + with Pool(4, initializer=setup) as pool: + for n, (k, rr) in enumerate(pool.imap_unordered(work, keys)): + out[k] = rr + if n % 20 == 0: + print("%d/%d mean IoU %.4f -> %.4f %.0fs" % (n + 1, len(keys), np.mean([o["iou0"] for o in out.values()]), + np.mean([o["iou"] for o in out.values()]), time.time() - t), flush=True) + json.dump(out, open(OUT, "w")) + print("done %d frames mean IoU %.4f -> %.4f %.0fs" % (len(out), np.mean([o["iou0"] for o in out.values()]), np.mean([o["iou"] for o in out.values()]), time.time() - t)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/run_poses13.py b/third_party/UO_Model3D_v13/pipeline/body13/run_poses13.py new file mode 100644 index 0000000..7fa095f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/run_poses13.py @@ -0,0 +1,53 @@ +"""refit every non-mounted frame on the 55-bone rig. usage: run_poses13.py shape.json out.json [--init poses.json] [--fix-extra] [--frames a,i;a,i]""" +import sys, json, time, numpy as np +from multiprocessing import Pool +SHAPE, OUT = sys.argv[1], sys.argv[2] +INIT = sys.argv[sys.argv.index("--init") + 1] if "--init" in sys.argv else None +G = {} + +def setup(): + from shape13 import Shape, load_params + from skel13 import Skel13 + import fastr + r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]) + S = Shape(v["U"], v["BV"], v["BDOM"], bones) + Vf = S.build(load_params(SHAPE), full=True); V = Vf[S.used] + K = Skel13(S, r["R"], r["parent"], bones, Vf) + idx, w = fastr.sparse_weights(K.SW); T = fastr.tris_of(S.faces) + G.update(r=r, v=v, V=V, K=K, idx=idx, w=w, T=T, vk={tuple(k): n for n, k in enumerate(v["keys"])}, + init=json.load(open(INIT)) if INIT else {}) + +def convert(x, L, names): + """old 19-bone layout (rot, loc, girth for all 19) -> 55-bone layout""" + if len(x) == L.size: return np.array(x) + y = L.zero(); x = np.array(x); y[:60] = x[:60] + if len(x) > 60: + g = x[60:].reshape(19, 2) + for k, b in enumerate(L.gi): y[L.o_g + 2 * k:L.o_g + 2 * k + 2] = g[b] + return y + +def work(key): + from posefit13 import Frame13 + a, i = key; r, v = G["r"], G["v"] + f = [n for n, k in enumerate(r["keys"]) if tuple(k) == (a, i)][0] + vi = [G["vk"][(a, i, d)] for d in range(5)] + fr = Frame13(G["K"], G["V"], G["idx"], G["w"], G["T"], r["Brel"], v["C"][vi], v["masks"][vi], list(range(5)), r["loc"][f], r["quat"][f]) + k = "%d,%d" % (a, i) + x0 = convert(G["init"][k]["x"], fr.L, G["K"].names) if k in G["init"] else None + x, i0, i1, res = fr.fit(x0=x0, fix_extra="--fix-extra" in sys.argv) + return k, {"x": list(map(float, x)), "iou0": float(i0), "iou": float(i1), "res": res.tolist()} + +if __name__ == "__main__": + v = np.load("views_all.npz") + keys = sorted({(int(a), int(i)) for a, i, d in v["keys"]}) + if "--frames" in sys.argv: + keys = [tuple(map(int, s.split(","))) for s in sys.argv[sys.argv.index("--frames") + 1].split(";")] + out = {}; t = time.time() + with Pool(4, initializer=setup) as pool: + for n, (k, rr) in enumerate(pool.imap_unordered(work, keys)): + out[k] = rr + if n % 20 == 0 or len(keys) < 20: + print("%d/%d mean IoU %.4f -> %.4f %.0fs" % (n + 1, len(keys), np.mean([o["iou0"] for o in out.values()]), + np.mean([o["iou"] for o in out.values()]), time.time() - t), flush=True) + json.dump(out, open(OUT, "w")) + print("done %d frames mean IoU %.4f -> %.4f %.0fs" % (len(out), np.mean([o["iou0"] for o in out.values()]), np.mean([o["iou"] for o in out.values()]), time.time() - t)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/shape13.py b/third_party/UO_Model3D_v13/pipeline/body13/shape13.py new file mode 100644 index 0000000..baa9ede --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/shape13.py @@ -0,0 +1,242 @@ +"""v13 body shape generator (pure numpy, no Blender): MakeHuman male -> UO proportions with tunable multipliers. + +Same construction as mh_stage1.py (limb segment transforms, torso height map, neck, head, blended with the MakeHuman +part weights), plus parameters on top of the measured values: + limb girth at the proximal / distal end (linear along the bone), two radial axes (side / front-back), + torso width / depth / centre per height level, neck width / depth, head scale. +build(params) -> (N,3) vertices in UO_Body local space (rest pose of the v12 skeleton). +""" +import json, numpy as np +from scipy.spatial import cKDTree +from mhlib import load_mh, MH + +LIMBS = ["upper_arm", "forearm", "hand", "thigh", "shin", "foot"] +NLEV = 7 +PARTS = ["pelvis", "spine", "chest", "neck", "head"] + [p + s for s in (".L", ".R") for p in ("clavicle", "upper_arm", "forearm", "hand", "thigh", "shin", "foot")] +PI = {p: i for i, p in enumerate(PARTS)} + + +def default_params(): + p = {} + for l in LIMBS: + p[l] = np.array([1.0, 1.0, 1.0, 1.0]) # girth proximal side, distal side, proximal front, distal front + p["tw"] = np.ones(NLEV); p["td"] = np.ones(NLEV); p["tc"] = np.zeros(NLEV) # torso width, depth, centre shift (m) + p["neck"] = np.array([1.0, 1.0]); p["head"] = np.array([1.0]) + p["head3"] = np.array([1.0, 1.0, 1.0]) # head width, depth, height on top of the head scale + p["footl"] = np.array([1.0]) # foot length + return p + + +OLD_KEYS = ["foot", "forearm", "hand", "head", "neck", "shin", "tc", "td", "thigh", "tw", "upper_arm"] + + +def load_params(fn): + """json with {"p": {key: values}} or the old {"x": [...]} layout""" + j = json.load(open(fn)); p = default_params() + if "p" in j: + for k, val in j["p"].items(): p[k] = np.array(val, float) + else: + i = 0 + for k in OLD_KEYS: + n = np.size(p[k]); p[k] = np.array(j["x"][i:i + n], float); i += n + return p + + +def save_params(fn, p, **extra): + json.dump(dict(p={k: np.ravel(val).tolist() for k, val in p.items()}, **extra), open(fn, "w"), indent=0) + + +def flat(p): + return np.concatenate([np.ravel(p[k]) for k in sorted(p)]) + + +def unflat(x, like=None): + like = like or default_params(); out = {}; i = 0 + for k in sorted(like): + n = np.size(like[k]); out[k] = np.array(x[i:i + n], float).reshape(np.shape(like[k])); i += n + return out + + +class Shape: + def __init__(self, U, BV, BDOM, bones, muscle=0.6): + """U: (19,2,3) UO bone head/tail rest (body space) in the order of `bones`; BV / BDOM: v12 basis mesh + dominant group""" + U = {b: (U[i][0], U[i][1]) for i, b in enumerate(bones)} + self.U = U + P, F, B, W = load_mh(muscle=muscle) + self.P = P + body_verts = sorted({i for f in F for i in f}); self.used = np.array(body_verts) + PW = np.zeros((len(P), len(PARTS))) + for b, lst in W.items(): + j = PI[self.part_of(b)] + for vi, w in lst: + PW[vi, j] += w + noW = np.nonzero(PW.sum(1) < 1e-6)[0] + if len(noW): + kd = cKDTree(P[body_verts]); _, nn = kd.query(P[noW]) + PW[noW] = PW[np.array(body_verts)[nn]] + PW /= np.maximum(PW.sum(1, keepdims=True), 1e-9) + self.PW = PW + MDOM = np.array([PARTS[i] for i in PW.argmax(1)]) + remap = {o: n for n, o in enumerate(body_verts)} + self.faces = [[remap[i] for i in f] for f in F] + J = lambda b, e="head": B[b][0] if e == "head" else B[b][1] + self.J = J + TORSO = ("pelvis", "spine", "chest", "clavicle.L", "clavicle.R") + self.mh_top = P[body_verts, 2].max(); self.uo_top = BV[:, 2].max() + self.mh_hip = 0.5 * (J("upperleg01.L")[2] + J("upperleg01.R")[2]); self.uo_hip = 0.5 * (U["thigh.L"][0][2] + U["thigh.R"][0][2]) + self.mh_sh = 0.5 * (J("upperarm01.L")[2] + J("upperarm01.R")[2]); self.uo_sh = 0.5 * (U["upper_arm.L"][0][2] + U["upper_arm.R"][0][2]) + self.mh_hj = J("head")[2] + # ------------------------------------------------ limbs (measured girth from the v12 mesh, like stage 1) + CAP = {"upper_arm": (0.35, 0.75, 0.10), "forearm": (0.25, 0.75, 0.09), "hand": (0.2, 0.7, 0.07), + "thigh": (0.3, 0.8, 0.13), "shin": (0.2, 0.8, 0.10), "foot": (0.2, 0.8, 0.08)} + self.LIMB = {} + X = P[body_verts] + for part in PARTS: + base = part.split(".")[0] + if base not in CAP: + continue + am, bm = self.seg_mh(part, MDOM, body_verts); au, bu = U[part] + R = rot_between(bm - am, bu - au) + s_len = np.linalg.norm(bu - au) / np.linalg.norm(bm - am) + du = (bu - au) / np.linalg.norm(bu - au) + # second radial axis: 'front' = the body -Y direction made perpendicular to the bone, 'side' = the rest + fr = np.array([0.0, -1.0, 0.0]) - du * (-du[1]); + if np.linalg.norm(fr) < 0.3: + fr = np.array([0.0, 0.0, 1.0]) - du * du[2] + fr /= np.linalg.norm(fr); sd = np.cross(du, fr) + t0, t1, cap = CAP[base] + Y = (X - am) @ R.T; t = Y @ du; Y = au + Y + np.outer(t, du) * (s_len - 1) + rm, tm = radial(Y, au, bu); ru, tu = radial(BV, au, bu) + km = (tm > t0) & (tm < t1) & (rm < cap); ku = (tu > t0) & (tu < t1) & (ru < cap) + s_rad = float(np.median(ru[ku]) / max(np.median(rm[km]), 1e-6)) if km.sum() > 5 and ku.sum() > 5 else 1.0 + s_rad = float(np.clip(s_rad, 0.7, 1.8)) + self.LIMB[part] = (am, au, R, du, s_len, s_rad, np.linalg.norm(bu - au), sd, fr) + # ------------------------------------------------ torso levels + armw = sum(PW[:, PI[p]] for p in self.LIMB if p.startswith(("upper_arm", "forearm", "hand"))) + tm_idx = np.array([i for i in body_verts if MDOM[i] in TORSO and armw[i] < 0.05]) + d = np.full(len(BV), np.inf) + for s in (".L", ".R"): + for b in ("upper_arm", "forearm"): + r, t = radial(BV, *U[b + s]); d = np.minimum(d, np.where((t > -0.1) & (t < 1.1), r, np.inf)) + tu_idx = np.nonzero(d > 0.08)[0] + tu_idx = tu_idx[np.isin(BDOM[tu_idx], ["pelvis", "spine", "chest", "thigh.L", "thigh.R"])] + self.LEV = np.linspace(self.uo_hip - 0.02, self.uo_sh - 0.02, NLEV) + zt_m = self.torso_z(P[tm_idx, 2]) + SX, SY, CY, MC = [], [], [], [] + for z in self.LEV: + mm = np.abs(zt_m - z) < 0.03; uu = np.abs(BV[tu_idx, 2] - z) < 0.03 + xm = np.percentile(np.abs(P[tm_idx[mm], 0]), 95); xu = np.percentile(np.abs(BV[tu_idx[uu], 0]), 95) + ym = P[tm_idx[mm], 1]; yu = BV[tu_idx[uu], 1] + SX.append(xu / xm); SY.append((np.percentile(yu, 97) - np.percentile(yu, 3)) / (np.percentile(ym, 97) - np.percentile(ym, 3))) + MC.append(0.5 * (np.percentile(ym, 97) + np.percentile(ym, 3))); CY.append(0.5 * (np.percentile(yu, 97) + np.percentile(yu, 3))) + self.SX, self.SY, self.CY, self.MC = map(np.array, (SX, SY, CY, MC)) + # ------------------------------------------------ head + hu = np.nonzero(BDOM == "head")[0]; hm = np.array([i for i in body_verts if MDOM[i] == "head"]) + hu_top = BV[hu, 2].max(); hm_top = P[hm, 2].max() + wu = np.percentile(np.abs(BV[hu[BV[hu, 2] > hu_top - 0.12], 0]), 97); wm = np.percentile(np.abs(P[hm[P[hm, 2] > hm_top - 0.11], 0]), 97) + self.s_head = float(np.clip(wu / wm, 0.8, 1.6)) + self.cyu = 0.5 * (np.percentile(BV[hu, 1], 97) + np.percentile(BV[hu, 1], 3)); self.cym = 0.5 * (np.percentile(P[hm, 1], 97) + np.percentile(P[hm, 1], 3)) + # parts that actually move each vertex + self.sel = {p: np.nonzero(PW[:, PI[p]] > 1e-6)[0] for p in PARTS} + self.sel_all = dict(self.sel) + self.sel = {p: s[np.isin(s, self.used)] for p, s in self.sel.items()} + + @staticmethod + def part_of(b): + side = "." + b.split(".")[-1] if b.endswith((".L", ".R")) else "" + if b.startswith(("root", "spine05", "pelvis")): return "pelvis" + if b.startswith(("spine04", "spine03")): return "spine" + if b.startswith(("spine02", "spine01", "breast")): return "chest" + if b.startswith(("clavicle", "shoulder01")): return "clavicle" + side + if b.startswith("neck"): return "neck" + if b.startswith("upperarm"): return "upper_arm" + side + if b.startswith("lowerarm"): return "forearm" + side + if b.startswith(("wrist", "metacarpal", "finger")): return "hand" + side + if b.startswith("upperleg"): return "thigh" + side + if b.startswith("lowerleg"): return "shin" + side + if b.startswith(("foot", "toe")): return "foot" + side + return "head" + + def seg_mh(self, part, MDOM, body_verts): + J = self.J; P = self.P + s = part[-2:]; base = part[:-2] + if base == "upper_arm": return J("upperarm01" + s), J("lowerarm01" + s) + if base == "forearm": return J("lowerarm01" + s), J("wrist" + s) + if base == "hand": return J("wrist" + s), J("finger3-3" + s, "tail") + if base == "thigh": return J("upperleg01" + s), J("lowerleg01" + s) + if base == "shin": return J("lowerleg01" + s), J("foot" + s) + if base == "foot": + fv = np.array([i for i in body_verts if MDOM[i] == "foot" + s]) + tip = P[fv[np.argmin(P[fv, 1])]] + return J("foot" + s), np.array([J("foot" + s)[0], tip[1], tip[2]]) + raise KeyError(part) + + def torso_z(self, z): + return zmap(z, np.array([self.mh_hip, self.mh_sh]), np.array([self.uo_hip, self.uo_sh])) + + # ------------------------------------------------ transforms + def T_limb(self, part, X, g): + am, au, R, du, s_len, s_rad, L, sd, fr = self.LIMB[part] + Y = (X - am) @ R.T + t = Y @ du + Yr = Y - np.outer(t, du) + if part.startswith("foot"): + s_len = s_len * g[4] + tt = np.clip(t * s_len / L, 0, 1) + gs = s_rad * (g[0] + (g[1] - g[0]) * tt); gf = s_rad * (g[2] + (g[3] - g[2]) * tt) + a = Yr @ sd; b = Yr @ fr + return au + np.outer(t * s_len, du) + np.outer(a * gs, sd) + np.outer(b * gf, fr) + + def T_torso(self, X, p): + z = self.torso_z(X[:, 2]) + sx = np.interp(z, self.LEV, self.SX * p["tw"]); sy = np.interp(z, self.LEV, self.SY * p["td"]) + cm = np.interp(z, self.LEV, self.MC); cu = np.interp(z, self.LEV, self.CY + p["tc"]) + return np.stack([X[:, 0] * sx, cu + (X[:, 1] - cm) * sy, z], 1) + + def T_head(self, X, p): + s = self.s_head * p["head"][0]; h3 = p["head3"] + return np.stack([X[:, 0] * s * h3[0], self.cyu + (X[:, 1] - self.cym) * s * h3[1], self.uo_top + (X[:, 2] - self.mh_top) * s * h3[2]], 1) + + def T_neck(self, X, p): + s = self.s_head * p["head"][0] * p["head3"][2] + hb = self.uo_top - (self.mh_top - self.mh_hj) * s + z = zmap(X[:, 2], np.array([self.mh_sh, self.mh_hj]), np.array([self.uo_sh, hb])) + tw, td, tc = p["tw"][-1], p["td"][-1], p["tc"][-1] + return np.stack([X[:, 0] * self.SX[-1] * tw * p["neck"][0], self.CY[-1] + tc + (X[:, 1] - self.MC[-1]) * self.SY[-1] * td * p["neck"][1], z], 1) + + def build(self, p=None, full=False): + p = p or default_params() + P = self.P; OUT = np.zeros_like(P) + for part in PARTS: + s = (self.sel_all if full else self.sel)[part] + if not len(s): + continue + w = self.PW[s, PI[part]] + base = part.split(".")[0] + if part in self.LIMB: Y = self.T_limb(part, P[s], np.r_[p[base], p["footl"]] if base == "foot" else p[base]) + elif part == "neck": Y = self.T_neck(P[s], p) + elif part == "head": Y = self.T_head(P[s], p) + else: Y = self.T_torso(P[s], p) + OUT[s] += w[:, None] * Y + return OUT if full else OUT[self.used] + + +def zmap(z, zs_m, zs_u): + return np.where(z < zs_m[0], zs_u[0] + (z - zs_m[0]) * (zs_u[1] - zs_u[0]) / (zs_m[1] - zs_m[0]), + np.where(z > zs_m[-1], zs_u[-1] + (z - zs_m[-1]) * (zs_u[-1] - zs_u[-2]) / (zs_m[-1] - zs_m[-2]), np.interp(z, zs_m, zs_u))) + + +def rot_between(a, b): + a = a / np.linalg.norm(a); b = b / np.linalg.norm(b) + v = np.cross(a, b); c = float(a @ b) + if np.linalg.norm(v) < 1e-9: + return np.eye(3) + vx = np.array([[0, -v[2], v[1]], [v[2], 0, -v[0]], [-v[1], v[0], 0]]) + return np.eye(3) + vx + vx @ vx * (1 / (1 + c)) + + +def radial(X, a, b): + d = (b - a) / np.linalg.norm(b - a) + rel = X - a + t = rel @ d + return np.linalg.norm(rel - np.outer(t, d), axis=1), t / np.linalg.norm(b - a) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/shape_r2.json b/third_party/UO_Model3D_v13/pipeline/body13/shape_r2.json new file mode 100644 index 0000000..2ed8870 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/shape_r2.json @@ -0,0 +1,83 @@ +{ +"p": { +"foot": [ +1.2550000000000003, +1.2550000000000003, +1.1500000000000001, +1.1950000000000003 +], +"footl": [ +0.97 +], +"forearm": [ +1.2050000000000003, +1.235, +1.2100000000000002, +1.2100000000000002 +], +"hand": [ +1.1400000000000001, +1.11, +1.11, +1.08 +], +"head": [ +1.06 +], +"head3": [ +1.02, +1.02, +1.03 +], +"neck": [ +1.03, +1.0 +], +"shin": [ +0.8799999999999999, +0.9349999999999999, +0.8999999999999999, +0.8799999999999999 +], +"tc": [ +0.0, +0.0, +0.0, +0.0, +0.0, +0.0, +0.0 +], +"td": [ +0.955, +0.985, +1.0, +1.0, +1.0, +1.0, +1.0 +], +"thigh": [ +1.0625000000000002, +1.1475000000000002, +0.9974999999999999, +1.0825 +], +"tw": [ +0.9249999999999999, +0.9625, +0.9925, +1.0, +1.0, +1.0, +1.0 +], +"upper_arm": [ +1.1475000000000002, +1.1075000000000002, +1.2325, +1.1625 +] +}, +"iou": 0.886740051965023 +} \ No newline at end of file diff --git a/third_party/UO_Model3D_v13/pipeline/body13/shield_heater.json b/third_party/UO_Model3D_v13/pipeline/body13/shield_heater.json new file mode 100644 index 0000000..8376fb3 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/shield_heater.json @@ -0,0 +1,17 @@ +{ + "anim": 582, + "bone": "forearm.L", + "centre": [ + -0.06999999999999999, + 0.21003260906299165, + -0.03 + ], + "normal": [ + -0.99622020111851, + -0.07986807405616936, + 0.034152622592618614 + ], + "radius": 0.41999999999999993, + "stretch": 1.3000000000000003, + "iou": 0.45303569796511023 +} \ No newline at end of file diff --git a/third_party/UO_Model3D_v13/pipeline/body13/shieldfit.py b/third_party/UO_Model3D_v13/pipeline/body13/shieldfit.py new file mode 100644 index 0000000..e9575f8 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/shieldfit.py @@ -0,0 +1,77 @@ +"""calibrate a shield (disc) on the left forearm from the original UO shield frames (anim.mul, heater 582): +centre + normal + radius in the forearm's local frame, one for all frames, maximising the IoU with the sprite. +usage: shieldfit.py anim bone out.json""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, json, numpy as np +sys.path.insert(0, HERE) +from itemframes import load, canvas +from shape13 import Shape, load_params +from skel13 import Skel13 +from posefit13 import Frame13 +from fk import rig_world +from fastr import raster_one + +ANIM, BONE, OUT = int(sys.argv[1]), sys.argv[2], sys.argv[3] +POSES = sys.argv[sys.argv.index("--poses") + 1] if "--poses" in sys.argv else "poses13_r3.json" +r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]) +S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params("shape_r2.json"), full=True) +K = Skel13(S, r["R"], r["parent"], bones, Vf); P = json.load(open(POSES)) +fk = {tuple(int(x) for x in k): n for n, k in enumerate(r["keys"])} +it = load(ANIM); b = K.ix[BONE] +Ms, masks = [], []; cache = {} +for n, k in enumerate(v["keys"]): + a, i, d = (int(x) for x in k) + m = canvas(it.get((a, d)), i)[..., 3] > 0 + if not m.any() or "%d,%d" % (a, i) not in P: continue + if (a, i) not in cache: + f = fk[(a, i)] + fr = Frame13(K, None, None, None, None, r["Brel"], None, None, [], r["loc"][f], r["quat"][f]) + cache[(a, i)] = fr.skin(np.array(P["%d,%d" % (a, i)]["x"]))[b] @ K.R[b] + Ms.append(v["C"][n] @ rig_world(d) @ cache[(a, i)]); masks.append(m) +Ms = np.array(Ms); masks = np.array(masks); print("views with the shield", len(Ms)) +NB = 32; FAN = np.array([[0, 1 + k, 1 + (k + 1) % NB] for k in range(NB)], np.int32) + + +def disc(c, nrm, rad, sx=1.0): + nrm = nrm / np.linalg.norm(nrm); a = np.cross(nrm, [0, 1, 0]); + if np.linalg.norm(a) < 1e-3: a = np.cross(nrm, [1, 0, 0]) + a /= np.linalg.norm(a); b_ = np.cross(nrm, a) + t = np.linspace(0, 2 * np.pi, NB, endpoint=False) + return np.vstack([c, c + rad * (np.outer(np.cos(t), a) * sx + np.outer(np.sin(t), b_))]) + + +def score(x, sel=slice(None)): + c = x[:3]; nrm = np.array([np.sin(x[3]) * np.cos(x[4]), np.sin(x[3]) * np.sin(x[4]), np.cos(x[3])]) + D = disc(c, nrm, x[5], x[6]); Dh = np.c_[D, np.ones(len(D))] + tot = 0.0; MM = Ms[sel]; mm = masks[sel] + for k in range(len(MM)): + h = Dh @ MM[k].T; Sxy = np.stack([(h[:, 0] + 1) * 68.0, (1 - h[:, 1]) * 60.0], 1) + img = np.zeros((120, 136), np.bool_); raster_one(Sxy, FAN, img) + tot += (img & mm[k]).sum() / max((img | mm[k]).sum(), 1) + return tot / len(MM) + + +# start: forearm middle, pushed out along -Z (back of the forearm), facing out +L = np.linalg.norm(K.R[K.ix[BONE.replace("forearm", "hand")]][:3, 3] - K.R[b][:3, 3]) +best = (-1, None) +for ox in (-0.08, 0.0, 0.08): + for oz in (-0.08, 0.0, 0.08): + for th in np.linspace(0.2, np.pi - 0.2, 6): + for ph in np.linspace(-np.pi, np.pi, 8, endpoint=False): + x = np.array([ox, L * 0.5, oz, th, ph, 0.3, 1.0]); s = score(x, slice(None, None, 6)) + if s > best[0]: best = (s, x) +x = best[1]; f = score(x); print("coarse IoU %.3f" % f) +steps = np.array([0.02, 0.02, 0.02, 0.08, 0.08, 0.02, 0.05]) +for sc_ in (2, 1, 0.5, 0.25): + for _ in range(3): + imp = False + for j in range(7): + for sg in (1, -1): + y = x.copy(); y[j] += sg * steps[j] * sc_; fy = score(y) + if fy > f + 1e-4: x, f = y, fy; imp = True; break + if not imp: break + print("scale %.2f IoU %.4f" % (sc_, f), flush=True) +nrm = np.array([np.sin(x[3]) * np.cos(x[4]), np.sin(x[3]) * np.sin(x[4]), np.cos(x[3])]) +json.dump(dict(anim=ANIM, bone=BONE, centre=x[:3].tolist(), normal=nrm.tolist(), radius=float(x[5]), stretch=float(x[6]), iou=float(f)), open(OUT, "w"), indent=1) +print("centre", np.round(x[:3], 3), "normal", np.round(nrm, 3), "radius %.2f stretch %.2f IoU %.4f" % (x[5], x[6], f)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/skel13.py b/third_party/UO_Model3D_v13/pipeline/body13/skel13.py new file mode 100644 index 0000000..40dd373 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/skel13.py @@ -0,0 +1,115 @@ +"""v13 skeleton: the 19 UO bones (same rest pose, so every existing action still works) + twist bones, 15 finger bones +per hand and a toe bone per foot (55 bones). Skin weights come straight from the MakeHuman weights. + +Finger bones: local Z points to the palm, so a positive rotation about local X curls the finger into the fist. +Toe bone: positive rotation about local X lifts the toes.""" +import json, numpy as np +from mhlib import MH +from shape13 import Shape + +SIDES = (".L", ".R") +FING = ["finger%d-%d" % (f, s) for f in range(1, 6) for s in range(1, 4)] +# fist: curl angle (rad) per segment at curl = 1 (fingers 2-5) and thumb = 1 +FIST = {1: 1.25, 2: 1.55, 3: 1.05} +THUMB = {1: 0.35, 2: 0.55, 3: 0.6} + + +def skin_bone_of(b): + side = "." + b.split(".")[-1] if b.endswith(SIDES) else "" + base = b[:-2] if side else b + if base == "upperarm02": return "upper_arm_twist" + side + if base == "lowerarm02": return "forearm_twist" + side + if base in FING: return b + if base.startswith("toe"): return "toe" + side + return Shape.part_of(b) + + +def names13(uo_bones): + out = list(uo_bones) + for s in SIDES: + out += ["upper_arm_twist" + s, "forearm_twist" + s] + for s in SIDES: + out += [f + s for f in FING] + out += ["toe" + s for s in SIDES] + return out + + +def frame_from(head, tail, z_hint): + """Blender-like bone matrix: Y along the bone, Z as close as possible to z_hint, X = Y x Z""" + y = tail - head; L = np.linalg.norm(y); y = y / L + z = z_hint - y * (z_hint @ y); z /= np.linalg.norm(z) + x = np.cross(y, z) + M = np.eye(4); M[:3, 0] = x; M[:3, 1] = y; M[:3, 2] = z; M[:3, 3] = head + return M, L + + +class Skel13: + def __init__(self, S, R19, parent19, uo_bones, V_full): + """S: Shape; R19/parent19: UO rest matrices (armature space) + parents; V_full: shaped verts incl. helpers""" + sk = json.load(open(MH + "default.mhskel")) + JD = {k: V_full[v].mean(0) for k, v in sk["joints"].items()} + bh = lambda b: JD[sk["bones"][b]["head"]]; bt = lambda b: JD[sk["bones"][b]["tail"]] + self.names = names13(uo_bones); ix = {n: i for i, n in enumerate(self.names)}; self.ix = ix + B = len(self.names); R = np.zeros((B, 4, 4)); par = np.full(B, -1); L = np.zeros(B) + R[:19] = R19; par[:19] = parent19 + for i in range(19): + L[i] = 0 # unused for the UO bones + for s in SIDES: + for tw, pb in (("upper_arm_twist", "upper_arm"), ("forearm_twist", "forearm")): + P = R19[uo_bones.index(pb + s)] + ln = self.uo_len(pb + s, R19, uo_bones, V_full) + M = P.copy(); M[:3, 3] = P[:3, 3] + P[:3, 1] * ln * 0.5 + R[ix[tw + s]] = M; par[ix[tw + s]] = uo_bones.index(pb + s); L[ix[tw + s]] = ln * 0.5 + # palm normal: knuckles bulge to the back of the hand when the MakeHuman fingers are slightly bent + w = bh("wrist" + s); m2 = bh("finger2-1" + s); m5 = bh("finger5-1" + s) + n = np.cross(m2 - w, m5 - w); n /= np.linalg.norm(n) + back = np.zeros(3) + for f in (2, 3, 4, 5): + a, c = bh("finger%d-1" % f + s), bt("finger%d-3" % f + s); mid = bh("finger%d-2" % f + s) + d = (c - a) / np.linalg.norm(c - a); back += (mid - a) - d * ((mid - a) @ d) + if n @ back > 0: + n = -n # n now points to the palm + self.palm = getattr(self, "palm", {}); self.palm[s] = n + for f in FING: + b = f + s; M, ln = frame_from(bh(b), bt(b), n) + R[ix[b]] = M; L[ix[b]] = ln + seg = int(f[-1]) + par[ix[b]] = ix["hand" + s] if seg == 1 else ix[f[:-1] + str(seg - 1) + s] + toes1 = [bh("toe%d-1" % t + s) for t in range(1, 6)] + tips = [bt("toe1-2" + s)] + [bt("toe%d-3" % t + s) for t in range(2, 6)] + M, ln = frame_from(np.mean(toes1, 0), np.mean(tips, 0), np.array([0.0, 0.0, 1.0])) + R[ix["toe" + s]] = M; L[ix["toe" + s]] = ln; par[ix["toe" + s]] = uo_bones.index("foot" + s) + self.R, self.parent, self.L = R, par, L + # skin weights + Wmh = json.load(open(MH + "default_weights.mhw"))["weights"] + N = len(S.P); SW = np.zeros((N, B)) + for b, lst in Wmh.items(): + j = ix[skin_bone_of(b)] + for vi, wv in lst: + SW[vi, j] += wv + SW = SW[S.used] + SW /= np.maximum(SW.sum(1, keepdims=True), 1e-9) + self.SW = SW + + @staticmethod + def uo_len(b, R19, uo_bones, V_full): + """UO bone length from the child head (connected chain)""" + child = {"upper_arm": "forearm", "forearm": "hand"}[b[:-2]] + b[-2:] + return np.linalg.norm(R19[uo_bones.index(child)][:3, 3] - R19[uo_bones.index(b)][:3, 3]) + + def extra_bases(self, curl, thumb, toe): + """basis rotations (3x3) of the 36 extra bones for given curl / thumb / toe per side (dicts side -> value)""" + out = {} + for s in SIDES: + out["upper_arm_twist" + s] = np.eye(3); out["forearm_twist" + s] = np.eye(3) + for f in FING: + fi, seg = int(f[6]), int(f[-1]) + a = (THUMB[seg] * thumb[s]) if fi == 1 else (FIST[seg] * curl[s]) + out[f + s] = rotx(a) + out["toe" + s] = rotx(toe[s]) + return out + + +def rotx(a): + c, s = np.cos(a), np.sin(a) + return np.array([[1, 0, 0], [0, c, -s], [0, s, c]]) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/v12_mesh.npz b/third_party/UO_Model3D_v13/pipeline/body13/v12_mesh.npz new file mode 100644 index 0000000..164e014 Binary files /dev/null and b/third_party/UO_Model3D_v13/pipeline/body13/v12_mesh.npz differ diff --git a/third_party/UO_Model3D_v13/pipeline/body13/views_from_poses.py b/third_party/UO_Model3D_v13/pipeline/body13/views_from_poses.py new file mode 100644 index 0000000..2933699 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/views_from_poses.py @@ -0,0 +1,19 @@ +"""views npz with skin matrices from refit poses: views_from_poses.py poses.json out.npz""" +import sys, json, numpy as np +from posefit import rotvec +from fk import qmat, rig_world +r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); P = json.load(open(sys.argv[1])) +R, par, Brel = r["R"], r["parent"], r["Brel"]; Rinv = np.linalg.inv(R); B = len(R) +fk = {tuple(k): n for n, k in enumerate(r["keys"])} +W = v["W"].copy() +for n, (a, i, d) in enumerate(v["keys"]): + x = np.array(P["%d,%d" % (a, i)]["x"]); f = fk[(a, i)] + rr = x[:3 * B].reshape(B, 3); dl = x[3 * B:3 * B + 3]; g = x[3 * B + 3:].reshape(B, 2) if len(x) > 3 * B + 3 else np.zeros((B, 2)) + Pm = np.zeros((B, 4, 4)) + for b in range(B): + M = np.eye(4); M[:3, :3] = qmat(r["quat"][f, b]) @ rotvec(rr[b]); M[:3, 3] = r["loc"][f, b] + (dl if b == 0 else 0) + Pm[b] = (R[b] if par[b] < 0 else Pm[par[b]] @ Rinv[par[b]] @ R[b]) @ M + Gm = np.tile(np.eye(4), (B, 1, 1)); Gm[:, 0, 0] = np.exp(g[:, 0]); Gm[:, 2, 2] = np.exp(g[:, 1]) + W[n] = rig_world(d) @ Pm @ Gm @ Rinv @ Brel +out = {k: v[k] for k in v.files}; out["W"] = W +np.savez_compressed(sys.argv[2], **out); print("ok", len(W)) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/views_from_poses13.py b/third_party/UO_Model3D_v13/pipeline/body13/views_from_poses13.py new file mode 100644 index 0000000..89eb959 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/views_from_poses13.py @@ -0,0 +1,19 @@ +"""views npz with 55-bone skin matrices from refit poses: views_from_poses13.py shape.json poses.json out.npz""" +import sys, json, numpy as np +from shape13 import Shape, load_params +from skel13 import Skel13 +from posefit13 import Frame13 +from fk import rig_world +r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]); P = json.load(open(sys.argv[2])) +S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params(sys.argv[1]), full=True) +K = Skel13(S, r["R"], r["parent"], bones, Vf) +fk = {tuple(k): n for n, k in enumerate(r["keys"])} +W = np.zeros((len(v["keys"]), len(K.names), 4, 4)); cache = {} +for n, (a, i, d) in enumerate(v["keys"]): + if (a, i) not in cache: + f = fk[(a, i)] + fr = Frame13(K, None, None, None, None, r["Brel"], None, None, [], r["loc"][f], r["quat"][f]) + cache[(a, i)] = fr.skin(np.array(P["%d,%d" % (a, i)]["x"])) + W[n] = rig_world(d) @ cache[(a, i)] +out = {k: v[k] for k in v.files}; out["W"] = W +np.savez_compressed(sys.argv[3], **out); print("ok", W.shape) diff --git a/third_party/UO_Model3D_v13/pipeline/body13/weaponfit.py b/third_party/UO_Model3D_v13/pipeline/body13/weaponfit.py new file mode 100644 index 0000000..889ff2f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body13/weaponfit.py @@ -0,0 +1,102 @@ +"""calibrate how a weapon sits in the hand from the original UO weapon frames (anim.mul, e.g. katana 627): +a rigid stick (grip point + direction + length) in the hand bone's local frame, one for all frames, maximising the +IoU of the drawn stick with the weapon sprite. usage: weaponfit.py anim bone out.json [--len 0.9]""" +import os, sys +HERE = os.path.dirname(os.path.abspath(__file__)) +import sys, json, numpy as np +from numba import njit +sys.path.insert(0, HERE) +from itemframes import load, canvas +from shape13 import Shape, load_params +from skel13 import Skel13 +from posefit13 import Frame13 +from fk import rig_world + +ANIM, BONE, OUT = int(sys.argv[1]), sys.argv[2], sys.argv[3] +r = np.load("rig_poses.npz"); v = np.load("views_all.npz"); bones = list(r["bones"]) +S = Shape(v["U"], v["BV"], v["BDOM"], bones); Vf = S.build(load_params("shape_r2.json"), full=True) +K = Skel13(S, r["R"], r["parent"], bones, Vf); P = json.load(open(sys.argv[sys.argv.index("--poses") + 1] if "--poses" in sys.argv else "poses13_r3.json")) +fk = {tuple(int(x) for x in k): n for n, k in enumerate(r["keys"])} +it = load(ANIM); b = K.ix[BONE] +views = []; cache = {} +for n, k in enumerate(v["keys"]): + a, i, d = (int(x) for x in k) + m = canvas(it.get((a, d)), i)[..., 3] > 0 + if not m.any() or "%d,%d" % (a, i) not in P: continue + if (a, i) not in cache: + f = fk[(a, i)] + fr = Frame13(K, None, None, None, None, r["Brel"], None, None, [], r["loc"][f], r["quat"][f]) + Sk = fr.skin(np.array(P["%d,%d" % (a, i)]["x"])) + cache[(a, i)] = Sk[b] @ K.R[b] # bone pose matrix (armature) + M = v["C"][n] @ rig_world(d) @ cache[(a, i)] + views.append((M, m)) +print("views with the weapon", len(views)) +Ms = np.array([x[0] for x in views]); masks = np.array([x[1] for x in views]) + + +from scipy.ndimage import distance_transform_edt +DT = np.array([distance_transform_edt(~m) for m in masks]) # distance to the sprite +PIX = [np.argwhere(m)[:, ::-1] + 0.5 for m in masks] # sprite pixel centres (x, y) +NP = max(len(p) for p in PIX); PX = np.zeros((len(PIX), NP, 2)); PN = np.array([len(p) for p in PIX]) +for k, p in enumerate(PIX): PX[k, :len(p)] = p + + +@njit(cache=True) +def score(Ms, DT, PX, PN, p0, u, L, rad): + """- mean symmetric chamfer distance (px) between the projected stick and the sprite (higher is better)""" + tot = 0.0; ns = 40 + for k in range(Ms.shape[0]): + M = Ms[k] + a0 = p0; a1 = p0 + u * L + ax = (M[0, 0] * a0[0] + M[0, 1] * a0[1] + M[0, 2] * a0[2] + M[0, 3] + 1.0) * 68.0 + ay = (1.0 - (M[1, 0] * a0[0] + M[1, 1] * a0[1] + M[1, 2] * a0[2] + M[1, 3])) * 60.0 + bx = (M[0, 0] * a1[0] + M[0, 1] * a1[1] + M[0, 2] * a1[2] + M[0, 3] + 1.0) * 68.0 + by = (1.0 - (M[1, 0] * a1[0] + M[1, 1] * a1[1] + M[1, 2] * a1[2] + M[1, 3])) * 60.0 + d1 = 0.0 + for s in range(ns + 1): + x = ax + (bx - ax) * s / ns; y = ay + (by - ay) * s / ns + xi = min(max(int(x), 0), 135); yi = min(max(int(y), 0), 119) + d1 += min(DT[k, yi, xi], 15.0) + d1 /= ns + 1 + d2 = 0.0; ex = bx - ax; ey = by - ay; ll = ex * ex + ey * ey + 1e-9 + for j in range(PN[k]): + qx = PX[k, j, 0]; qy = PX[k, j, 1] + t = ((qx - ax) * ex + (qy - ay) * ey) / ll + t = min(max(t, 0.0), 1.0) + dx = ax + ex * t - qx; dy = ay + ey * t - qy + d2 += min(np.sqrt(dx * dx + dy * dy), 15.0) + d2 /= max(PN[k], 1) + tot += 0.5 * (d1 + d2) + return -tot / Ms.shape[0] + + +def unit(th, ph): + return np.array([np.sin(th) * np.cos(ph), np.sin(th) * np.sin(ph), np.cos(th)]) + + +L0 = float(sys.argv[sys.argv.index("--len") + 1]) if "--len" in sys.argv else 0.9 +best = (-np.inf, None) +# coarse search of the direction (hand local), grip at the fist centre +fist = np.linalg.inv(K.R[b])[:3, :3] @ (np.mean([K.R[K.ix[f + BONE[-2:]]][:3, 3] for f in ("finger2-1", "finger5-1")], 0) - K.R[b][:3, 3]) +print("fist centre in hand space", np.round(fist, 3)) +for th in np.linspace(0, np.pi, 13): + for ph in np.linspace(-np.pi, np.pi, 24, endpoint=False): + u = unit(th, ph); s = score(Ms[::3], DT[::3], PX[::3], PN[::3], fist, u, L0, 1.2) + if s > best[0]: best = (s, (th, ph)) +print("coarse best dir", np.round(best[1], 3), "chamfer %.2f px" % -best[0]) +x = np.array([best[1][0], best[1][1], fist[0], fist[1], fist[2], L0]) +f = score(Ms, DT, PX, PN, fist, unit(x[0], x[1]), x[5], 1.2) +steps = np.array([0.1, 0.1, 0.02, 0.02, 0.02, 0.08]) +for sc_ in (1, 0.5, 0.25, 0.12): + for _ in range(3): + imp = False + for j in range(6): + for sg in (1, -1): + y = x.copy(); y[j] += sg * steps[j] * sc_ + fy = score(Ms, DT, PX, PN, y[2:5], unit(y[0], y[1]), y[5], 1.2) + if fy > f + 1e-4: x, f = y, fy; imp = True; break + if not imp: break + print("scale %.2f chamfer %.3f px" % (sc_, -f), flush=True) +u = unit(x[0], x[1]); p0 = x[2:5] +json.dump(dict(anim=ANIM, bone=BONE, grip=p0.tolist(), dir=u.tolist(), length=float(x[5]), iou=float(f)), open(OUT, "w"), indent=1) +print("grip (hand local)", np.round(p0, 3), "dir", np.round(u, 3), "length %.2f" % x[5], "chamfer %.3f px" % -f) diff --git a/third_party/UO_Model3D_v13/pipeline/body_part_qa.py b/third_party/UO_Model3D_v13/pipeline/body_part_qa.py new file mode 100644 index 0000000..86bf72d --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_part_qa.py @@ -0,0 +1,65 @@ +"""Body QA per part: the label images of body_part_raster.py against the original UO body frames (client/body_0x190_frames). + + python body_part_raster.py ../model/UO_Body_0x190.blend /tmp/lab.npz + python body_part_qa.py /tmp/lab.npz [--out ../docs/qa/body_parts_baseline.json] + +Per part: `model+` = pixels only the model has (counted for the part that draws them), `sprite+` = pixels only the original has +(counted for the nearest model part). Totals are pixels per frame; IoU is the whole-silhouette IoU (same as body_silhouette_qa.py). +""" +import argparse, json, os +import numpy as np +from PIL import Image +from scipy.ndimage import distance_transform_edt + +HERE = os.path.dirname(os.path.abspath(__file__)) +ORIG = os.path.join(HERE, "..", "client", "body_0x190_frames") + + +def originals(): + meta = json.load(open(os.path.join(ORIG, "meta.json"))) + W, H = meta["canvas"]; out = {} + for blk in meta["blocks"]: + act = "%02d_%s" % (blk["action"], blk["name"]) + for i, fr in enumerate(blk["frames"]): + p = os.path.join(ORIG, "frames", act, "dir%d" % blk["dir"], fr["file"]) + out[(blk["action"], blk["dir"], i)] = np.array(Image.open(p).convert("RGBA"))[..., 3] > 0 if os.path.exists(p) else np.zeros((H, W), bool) + return out + + +def analyse(lab, key, parts): + O = originals(); P = len(parts) + sprite = np.zeros((len(key), P)); model = np.zeros((len(key), P)); iou = np.zeros(len(key)); ok = np.zeros(len(key), bool) + for n, (a, d, i) in enumerate(key): + g = O[(a, d, i)]; L = lab[n]; m = L >= 0 + if not g.any(): + continue + ok[n] = True + iou[n] = (m & g).sum() / max((m | g).sum(), 1) + b = m & ~g; np.add.at(model[n], L[b], 1) + r = g & ~m + if r.any(): + _, (iy, ix) = distance_transform_edt(~m, return_indices=True) + np.add.at(sprite[n], L[iy[r], ix[r]], 1) + return iou, sprite, model, ok + + +def main(): + ap = argparse.ArgumentParser(); ap.add_argument("lab"); ap.add_argument("--out") + a = ap.parse_args() + d = np.load(a.lab); lab, key, parts = d["lab"], d["key"], [str(p) for p in d["parts"]] + iou, sprite, model, ok = analyse(lab, key, parts) + k = ok + print("frames %d IoU %.4f model+ %.1f sprite+ %.1f px/frame" % (k.sum(), iou[k].mean(), model[k].sum(1).mean(), sprite[k].sum(1).mean())) + print("%-12s %8s %8s %8s" % ("part", "sprite+", "model+", "sum")) + rows = [] + for j, p in sorted(enumerate(parts), key=lambda t: -(sprite[k][:, t[0]].sum() + model[k][:, t[0]].sum())): + s, m = sprite[k][:, j].mean(), model[k][:, j].mean(); rows.append((p, s, m)) + print("%-12s %8.2f %8.2f %8.2f" % (p, s, m, s + m)) + if a.out: + out = dict(frames=int(k.sum()), iou=float(iou[k].mean()), parts={p: dict(sprite=float(s), model=float(m)) for p, s, m in rows}, + iou_by_action={str(x): float(iou[k & (key[:, 0] == x)].mean()) for x in sorted(set(key[:, 0]))}) + json.dump(out, open(a.out, "w"), indent=1) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/body_part_raster.py b/third_party/UO_Model3D_v13/pipeline/body_part_raster.py new file mode 100644 index 0000000..7969001 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_part_raster.py @@ -0,0 +1,134 @@ +"""Per-part label images of the pure 3D body, for every UO action / direction / frame (no Cycles: pixel-centre rasteriser). + + python body_part_raster.py ../model/UO_Body_0x190.blend OUT.npz [--offset dx,dy] [--actions 0,1,2] + +Writes `lab` (N, 133, 145) int8 in the canvas of the ORIGINAL body frames (145x133, anchor (75,92), 36 px/m): part index per pixel, +-1 = empty or hidden by the horse (mounted actions); `key` (N, 3) = (action, dir, frame); `parts` = part names. Parts: dominant bone group of a triangle's vertices, merged +(fingers -> hand, twist bones -> limb, toe -> foot), left / right kept apart. `body_part_qa.py` compares it with the original frames. +Needs: pip install numpy "bpy==4.2.*". +""" +import sys, os +import numpy as np +import bpy + +CW, CH, CANCH = 145, 133, (75, 92) # canvas and anchor of the original UO body frames +STEP = 3 # scene frames between two UO frames + + +def part_of(name): + base, _, side = name.partition(".") + if base.startswith("finger"): + base = "hand" + base = {"upper_arm_twist": "upper_arm", "forearm_twist": "forearm", "toe": "foot"}.get(base, base) + return base + ("." + side if side else "") + + +def raster(ob, dg, Pm, Vm, tlab, off=(0.0, 0.0)): + """label (tlab[triangle], or 0 when tlab is None) and camera depth of the nearest triangle per pixel, pixel-centre rule""" + ev = ob.evaluated_get(dg); m2 = ev.to_mesh() + co = np.empty(len(m2.vertices) * 3, np.float32); m2.vertices.foreach_get("co", co); co = co.reshape(-1, 3) + m2.calc_loop_triangles() + tri = np.empty(len(m2.loop_triangles) * 3, np.int32); m2.loop_triangles.foreach_get("vertices", tri); tri = tri.reshape(-1, 3) + Mw = np.array(ev.matrix_world); ev.to_mesh_clear() + lt = np.zeros(len(tri), np.int8) if tlab is None else tlab + assert len(tri) == len(lt) + hv = np.c_[co, np.ones(len(co))] @ (Vm @ Mw).T + h = hv @ Pm.T; ndc = h[:, :2] / h[:, 3:4] + P = np.stack([(ndc[:, 0] + 1) * 0.5 * CW, (1 - ndc[:, 1]) * 0.5 * CH], 1)[tri] + np.array(off) + Z = -hv[:, 2][tri] + lab = np.full((CH, CW), -1, np.int8); depth = np.full((CH, CW), np.inf) + mn = np.floor(P.min(1)).astype(int); mx = np.ceil(P.max(1)).astype(int) + A, B, C = P[:, 0], P[:, 1], P[:, 2] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + ok = np.abs(den) > 1e-12; size = np.clip(mx - mn, 0, 16) + for dy in range(int(size[:, 1].max(initial=0)) + 1): + for dx in range(int(size[:, 0].max(initial=0)) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px_ = mn[t, 0] + dx; py_ = mn[t, 1] + dy; cx, cy = px_ + 0.5, py_ + 0.5 + l0 = ((B[t, 1] - C[t, 1]) * (cx - C[t, 0]) + (C[t, 0] - B[t, 0]) * (cy - C[t, 1])) / den[t] + l1 = ((C[t, 1] - A[t, 1]) * (cx - C[t, 0]) + (A[t, 0] - C[t, 0]) * (cy - C[t, 1])) / den[t] + kk = (l0 >= -1e-4) & (l1 >= -1e-4) & (1 - l0 - l1 >= -1e-4) & (px_ >= 0) & (py_ >= 0) & (px_ < CW) & (py_ < CH) + z = l0[kk] * Z[t[kk], 0] + l1[kk] * Z[t[kk], 1] + (1 - l0[kk] - l1[kk]) * Z[t[kk], 2] + tt, yy, xx = t[kk], py_[kk], px_[kk] + o = np.argsort(-z) # far first: the nearest triangle is written last + o = o[z[o] < depth[yy[o], xx[o]]] + depth[yy[o], xx[o]] = z[o]; lab[yy[o], xx[o]] = lt[tt[o]] + return lab, depth + + +def main(): + args = sys.argv[1:] + blend, out = os.path.abspath(args.pop(0)), os.path.abspath(args.pop(0)) + only, OFF = None, (0.0, 0.0) + if args and args[0] == "--offset": # test: shift the whole render by (dx, dy) px + args.pop(0); OFF = tuple(float(x) for x in args.pop(0).split(",")) + if args and args[0] == "--actions": + args.pop(0); only = {int(x) for x in args.pop(0).split(",")} + bpy.ops.wm.open_mainfile(filepath=blend) + sc = bpy.context.scene + rig, body = bpy.data.objects["UO_Rig"], bpy.data.objects["UO_Body"] + sc.camera = bpy.data.objects["UO_Camera"]; cd = sc.camera.data + cd.sensor_fit = "HORIZONTAL"; cd.ortho_scale = CW / sc.get("uo_px_per_m", 36.0); cd.shift_x = cd.shift_y = 0.0 + sc.render.resolution_x, sc.render.resolution_y, sc.render.resolution_percentage = CW, CH, 100 + + def anchor_px(): + bpy.context.view_layer.update(); dg = bpy.context.evaluated_depsgraph_get(); cam = sc.camera.evaluated_get(dg) + P = np.array(cam.calc_matrix_camera(dg, x=CW, y=CH)) @ np.array(cam.matrix_world.inverted()) @ \ + np.array([0.0, 0.0, sc.get("uo_anchor_height", 0.07), 1.0]) + return np.array([(P[0] / P[3] + 1) * 0.5 * CW, (1 - P[1] / P[3]) * 0.5 * CH]) + + p0 = anchor_px(); cd.shift_x = cd.shift_y = 0.01; p1 = anchor_px(); k = (p1 - p0) / 0.01 + want = np.array(CANCH, float) + (np.array(sc.get("uo_anchor_px", (68.5, 86.0))) - np.array((68, 86))) + sh = (want - p0) / k; cd.shift_x, cd.shift_y = float(sh[0]), float(sh[1]) + assert np.abs(anchor_px() - want).max() < 1e-3 + + names = [g.name for g in body.vertex_groups] + parts = sorted({part_of(n) for n in names}); pid = {p: i for i, p in enumerate(parts)} + gpart = np.array([pid[part_of(n)] for n in names]) + me = body.data + Wv = np.zeros((len(me.vertices), len(parts))) + for v in me.vertices: + for g in v.groups: + Wv[v.index, gpart[g.group]] += g.weight + me.calc_loop_triangles() + tri0 = np.array([t.vertices[:] for t in me.loop_triangles]) + tlab = Wv[tri0].sum(1).argmax(1) + + horses = {o.name: o for o in bpy.data.objects if o.name.startswith("Horse_")} + for o in horses.values(): + o.hide_viewport = o.hide_render = False # hidden objects are not evaluated by the depsgraph + HORSE = {} + if "uo_horse_masks.json" in bpy.data.texts: + import base64, zlib, json + for k, v in json.loads(bpy.data.texts["uo_horse_masks.json"].as_string())["masks"].items(): + bits = np.unpackbits(np.frombuffer(zlib.decompress(base64.b64decode(v)), np.uint8))[:120 * 136].reshape(120, 136).astype(bool) + m = np.zeros((CH, CW), bool); m[CANCH[1] - 86:CANCH[1] - 86 + 120, CANCH[0] - 68:CANCH[0] - 68 + 136] = bits + HORSE[tuple(int(x) for x in k.split(","))] = m + + acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) + labs, keys = [], [] + for act in acts: + a = int(act["uo_action"]) + if only is not None and a not in only: + continue + rig.animation_data.action = act + for d in range(5): + rig["uo_direction"] = d + for i in range(int(act["uo_frames"])): + sc.frame_set(1 + i * STEP); rig.update_tag(); body.update_tag(); bpy.context.view_layer.update() + dg = bpy.context.evaluated_depsgraph_get(); cam = sc.camera.evaluated_get(dg) + Pm = np.array(cam.calc_matrix_camera(dg, x=CW, y=CH)); Vm = np.array(cam.matrix_world.inverted()) + lab, depth = raster(body, dg, Pm, Vm, tlab, OFF) + h_ob = horses.get("Horse_a%d_f%d" % (a, i)) + hm = HORSE.get((a, i, d)) + if h_ob is not None and hm is not None: # mounted: the horse hides what is behind it, clipped to its sprite + hl, hd = raster(h_ob, dg, Pm, Vm, None, OFF) + hide = (hl >= 0) & (hd < depth) & hm + lab[hide] = -1 + labs.append(lab); keys.append((a, d, i)) + print("action", a, "done", flush=True) + np.savez_compressed(out, lab=np.array(labs), key=np.array(keys), parts=np.array(parts)) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/body_pose_apply.py b/third_party/UO_Model3D_v13/pipeline/body_pose_apply.py new file mode 100644 index 0000000..f8e6f3b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_pose_apply.py @@ -0,0 +1,49 @@ +"""Write fitted pose corrections (corr.npz of body_pose_fit.py) into the keyframes of the actions of model/UO_Body_0x190.blend. + + python body_pose_apply.py ../model/UO_Body_0x190.blend corr.npz [--out OTHER.blend] + +Only the keyframe VALUES of rotation_quaternion / location / scale of the bones that differ are changed (handles move with their key), at frame 1+3*i of the +pose (action, i). Nothing else in the file changes. Bones without a curve for the changed channel are skipped with a warning. +""" +import sys, argparse, os +import numpy as np +import bpy +from bpy_compat import action_fcurves, find_fcurve + + +def main(): + ap = argparse.ArgumentParser(); ap.add_argument("blend"); ap.add_argument("corr"); ap.add_argument("--out"); a = ap.parse_args() + bpy.ops.wm.open_mainfile(filepath=os.path.abspath(a.blend)) + c = np.load(a.corr); bones = [str(b) for b in c["bones"]]; key = c["key"] + rig = bpy.data.objects["UO_Rig"] + acts = {int(x["uo_action"]): x for x in bpy.data.actions if "uo_action" in x} + chan = {"rotation_quaternion": (c["quat"], 4), "location": (c["loc"], 3), "scale": (c["scl"], 3)} + nset = nskip = 0; skipped = set() + for p, (act, i) in enumerate(key): + A = acts[int(act)]; fr = 1 + int(i) * 3 + for dp, (arr, n) in chan.items(): + for j, bn in enumerate(bones): + new = arr[p, j] + if dp == "rotation_quaternion": # keep the sign convention of the old key (q and -q are the same rotation) + old = np.array([find_fcurve(A, 'pose.bones["%s"].%s' % (bn, dp), k).evaluate(fr) if find_fcurve(A, 'pose.bones["%s"].%s' % (bn, dp), k) else np.nan for k in range(4)]) + if not np.isnan(old).any() and (old * new).sum() < 0: + new = -new + for k in range(n): + fc = find_fcurve(A, 'pose.bones["%s"].%s' % (bn, dp), k) + if fc is None: + skipped.add((bn, dp)); continue + kp = [q for q in fc.keyframe_points if abs(q.co[0] - fr) < 1e-6] + if not kp: + skipped.add((bn, dp, "nokey")); continue + v = float(new[k]); q = kp[0] + if abs(q.co[1] - v) > 1e-7: + d = v - q.co[1]; q.co[1] = v; q.handle_left[1] += d; q.handle_right[1] += d; nset += 1 + for A in acts.values(): + for fc in action_fcurves(A): + fc.update() + print("keyframe values changed: %d; skipped channels: %s" % (nset, sorted(skipped)[:10])) + bpy.ops.wm.save_as_mainfile(filepath=os.path.abspath(a.out or a.blend)) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/body_pose_export.py b/third_party/UO_Model3D_v13/pipeline/body_pose_export.py new file mode 100644 index 0000000..7dbadcf --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_pose_export.py @@ -0,0 +1,101 @@ +"""Export the posed-body data of all 1050 UO frames, so shape work can run offline (numpy only, no Blender). + + python body_pose_export.py ../model/UO_Body_0x190.blend OUT.npz + +Writes: rest (N,3) rest vertices, wi (N,K) / ww (N,K) bone indices and weights (K influences, padded with weight 0), tris (T,3) triangles of +the quads, tpart-less; bones (list), M (F,B,4,4) armature-space skinning matrices per frame (pose @ rest^-1), MW (F,4,4) body matrix_world, +key (F,3) = (action, dir, frame), cam (3,4,4)= [Pm, Vm, (CW, CH, 0, 0)], horse_depth (F,CH,CW) float32 (inf = none) and horse_mask (F,CH,CW) +bool for mounted frames. Canvas is the one of the original frames: 145x133, anchor (75,92). resid_idx / resid_val / resid_frame: where plain LBS of rest with M differs from Blender's evaluated mesh by > 0.1 mm (shoulders: +bendy-bone / twist bones), as sparse vertex offsets per frame; Scene.posed adds them. +""" +import sys, os, json +import numpy as np +import bpy + +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) +CW, CH, CANCH = 145, 133, (75, 92) +STEP = 3 + + +def main(): + blend, out = os.path.abspath(sys.argv[1]), os.path.abspath(sys.argv[2]) + bpy.ops.wm.open_mainfile(filepath=blend) + sc = bpy.context.scene + rig, body = bpy.data.objects["UO_Rig"], bpy.data.objects["UO_Body"] + sc.camera = bpy.data.objects["UO_Camera"]; cd = sc.camera.data + cd.sensor_fit = "HORIZONTAL"; cd.ortho_scale = CW / sc.get("uo_px_per_m", 36.0); cd.shift_x = cd.shift_y = 0.0 + sc.render.resolution_x, sc.render.resolution_y, sc.render.resolution_percentage = CW, CH, 100 + + def anchor_px(): + bpy.context.view_layer.update(); dg = bpy.context.evaluated_depsgraph_get(); cam = sc.camera.evaluated_get(dg) + P = np.array(cam.calc_matrix_camera(dg, x=CW, y=CH)) @ np.array(cam.matrix_world.inverted()) @ \ + np.array([0.0, 0.0, sc.get("uo_anchor_height", 0.07), 1.0]) + return np.array([(P[0] / P[3] + 1) * 0.5 * CW, (1 - P[1] / P[3]) * 0.5 * CH]) + + p0 = anchor_px(); cd.shift_x = cd.shift_y = 0.01; p1 = anchor_px(); k = (p1 - p0) / 0.01 + want = np.array(CANCH, float) + (np.array(sc.get("uo_anchor_px", (68.5, 86.0))) - np.array((68, 86))) + sh = (want - p0) / k; cd.shift_x, cd.shift_y = float(sh[0]), float(sh[1]) + assert np.abs(anchor_px() - want).max() < 1e-3 + rig.data.pose_position = "POSE" + bpy.context.view_layer.update() + dg = bpy.context.evaluated_depsgraph_get(); cam = sc.camera.evaluated_get(dg) + Pm = np.array(cam.calc_matrix_camera(dg, x=CW, y=CH)); Vm = np.array(cam.matrix_world.inverted()) + + names = [g.name for g in body.vertex_groups] + rest = np.array([v.co[:] for v in body.data.vertices]) + Wm = np.zeros((len(rest), len(names))) + for v in body.data.vertices: + for g in v.groups: + Wm[v.index, g.group] = g.weight + for j, n in enumerate(names): # Blender ignores the groups of bones with Deform off (the clavicles) and renormalises + if not rig.data.bones[n].use_deform: + Wm[:, j] = 0.0 + Wm /= np.maximum(Wm.sum(1, keepdims=True), 1e-9) + K = int((Wm > 0).sum(1).max()) + wi = np.argsort(-Wm, 1)[:, :K]; ww = np.take_along_axis(Wm, wi, 1) + body.data.calc_loop_triangles() + tris = np.array([t.vertices[:] for t in body.data.loop_triangles], np.int32) + horses = {o.name: o for o in bpy.data.objects if o.name.startswith("Horse_")} + for o in horses.values(): + o.hide_viewport = o.hide_render = False + HM = {} + if "uo_horse_masks.json" in bpy.data.texts: + import base64, zlib + for kk, v in json.loads(bpy.data.texts["uo_horse_masks.json"].as_string())["masks"].items(): + bits = np.unpackbits(np.frombuffer(zlib.decompress(base64.b64decode(v)), np.uint8))[:120 * 136].reshape(120, 136).astype(bool) + m = np.zeros((CH, CW), bool); m[CANCH[1] - 86:CANCH[1] - 86 + 120, CANCH[0] - 68:CANCH[0] - 68 + 136] = bits + HM[tuple(int(x) for x in kk.split(","))] = m + + Ms, MWs, keys, hd, hm = [], [], [], [], [] + R4 = np.c_[rest, np.ones(len(rest))]; RI, RV, RF = [], [], [] # residual: Blender's evaluated mesh minus the plain LBS below + from body_part_raster import raster # horse proxies are rasterised with the same code + acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) + for act in acts: + a = int(act["uo_action"]); rig.animation_data.action = act + for d in range(5): + rig["uo_direction"] = d + for i in range(int(act["uo_frames"])): + sc.frame_set(1 + i * STEP); rig.update_tag(); bpy.context.view_layer.update() + M = np.zeros((len(names), 4, 4)) + for j, n in enumerate(names): + pb = rig.pose.bones[n]; M[j] = np.array(pb.matrix @ pb.bone.matrix_local.inverted()) + Ms.append(M); MWs.append(np.array(body.matrix_world)); keys.append((a, d, i)) + ev = body.evaluated_get(bpy.context.evaluated_depsgraph_get()); me = ev.to_mesh() + co = np.empty(len(me.vertices) * 3, np.float32); me.vertices.foreach_get("co", co); ev.to_mesh_clear() + lbs = (np.einsum("nkij,nj->nki", M[wi], R4)[..., :3] * ww[..., None]).sum(1) + r = co.reshape(-1, 3) - lbs; bad = np.nonzero(np.linalg.norm(r, axis=1) > 1e-4)[0] + RI.append(bad); RV.append(r[bad].astype(np.float32)); RF.append(np.full(len(bad), len(Ms) - 1)) + h = horses.get("Horse_a%d_f%d" % (a, i)); m = HM.get((a, i, d)) + if h is not None and m is not None: + dg = bpy.context.evaluated_depsgraph_get() + hl, depth = raster(h, dg, Pm, Vm, None) + hd.append(np.where(hl >= 0, depth, np.inf).astype(np.float32)); hm.append(m) + else: + hd.append(np.full((CH, CW), np.inf, np.float32)); hm.append(np.zeros((CH, CW), bool)) + print("action", a, flush=True) + np.savez_compressed(out, rest=rest, wi=wi, ww=ww, tris=tris, bones=np.array(names), M=np.array(Ms, np.float32), MW=np.array(MWs), + key=np.array(keys), resid_idx=np.concatenate(RI), resid_val=np.concatenate(RV), resid_frame=np.concatenate(RF), Pm=Pm, Vm=Vm, canvas=np.array([CW, CH]), horse_depth=np.array(hd), horse_mask=np.array(hm)) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/body_pose_fit.py b/third_party/UO_Model3D_v13/pipeline/body_pose_fit.py new file mode 100644 index 0000000..267ec08 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_pose_fit.py @@ -0,0 +1,171 @@ +"""Silhouette-driven refinement of the POSES of the body (per pose: small corrections of bone rotations / pelvis location / limb scales). + + python body_pose_fit.py pose.npz fk.npz --out corr.npz [--iters 4] [--lam 1.0] [--holdout-dir 3] [--max-rot 0.12] [--scale] + +A pose (action, frame) is shared by the 5 directions, so its 5 silhouettes constrain the 3D pose together. For every pose we fit +theta = (rotation vectors of the fitted bones, pelvis location, optionally x/z scale of limb bones) so that the contour of the model moves onto the +contour of the sprites. Same contour constraints as body_shape_fit.py (signed distance of the model contour to the sprite contour along the 2D normal), +Jacobian by finite differences of the forward kinematics (exact for inherit-scale-NONE bones too), damped Gauss-Newton with an absolute ridge (--lam-*, px^2 per rad^2 / m^2) towards the +ORIGINAL pose and a hard cap on the accumulated rotation. The body shape (rest vertices) is not touched. `--holdout-dir d` keeps direction d out of the fit +and reports its IoU: poses that are right in 3D improve there too. Writes corr.npz: for each pose the new loc / quat / scl of every bone. +Needs numpy, scipy, pillow. +""" +import argparse, time +import numpy as np +from scipy.ndimage import distance_transform_edt, map_coordinates, binary_dilation +import body_shape_lib as L +import body_pose_lib as PL +from body_shape_fit import signed_dist, vertex_normals + +ROT = ["pelvis", "spine", "chest", "neck", "head", "clavicle.L", "clavicle.R", "upper_arm.L", "upper_arm.R", "forearm.L", "forearm.R", "hand.L", "hand.R", + "thigh.L", "thigh.R", "shin.L", "shin.R", "foot.L", "foot.R", "toe.L", "toe.R"] +SCALE = ["upper_arm.L", "upper_arm.R", "forearm.L", "forearm.R", "hand.L", "hand.R", "thigh.L", "thigh.R", "shin.L", "shin.R", "foot.L", "foot.R", "head"] + + +class Params: + """layout of theta: (kind, bone, axis) with kind r (rotation vector), t (translation of the pelvis), s (log-scale)""" + def __init__(self, K, scale): + self.items = [("r", K.idx[n], a) for n in ROT if n in K.idx for a in range(3)] + [("t", K.idx["pelvis"], a) for a in range(3)] + if scale: + self.items += [("s", K.idx[n], a) for n in SCALE if n in K.idx for a in (0, 2)] + self.n = len(self.items) + + def apply(self, K, base, theta): + loc, quat, scl = [x.copy() for x in base] + for (k, b, a), v in zip(self.items, theta): + if k == "r": + pass + elif k == "t": + loc[b, a] += v + else: + scl[b, a] *= np.exp(v) + for b in sorted({b for k, b, a in self.items if k == "r"}): + w = np.array([v for (k, bb, a), v in zip(self.items, theta) if k == "r" and bb == b]) + quat[b] = PL.qmul(quat[b] / np.linalg.norm(quat[b]), PL.rotvec_to_quat(w)) + return loc, quat, scl + + +def contour_rows(S, f, M, clip, band, side): + """contour vertices of frame f for pose matrices M: (idx, n2 (n,2), t (n,) target shift in px, J (2,3))""" + S.M[f] = M + m, lab, depth, X, xy, z = L.model_mask(S, f) + smd = signed_dist(m); sdg = signed_dist(S.G[f]) + pc = np.stack([xy[:, 1] - 0.5, xy[:, 0] - 0.5]) + s_m = map_coordinates(smd, pc, order=1, mode="nearest"); s_g = map_coordinates(sdg, pc, order=1, mode="nearest") + ix = np.clip(xy[:, 0].astype(int), 0, S.CW - 1); iy = np.clip(xy[:, 1].astype(int), 0, S.CH - 1) + vis = z <= depth[iy, ix] + 0.03 + if S.hm[f].any(): + vis &= ~binary_dilation(S.hm[f], iterations=2)[iy, ix] + Xn = vertex_normals(X, S.tris) + T = S.Vm @ S.MW[f]; view = np.linalg.inv(T)[:3, :3] @ np.array([0, 0, 1.0]) + nz = np.abs(Xn @ view) / np.linalg.norm(view) + sel = vis & (np.abs(s_m) < band) & (nz < side) & (np.abs(s_g) < 6) + if not sel.any(): + return None + idx = np.nonzero(sel)[0] + gy, gx = np.gradient(smd) + ny = map_coordinates(gy, pc[:, idx], order=1, mode="nearest"); nx = map_coordinates(gx, pc[:, idx], order=1, mode="nearest") + nn = np.hypot(nx, ny); good = nn > 1e-6 + idx, nx, ny, nn = idx[good], nx[good], ny[good], nn[good] + n2 = np.stack([nx, ny], 1) / nn[:, None] + Pt = (S.Pm @ S.Vm @ S.MW[f])[:2, :3] + J = np.stack([Pt[0] * 0.5 * S.CW, -Pt[1] * 0.5 * S.CH]) + t = -np.clip(s_g[idx] - s_m[idx], -clip, clip) + return idx, n2, t, J + + +def fit_pose(S, K, P, p, frames, theta0, args, hold_frames=()): + base = (K.loc[p], K.quat[p], K.scl[p]) + theta = theta0.copy(); R4 = np.c_[S.rest, np.ones(S.N)] + reg = np.array([args.lam_rot if k == "r" else args.lam_t if k == "t" else args.lam_s for k, b, a in P.items]) + cap = np.array([args.max_rot if k == "r" else args.max_t if k == "t" else args.max_s for k, b, a in P.items]) + M0 = {f: S.M[f].copy() for f in frames} + eps = 1e-4 + def skin(th): + return K.skin(*P.apply(K, base, th)) + for it in range(args.iters): + Mc = skin(theta) + Mp = [skin(theta + eps * np.eye(P.n)[j]) for j in range(P.n)] # finite-difference pose matrices + H = np.zeros((P.n, P.n)); g = np.zeros(P.n); used = 0 + for f in frames: + r = contour_rows(S, f, Mc, args.clip, args.band, args.side) + if r is None: + continue + idx, n2, t, Jc = r + Rv = R4[idx]; wi = S.wi[idx]; ww = S.ww[idx] # (n,K) + X0 = (np.einsum("nkij,nj->nki", Mc[wi], Rv)[..., :3] * ww[..., None]).sum(1) + A = np.zeros((len(idx), P.n)) + for j in range(P.n): + Xj = (np.einsum("nkij,nj->nki", Mp[j][wi], Rv)[..., :3] * ww[..., None]).sum(1) + dX = (Xj - X0) / eps # (n,3) body-local displacement per unit parameter + A[:, j] = np.einsum("nc,cd,nd->n", n2, Jc, dX) + H += A.T @ A; g += A.T @ t; used += len(idx) + if used == 0: + break + step = np.linalg.solve(H + np.diag(reg) + 1e-9 * np.eye(P.n), g - reg * theta) + theta = np.clip(theta + args.damp * step, -cap, cap) + for f in frames: + S.M[f] = M0[f] + return theta + + +def score_poses(S, K, P, thetas, poses, frames_of, mask=None): + """mean IoU over frames of the given poses with thetas applied""" + ious = [] + for p in poses: + base = (K.loc[p], K.quat[p], K.scl[p]); M = K.skin(*P.apply(K, base, thetas[p])) + for f in frames_of[p]: + old = S.M[f].copy(); S.M[f] = M + m = L.model_mask(S, f)[0]; g = S.G[f]; S.M[f] = old + ious.append((m & g).sum() / max((m | g).sum(), 1)) + return float(np.mean(ious)) + + +def main(): + ap = argparse.ArgumentParser(); ap.add_argument("pose"); ap.add_argument("fk"); ap.add_argument("--out"); ap.add_argument("--iters", type=int, default=4) + ap.add_argument("--lam-rot", type=float, default=3000.0); ap.add_argument("--lam-t", type=float, default=3e6); ap.add_argument("--lam-s", type=float, default=3e4) + ap.add_argument("--max-rot", type=float, default=0.12); ap.add_argument("--max-t", type=float, default=0.03); ap.add_argument("--max-s", type=float, default=0.1) + ap.add_argument("--scale", action="store_true"); ap.add_argument("--damp", type=float, default=0.7); ap.add_argument("--clip", type=float, default=2.0) + ap.add_argument("--band", type=float, default=1.0); ap.add_argument("--side", type=float, default=0.6); ap.add_argument("--holdout-dir", type=int, default=-1) + ap.add_argument("--bones", type=str, default="", help="comma list: restrict the fitted rotation bones (pelvis loc stays unless --no-loc)"); ap.add_argument("--no-loc", action="store_true") + ap.add_argument("--poses", type=str, default="", help="subset lo:hi[:step] of pose indices") + a = ap.parse_args() + S = L.Scene(a.pose); K = PL.FK(a.fk) + if a.bones: + ROT[:] = [n for n in a.bones.split(",") if n in K.idx] + P = Params(K, a.scale) + if a.no_loc: + P.items = [it for it in P.items if it[0] != "t"]; P.n = len(P.items) + assert K.bones == S.bones + frames_of = {} + for f, (act, d, i) in enumerate(S.key): + if S.ok[f]: + frames_of.setdefault(K.pose_index[(int(act), int(i))], []).append(f) + poses = sorted(frames_of) + if a.poses: + lo, hi, st = ([int(x) for x in a.poses.split(":")] + [1])[:3]; poses = [p for p in poses if lo <= p < hi and (p - lo) % st == 0] + thetas = {p: np.zeros(P.n) for p in range(len(K.key))} + fit_frames = {p: [f for f in frames_of[p] if S.key[f][1] != a.holdout_dir] for p in poses} + hold_frames = {p: [f for f in frames_of[p] if S.key[f][1] == a.holdout_dir] for p in poses} + print("params per pose:", P.n, " poses:", len(poses), flush=True) + t0 = time.time() + sc0_fit = score_poses(S, K, P, thetas, poses, fit_frames); sc0_hold = score_poses(S, K, P, thetas, poses, hold_frames) if a.holdout_dir >= 0 else float("nan") + print("start: fit-dirs IoU %.4f hold-out dir IoU %.4f" % (sc0_fit, sc0_hold), flush=True) + for n, p in enumerate(poses): + thetas[p] = fit_pose(S, K, P, p, fit_frames[p], thetas[p], a) + if n % 20 == 19: + print(" pose %d/%d %.0fs" % (n + 1, len(poses), time.time() - t0), flush=True) + sc1_fit = score_poses(S, K, P, thetas, poses, fit_frames); sc1_hold = score_poses(S, K, P, thetas, poses, hold_frames) if a.holdout_dir >= 0 else float("nan") + allf = {p: frames_of[p] for p in poses} + print("end: fit-dirs IoU %.4f hold-out dir IoU %.4f all %.4f -> %.4f" % (sc1_fit, sc1_hold, score_poses(S, K, P, {p: np.zeros(P.n) for p in thetas}, poses, allf), score_poses(S, K, P, thetas, poses, allf)), flush=True) + rot = np.array([[np.linalg.norm(thetas[p][3 * i:3 * i + 3]) for i in range(len([1 for k, b, aa in P.items if k == "r"]) // 3)] for p in poses]) + print("mean |rot| deg per bone:", dict(zip(ROT, np.degrees(rot.mean(0)).round(2)))) + if a.out: + loc = np.zeros_like(K.loc); quat = np.zeros_like(K.quat); scl = np.zeros_like(K.scl) + for p in range(len(K.key)): + loc[p], quat[p], scl[p] = P.apply(K, (K.loc[p], K.quat[p], K.scl[p]), thetas[p]) + np.savez_compressed(a.out, loc=loc, quat=quat, scl=scl, key=K.key, theta=np.array([thetas[p] for p in range(len(K.key))]), bones=np.array(K.bones)) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/body_pose_fk_export.py b/third_party/UO_Model3D_v13/pipeline/body_pose_fk_export.py new file mode 100644 index 0000000..874788f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_pose_fk_export.py @@ -0,0 +1,45 @@ +"""Export forward-kinematics data of the 210 UO poses (one per action/frame; the 5 directions share the pose), for offline pose fitting. + + python body_pose_fk_export.py ../model/UO_Body_0x190.blend OUT.npz + +Writes: bones (names, same order as body_pose_export.py), parent (B,) index (-1 = root), Lrest (B,4,4) rest matrix of the bone relative to its +parent (armature space for the root), Arest (B,4,4) armature-space rest matrix (bone.matrix_local), key (P,2) = (action, frame), loc (P,B,3), quat (P,B,4) +(w,x,y,z), scl (P,B,3) = local pose basis of every bone at frame 1+3*frame, P (P,B,4,4) armature-space pose matrix (Blender's pose_bone.matrix). +noscale (B,) bool = inherit_scale NONE (the parent's scale is not inherited; the offset still is). +Pose bone matrix = P[parent] @ Lrest @ T(loc) R(quat) S(scl) (checked against P by body_pose_lib.py). +""" +import sys, os +import numpy as np +import bpy + +STEP = 3 + + +def main(): + blend, out = os.path.abspath(sys.argv[1]), os.path.abspath(sys.argv[2]) + bpy.ops.wm.open_mainfile(filepath=blend) + rig, body = bpy.data.objects["UO_Rig"], bpy.data.objects["UO_Body"] + names = [g.name for g in body.vertex_groups] + idx = {n: i for i, n in enumerate(names)} + parent = np.array([idx[rig.data.bones[n].parent.name] if rig.data.bones[n].parent else -1 for n in names]) + assert all(p >= 0 or n == "pelvis" for p, n in zip(parent, names)), "a skinned bone has a parent outside the vertex groups" + Arest = np.array([np.array(rig.data.bones[n].matrix_local) for n in names]) + Lrest = np.array([Arest[i] if parent[i] < 0 else np.linalg.inv(Arest[parent[i]]) @ Arest[i] for i in range(len(names))]) + rig.data.pose_position = "POSE" + sc = bpy.context.scene + acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) + noscale = np.array([rig.data.bones[n].inherit_scale == "NONE" for n in names]) + keys, loc, quat, scl, P = [], [], [], [], [] + for act in acts: + rig.animation_data.action = act + for i in range(int(act["uo_frames"])): + sc.frame_set(1 + i * STEP); bpy.context.view_layer.update() + keys.append((int(act["uo_action"]), i)) + loc.append([list(rig.pose.bones[n].location) for n in names]); quat.append([list(rig.pose.bones[n].rotation_quaternion) for n in names]) + scl.append([list(rig.pose.bones[n].scale) for n in names]); P.append([np.array(rig.pose.bones[n].matrix) for n in names]) + np.savez_compressed(out, bones=np.array(names), parent=parent, noscale=noscale, Lrest=Lrest, Arest=Arest, key=np.array(keys), loc=np.array(loc), quat=np.array(quat), scl=np.array(scl), P=np.array(P)) + print("poses", len(keys), "bones", len(names)) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/body_pose_lib.py b/third_party/UO_Model3D_v13/pipeline/body_pose_lib.py new file mode 100644 index 0000000..19300c4 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_pose_lib.py @@ -0,0 +1,78 @@ +"""Offline forward kinematics of the 210 UO poses (numpy only), from the data of body_pose_fk_export.py. + + K = FK("fk.npz"); loc, quat, scl = K.params(p) # local pose basis of pose p, all bones + M = K.skin(loc, quat, scl) # (B,4,4) skinning matrices pose @ rest^-1, same as pose.npz `M` + +Pose bone matrix = P[parent] @ Lrest @ T(loc) R(quat) S(scl); skinning matrix = P @ inv(Arest). +""" +import numpy as np + + +def quat_to_mat(q): + q = q / np.linalg.norm(q, axis=-1, keepdims=True) + w, x, y, z = q[..., 0], q[..., 1], q[..., 2], q[..., 3] + R = np.empty(q.shape[:-1] + (3, 3)) + R[..., 0, 0] = 1 - 2 * (y * y + z * z); R[..., 0, 1] = 2 * (x * y - z * w); R[..., 0, 2] = 2 * (x * z + y * w) + R[..., 1, 0] = 2 * (x * y + z * w); R[..., 1, 1] = 1 - 2 * (x * x + z * z); R[..., 1, 2] = 2 * (y * z - x * w) + R[..., 2, 0] = 2 * (x * z - y * w); R[..., 2, 1] = 2 * (y * z + x * w); R[..., 2, 2] = 1 - 2 * (x * x + y * y) + return R + + +def qmul(a, b): + w1, x1, y1, z1 = a[..., 0], a[..., 1], a[..., 2], a[..., 3] + w2, x2, y2, z2 = b[..., 0], b[..., 1], b[..., 2], b[..., 3] + return np.stack([w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2, w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2, + w1 * y2 - x1 * z2 + y1 * w2 + z1 * x2, w1 * z2 + x1 * y2 - y1 * x2 + z1 * w2], -1) + + +def rotvec_to_quat(v): + a = np.linalg.norm(v, axis=-1, keepdims=True); s = np.where(a > 1e-12, np.sin(a / 2) / np.maximum(a, 1e-12), 0.5) + return np.concatenate([np.cos(a / 2), v * s], -1) + + +class FK: + def __init__(self, npz): + d = np.load(npz) + self.bones = [str(b) for b in d["bones"]]; self.parent = d["parent"]; self.Lrest = d["Lrest"]; self.Arest = d["Arest"] + self.noscale = d["noscale"] if "noscale" in d.files else np.zeros(len(self.bones), bool) + self.Ainv = np.linalg.inv(self.Arest); self.key = d["key"]; self.loc, self.quat, self.scl, self.P = d["loc"], d["quat"], d["scl"], d["P"] + self.B = len(self.bones); self.idx = {n: i for i, n in enumerate(self.bones)} + # subtree[b] = bool mask of the bones below (and including) b; order: parents precede children? + self.order = self._order() + self.sub = np.zeros((self.B, self.B), bool) + for b in range(self.B): + k = b + while k >= 0: + self.sub[k, b] = True; k = self.parent[k] + self.pose_index = {(int(a), int(i)): p for p, (a, i) in enumerate(self.key)} + + def _order(self): + o, seen = [], set() + def visit(b): + if b in seen: return + if self.parent[b] >= 0: visit(self.parent[b]) + seen.add(b); o.append(b) + for b in range(len(self.parent)): visit(b) + return o + + def basis(self, loc, quat, scl): + Bm = np.zeros((self.B, 4, 4)); Bm[:, 3, 3] = 1 + Bm[:, :3, :3] = quat_to_mat(quat) * scl[:, None, :] # R S + Bm[:, :3, 3] = loc + return Bm + + def pose(self, loc, quat, scl): + Bm = self.basis(loc, quat, scl); P = np.zeros((self.B, 4, 4)) + for b in self.order: + L = self.Lrest[b] @ Bm[b] + if self.parent[b] < 0: + P[b] = L + elif self.noscale[b]: # inherit_scale NONE: rotation/scale part from the parent with its scale removed, position as usual + Pp = P[self.parent[b]]; Rn = Pp[:3, :3] / np.linalg.norm(Pp[:3, :3], axis=0, keepdims=True) + P[b] = Pp @ L; P[b][:3, :3] = Rn @ L[:3, :3] + else: + P[b] = P[self.parent[b]] @ L + return P + + def skin(self, loc, quat, scl): + return self.pose(loc, quat, scl) @ self.Ainv diff --git a/third_party/UO_Model3D_v13/pipeline/body_shape_apply.py b/third_party/UO_Model3D_v13/pipeline/body_shape_apply.py new file mode 100644 index 0000000..d05918e --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_shape_apply.py @@ -0,0 +1,23 @@ +"""Apply a rest-shape displacement D (body_shape_fit.py output, key "D" (N,3) metres) to the body mesh of a .blend and save it. + + python body_shape_apply.py ../model/UO_Body_0x190.blend D.npz OUT.blend [--scale 1.0] + +D is added to the vertex coordinates of the rest mesh `UO_Body` (no shape keys, so skinning, UVs, weights and materials stay as they are). +Refuses to run when the mesh already differs from the one D was fitted on (vertex count) or has shape keys. +""" +import sys +import numpy as np +import bpy + +blend, dnpz, out = sys.argv[1], sys.argv[2], sys.argv[3] +scale = float(sys.argv[sys.argv.index("--scale") + 1]) if "--scale" in sys.argv else 1.0 +bpy.ops.wm.open_mainfile(filepath=blend) +body = bpy.data.objects["UO_Body"]; me = body.data +D = np.load(dnpz)["D"] +assert len(me.vertices) == len(D), "vertex count differs" +assert me.shape_keys is None, "body has shape keys" +co = np.empty(len(me.vertices) * 3, np.float32); me.vertices.foreach_get("co", co) +co = co.reshape(-1, 3) + scale * D.astype(np.float32) +me.vertices.foreach_set("co", co.ravel()); me.update() +bpy.ops.wm.save_as_mainfile(filepath=out) +print("saved", out, "mean |D| %.4f m, max %.4f m" % (np.linalg.norm(D, axis=1).mean() * scale, np.linalg.norm(D, axis=1).max() * scale)) diff --git a/third_party/UO_Model3D_v13/pipeline/body_shape_delta.npz b/third_party/UO_Model3D_v13/pipeline/body_shape_delta.npz new file mode 100644 index 0000000..9fc7b72 Binary files /dev/null and b/third_party/UO_Model3D_v13/pipeline/body_shape_delta.npz differ diff --git a/third_party/UO_Model3D_v13/pipeline/body_shape_fit.py b/third_party/UO_Model3D_v13/pipeline/body_shape_fit.py new file mode 100644 index 0000000..b2b7f1b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_shape_fit.py @@ -0,0 +1,155 @@ +"""Silhouette-driven refinement of the REST shape of the body (displacement D of the rest vertices, shared by all frames). + + python body_shape_fit.py pose.npz --out D.npz [--iters 4] [--lam 30] [--mu 1] [--holdout 5] + +Poses stay as they are. For every frame the contour vertices of the model (projected within 1 px of the model silhouette, facing sideways) +are compared with the sprite silhouette: signed distance s (px) of the vertex to the sprite contour. Each (vertex, frame) gives one linear +constraint on the rest displacement d_v: g . d_v = -s with g = A^T J^T n (A: skinning linear part, J: camera Jacobian, n: 2D outward normal). +The per-vertex normal equations are solved together with a mesh-Laplacian smoothness + small-norm prior (sparse solve). Frames of the +hold-out actions (action % holdout == 2) are not used for the fit and only scored. Needs numpy, scipy, pillow. +""" +import argparse, sys, time +import numpy as np +import scipy.sparse as sp +import scipy.sparse.linalg as spl +from scipy.ndimage import distance_transform_edt, map_coordinates +import body_shape_lib as L + + +def signed_dist(m): + """signed distance (px) from pixel centres to the contour of mask m (positive outside)""" + if not m.any(): + return np.full(m.shape, 50.0) + return np.where(m, -(distance_transform_edt(m) - 0.5), distance_transform_edt(~m) - 0.5) + + +def vertex_normals(X, tris): + n = np.cross(X[tris[:, 1]] - X[tris[:, 0]], X[tris[:, 2]] - X[tris[:, 0]]) + out = np.zeros_like(X) + for k in range(3): + np.add.at(out, tris[:, k], n) + return out / np.maximum(np.linalg.norm(out, axis=1, keepdims=True), 1e-12) + + +def laplacian(N, tris, rest=None, floor=0.005): + """graph Laplacian; with `rest` the edges are weighted 1/length (floor 5 mm): short edges (eyes, mouth, fingers) hold their vertices together""" + E = np.sort(np.concatenate([tris[:, [0, 1]], tris[:, [1, 2]], tris[:, [2, 0]]]), 1) + E = np.unique(E, axis=0) + w = np.ones(len(E)) if rest is None else 0.02 / np.maximum(np.linalg.norm(rest[E[:, 0]] - rest[E[:, 1]], axis=1), floor) + A = sp.coo_matrix((w, (E[:, 0], E[:, 1])), shape=(N, N)); A = A + A.T + return sp.diags(np.asarray(A.sum(1)).ravel()) - A + + +def mesh_report(S, D): + """rest mesh quality after D: flipped faces and edge-length ratio percentiles""" + t, r0, r1 = S.tris, S.rest, S.rest + D + fn = lambda X: (lambda n: n / np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12))(np.cross(X[t[:, 1]] - X[t[:, 0]], X[t[:, 2]] - X[t[:, 0]])) + flips = int(((fn(r0) * fn(r1)).sum(1) < 0).sum()) + E = np.unique(np.sort(np.concatenate([t[:, [0, 1]], t[:, [1, 2]], t[:, [2, 0]]]), 1), axis=0) + ratio = np.linalg.norm(r1[E[:, 0]] - r1[E[:, 1]], axis=1) / np.maximum(np.linalg.norm(r0[E[:, 0]] - r0[E[:, 1]], axis=1), 1e-9) + return flips, np.percentile(ratio, [0, 1, 99, 100]) + + +def repair_flips(S, D, passes=12): + """halve the displacement of the vertices of faces that the displacement flips (thumb, toes: tiny faces), until none is left""" + t, r0 = S.tris, S.rest + fn = lambda X: (lambda n: n / np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12))(np.cross(X[t[:, 1]] - X[t[:, 0]], X[t[:, 2]] - X[t[:, 0]])) + n0 = fn(r0); D = D.copy() + for _ in range(passes): + bad = np.nonzero((n0 * fn(r0 + D)).sum(1) < 0.1)[0] + if not len(bad): + break + D[np.unique(t[bad])] *= 0.5 + return D + + +def constraints(S, D, frames, clip=2.0, band=1.0, side=0.6, verbose=False): + """normal equations H (N,3,3), b (N,3) from the contour vertices of `frames`""" + H = np.zeros((S.N, 3, 3)); b = np.zeros((S.N, 3)); cnt = np.zeros(S.N) + for f in frames: + m, lab, depth, X, xy, z = L.model_mask(S, f, D) + smd = signed_dist(m); sdg = signed_dist(S.G[f]) + pc = np.stack([xy[:, 1] - 0.5, xy[:, 0] - 0.5]) # map_coordinates wants (row, col) in pixel-centre index space + s_m = map_coordinates(smd, pc, order=1, mode="nearest"); s_g = map_coordinates(sdg, pc, order=1, mode="nearest") + ix = np.clip(xy[:, 0].astype(int), 0, S.CW - 1); iy = np.clip(xy[:, 1].astype(int), 0, S.CH - 1) + vis = z <= depth[iy, ix] + 0.03 + if S.hm[f].any(): # near the horse the contour is the horse's, not the body's + from scipy.ndimage import binary_dilation + vis &= ~binary_dilation(S.hm[f], iterations=2)[iy, ix] + Xn = vertex_normals(X, S.tris) + # camera forward axis in body-local space: nz = normal . view + T = S.Vm @ S.MW[f]; view = np.linalg.inv(T)[:3, :3] @ np.array([0, 0, 1.0]) + nz = np.abs(Xn @ view) / np.linalg.norm(view) + sel = vis & (np.abs(s_m) < band) & (nz < side) & (np.abs(s_g) < 6) + if not sel.any(): + continue + idx = np.nonzero(sel)[0] + # 2D outward normal from the gradient of the model sdf + gy, gx = np.gradient(smd) + ny = map_coordinates(gy, pc[:, idx], order=1, mode="nearest"); nx = map_coordinates(gx, pc[:, idx], order=1, mode="nearest") + nn = np.hypot(nx, ny); good = nn > 1e-6 + idx, nx, ny, nn = idx[good], nx[good], ny[good], nn[good] + n2 = np.stack([nx, ny], 1) / nn[:, None] + # Jacobian of pixel position wrt body-local position: orthographic -> constant 2x3 (take it from the projection matrix) + Pt = (S.Pm @ S.Vm @ S.MW[f])[:2, :3]; Pw = (S.Pm @ S.Vm @ S.MW[f])[3, :3] + # orthographic: w = 1, so xy = ((Pt X + t)+1)/2 * (CW, -CH) ... + J = np.stack([Pt[0] * 0.5 * S.CW, -Pt[1] * 0.5 * S.CH]) # (2,3) px per metre of body-local displacement + A = S.linear(f)[idx] # (n,3,3) + g = np.einsum("nk,ki,nij->nj", n2, J, A) # (n,3): px of contour shift per metre of rest displacement + t = -np.clip(s_g[idx] - s_m[idx], -clip, clip) # outward shift (px) that moves the model contour onto the sprite contour + w = 1.0 + H[idx] += w * g[:, :, None] * g[:, None, :]; b[idx] += w * (g * (t + np.einsum("nj,nj->n", g, D[idx]))[:, None]) + cnt[idx] += 1 + return H, b, cnt + + +def solve_normal(S, H, b, lam, mu, Lap, n): + """displacement along the rest normal only: d_v = s_v n_v, scalar field s (a mesh can't tear or fold much when vertices only slide out / in)""" + Hs = np.einsum("ni,nij,nj->n", n, H, n); bs = np.einsum("ni,ni->n", n, b) + s = spl.spsolve((sp.diags(Hs) + lam * Lap + mu * sp.identity(S.N)).tocsc(), bs) + return s[:, None] * n + + +def solve(S, H, b, lam, mu, Lap, bilap=False): + N = S.N + cols = np.repeat(np.arange(3 * N).reshape(N, 3)[:, None, :], 3, 1).ravel() + rows = np.repeat(np.arange(3 * N).reshape(N, 3)[:, :, None], 3, 2).ravel() + Hs = sp.coo_matrix((H.ravel(), (rows, cols)), shape=(3 * N, 3 * N)).tocsc() + Lm = (Lap.T @ Lap) / 8.0 if bilap else Lap # bilap: penalises the roughness of D (bending), /8 ~ mean degree^2/... scale + K = sp.kron(Lm, sp.identity(3)).tocsc() + Aff = Hs + lam * K + mu * sp.identity(3 * N) + return spl.spsolve(Aff.tocsc(), b.ravel()).reshape(N, 3) + + +def main(): + ap = argparse.ArgumentParser(); ap.add_argument("pose"); ap.add_argument("--out"); ap.add_argument("--iters", type=int, default=3) + ap.add_argument("--lam", type=float, default=30.0); ap.add_argument("--mu", type=float, default=1.0); ap.add_argument("--holdout", type=int, default=5) + ap.add_argument("--weighted", action="store_true", help="edge weights 1/length in the smoothness term"); ap.add_argument("--bilap", action="store_true"); ap.add_argument("--normal", action="store_true", help="displace along the rest normal only"); ap.add_argument("--holdout-dir", type=int, default=-1); ap.add_argument("--clip", type=float, default=2.0); ap.add_argument("--maxd", type=float, default=0.04) + a = ap.parse_args() + S = L.Scene(a.pose); Lap = laplacian(S.N, S.tris, S.rest if a.weighted else None); RN = vertex_normals(S.rest, S.tris) + act = S.key[:, 0] + hk = (act % a.holdout == 2) if a.holdout > 0 else np.zeros(len(act), bool) + test = np.nonzero(S.ok & hk)[0]; train = np.nonzero(S.ok & ~hk)[0] + if a.holdout_dir >= 0: # stricter test: a whole direction (a view never used by the fit) + test = np.nonzero(S.ok & (S.key[:, 1] == a.holdout_dir))[0]; train = np.nonzero(S.ok & (S.key[:, 1] != a.holdout_dir))[0] + if a.holdout <= 0: # final fit: all frames (the 'test' numbers are then in-sample) + test = train + D = np.zeros((S.N, 3)) + r0 = L.score(S, D, test); r1 = L.score(S, D, train) + print("start: train IoU %.4f test IoU %.4f" % (r1["iou"], r0["iou"]), flush=True) + for it in range(a.iters): + t0 = time.time() + H, b, cnt = constraints(S, D, train, clip=a.clip) + Dn = solve_normal(S, H, b, a.lam, a.mu, Lap, RN) if a.normal else solve(S, H, b, a.lam, a.mu, Lap, a.bilap) + nrm = np.linalg.norm(Dn, axis=1); sc = np.minimum(1.0, a.maxd / np.maximum(nrm, 1e-12)); D = repair_flips(S, Dn * sc[:, None]) + r0 = L.score(S, D, test); r1 = L.score(S, D, train) + print("iter %d: constrained verts %d |D| mean %.4f max %.4f m train IoU %.4f (out %.1f miss %.1f) test IoU %.4f (out %.1f miss %.1f) %.0fs" % + (it, (cnt > 0).sum(), nrm.mean(), nrm.max(), r1["iou"], r1["outside"], r1["missing"], r0["iou"], r0["outside"], r0["missing"], time.time() - t0), flush=True) + fl, er = mesh_report(S, D) + print(" mesh: flipped faces %d edge ratio min %.2f p1 %.2f p99 %.2f max %.2f" % ((fl,) + tuple(er)), flush=True) + if a.out: + np.savez_compressed(a.out, D=D) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/body_shape_lib.py b/third_party/UO_Model3D_v13/pipeline/body_shape_lib.py new file mode 100644 index 0000000..e97aa8f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_shape_lib.py @@ -0,0 +1,115 @@ +"""Offline (numpy-only) body evaluation: skinning, rasteriser and silhouette scores from the data of body_pose_export.py. + + import body_shape_lib as L + S = L.Scene("pose.npz"); D = np.zeros((S.N, 3)) # D: displacement of the REST vertices (m) + print(L.score(S, D)) # mean IoU etc. over the 1050 frames + +All geometry is in the canvas of the original UO frames (145x133, anchor (75,92), 36 px/m). +""" +import json, os +import numpy as np +from PIL import Image +from scipy.ndimage import distance_transform_edt + +HERE = os.path.dirname(os.path.abspath(__file__)) +ORIG = os.path.join(HERE, "..", "client", "body_0x190_frames") + + +def sprite_masks(keys): + meta = json.load(open(os.path.join(ORIG, "meta.json"))); W, H = meta["canvas"]; out = {} + for blk in meta["blocks"]: + act = "%02d_%s" % (blk["action"], blk["name"]) + for i, fr in enumerate(blk["frames"]): + p = os.path.join(ORIG, "frames", act, "dir%d" % blk["dir"], fr["file"]) + out[(blk["action"], blk["dir"], i)] = np.array(Image.open(p).convert("RGBA"))[..., 3] > 0 if os.path.exists(p) else np.zeros((H, W), bool) + return np.array([out[tuple(k)] for k in keys]) + + +class Scene: + def __init__(self, npz): + d = np.load(npz) + self.rest, self.wi, self.ww, self.tris = d["rest"], d["wi"], d["ww"], d["tris"] + self.M = d["M"].astype(np.float64); self.MW = d["MW"]; self.key = d["key"] + self.Pm, self.Vm = d["Pm"], d["Vm"]; self.CW, self.CH = [int(x) for x in d["canvas"]] + self.hd, self.hm = d["horse_depth"], d["horse_mask"]; self.bones = [str(b) for b in d["bones"]] + self.N, self.F = len(self.rest), len(self.key) + self.resid = {} + if "resid_idx" in d.files: # Blender's evaluated mesh minus plain LBS (sparse), see body_pose_export.py + fr, ix, vl = d["resid_frame"], d["resid_idx"], d["resid_val"] + for f in np.unique(fr): + k = fr == f; self.resid[int(f)] = (ix[k], vl[k].astype(np.float64)) + self.G = sprite_masks(self.key) + self.ok = self.G.any((1, 2)) + # camera: world -> pixel (x, y) and depth, as a 3x4 matrix per frame (body-local -> pixel through skinning is applied first) + self.VP = [] + for f in range(self.F): + T = self.Pm @ self.Vm @ self.MW[f] + self.VP.append(T) + self.VP = np.array(self.VP) + + def posed(self, f, D=None, rest=None): + """body-local posed vertices of frame f (LBS of rest (+D))""" + R = self.rest if rest is None else rest + if D is not None: + R = R + D + R4 = np.c_[R, np.ones(len(R))] + Mb = self.M[f][self.wi] # (N,K,4,4) + X = np.einsum("nkij,nj->nki", Mb, R4)[..., :3] + X = (X * self.ww[..., None]).sum(1) + if f in self.resid: + X = X.copy(); X[self.resid[f][0]] += self.resid[f][1] + return X + + def linear(self, f): + """3x3 linear part of the skinning at every vertex: posed displacement = A @ rest displacement""" + return np.einsum("nk,nkij->nij", self.ww, self.M[f][self.wi][..., :3, :3]) + + def project(self, f, X): + """pixel xy (N,2) and camera depth (N,) of body-local points""" + hv = np.c_[X, np.ones(len(X))] @ self.VP[f].T + # VP = Pm @ Vm @ MW: homogeneous clip coordinates + ndc = hv[:, :2] / hv[:, 3:4] + xy = np.stack([(ndc[:, 0] + 1) * 0.5 * self.CW, (1 - ndc[:, 1]) * 0.5 * self.CH], 1) + z = -(np.c_[X, np.ones(len(X))] @ (self.Vm @ self.MW[f]).T)[:, 2] + return xy, z + + +def raster(xy, z, tris, CW, CH, label=None): + """nearest-triangle label (default: triangle index) and depth per pixel, pixel-centre rule. Returns (label (H,W) int32 (-1 empty), depth)""" + P = xy[tris]; Z = z[tris] + lab = np.full((CH, CW), -1, np.int32); depth = np.full((CH, CW), np.inf) + mn = np.floor(P.min(1)).astype(int); mx = np.ceil(P.max(1)).astype(int) + A, B, C = P[:, 0], P[:, 1], P[:, 2] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + ok = np.abs(den) > 1e-12; size = np.clip(mx - mn, 0, 16) + lt = np.arange(len(tris)) if label is None else label + for dy in range(int(size[:, 1].max(initial=0)) + 1): + for dx in range(int(size[:, 0].max(initial=0)) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px_ = mn[t, 0] + dx; py_ = mn[t, 1] + dy; cx, cy = px_ + 0.5, py_ + 0.5 + l0 = ((B[t, 1] - C[t, 1]) * (cx - C[t, 0]) + (C[t, 0] - B[t, 0]) * (cy - C[t, 1])) / den[t] + l1 = ((C[t, 1] - A[t, 1]) * (cx - C[t, 0]) + (A[t, 0] - C[t, 0]) * (cy - C[t, 1])) / den[t] + kk = (l0 >= -1e-4) & (l1 >= -1e-4) & (1 - l0 - l1 >= -1e-4) & (px_ >= 0) & (py_ >= 0) & (px_ < CW) & (py_ < CH) + zz = l0[kk] * Z[t[kk], 0] + l1[kk] * Z[t[kk], 1] + (1 - l0[kk] - l1[kk]) * Z[t[kk], 2] + tt, yy, xx = t[kk], py_[kk], px_[kk] + o = np.argsort(-zz); o = o[zz[o] < depth[yy[o], xx[o]]] + depth[yy[o], xx[o]] = zz[o]; lab[yy[o], xx[o]] = lt[tt[o]] + return lab, depth + + +def model_mask(S, f, D=None, rest=None): + X = S.posed(f, D, rest); xy, z = S.project(f, X) + lab, depth = raster(xy, z, S.tris, S.CW, S.CH) + m = lab >= 0 + hide = S.hm[f] & (S.hd[f] < depth) + m &= ~hide + return m, lab, depth, X, xy, z + + +def score(S, D=None, frames=None, rest=None): + fr = np.nonzero(S.ok)[0] if frames is None else np.asarray(frames) + iou = np.zeros(len(fr)); out = np.zeros(len(fr)); miss = np.zeros(len(fr)) + for n, f in enumerate(fr): + m = model_mask(S, f, D, rest)[0]; g = S.G[f] + iou[n] = (m & g).sum() / max((m | g).sum(), 1); out[n] = (m & ~g).sum(); miss[n] = (g & ~m).sum() + return dict(iou=float(iou.mean()), outside=float(out.mean()), missing=float(miss.mean()), per_frame=iou) diff --git a/third_party/UO_Model3D_v13/pipeline/body_shape_overlay.py b/third_party/UO_Model3D_v13/pipeline/body_shape_overlay.py new file mode 100644 index 0000000..ca13c83 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_shape_overlay.py @@ -0,0 +1,21 @@ +"""Overlay PNG: model silhouette before / after a rest-shape displacement D against the sprite (grey = both, red = sprite only, blue = model only). + + python body_shape_overlay.py pose.npz D.npz OUT.png [a,d,i ...] e.g. 9,1,2 21,3,0 +""" +import sys +import numpy as np +from PIL import Image +import body_shape_lib as L + +S = L.Scene(sys.argv[1]); D = np.load(sys.argv[2])["D"]; out = sys.argv[3] +want = [tuple(int(x) for x in a.split(",")) for a in sys.argv[4:]] or [(4, 0, 0), (9, 1, 2), (17, 2, 3), (21, 3, 2), (0, 4, 1)] +idx = {tuple(k): j for j, k in enumerate(S.key)} +rows = [] +for k in want: + f = idx[k]; g = S.G[f]; tiles = [] + for DD in (None, D): + m = L.model_mask(S, f, DD)[0] + im = np.zeros(g.shape + (3,), np.uint8); im[g & m] = (200, 200, 200); im[g & ~m] = (255, 40, 40); im[m & ~g] = (60, 90, 255) + tiles.append(im) + rows.append(np.hstack(tiles)) +Image.fromarray(np.vstack(rows)).resize((rows[0].shape[1] * 4, sum(r.shape[0] for r in rows) * 4), Image.NEAREST).save(out) diff --git a/third_party/UO_Model3D_v13/pipeline/body_silhouette_qa.py b/third_party/UO_Model3D_v13/pipeline/body_silhouette_qa.py new file mode 100644 index 0000000..c36b9b6 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/body_silhouette_qa.py @@ -0,0 +1,58 @@ +"""Body QA: silhouette of the pure 3D body (render with EXACT_BODY=False, EXACT_COLORS=False, 136x120 / (68,86)) against the original UO +body frames (client/body_0x190_frames, canvas 145x133, anchor (75,92)). + + python run_render_headless.py ../model/UO_Body_0x190.blend OUT LAYER='"body"' EXACT_BODY=False EXACT_COLORS=False CANVAS='(136,120)' ANCHOR='(68,86)' + python body_silhouette_qa.py OUT/body/frames [--out ../docs/qa/body_silhouette.json] [--bias bias.png] + +Per action / direction: IoU, area ratio (render / original: > 1 = our body is fatter), `outside` (render only) and `missing` (original only) pixels. +The signed bias map (red = we have extra, blue = we miss) is summed over all frames, in anchor coordinates. +""" +import argparse, json, os, sys +import numpy as np +from PIL import Image + +HERE = os.path.dirname(os.path.abspath(__file__)) +ORIG = os.path.join(HERE, "..", "client", "body_0x190_frames") +OANCH, RANCH = (75, 92), (68, 86) + + +def load(p, size): + return np.array(Image.open(p).convert("RGBA"))[..., 3] > 0 if os.path.exists(p) else np.zeros(size[::-1], bool) + + +def main(): + ap = argparse.ArgumentParser(); ap.add_argument("frames"); ap.add_argument("--out"); ap.add_argument("--bias") + a = ap.parse_args() + meta = json.load(open(os.path.join(ORIG, "meta.json"))) + W, H = meta["canvas"] + rows, bias = [], np.zeros((H, W, 2)) + for blk in meta["blocks"]: + act = "%02d_%s" % (blk["action"], blk["name"]) + for i, fr in enumerate(blk["frames"]): + g = load(os.path.join(ORIG, "frames", act, "dir%d" % blk["dir"], fr["file"]), (W, H)) + r = np.zeros((H, W), bool) + R = load(os.path.join(a.frames, act, "dir%d" % blk["dir"], "%02d.png" % i), (136, 120)) + dx, dy = OANCH[0] - RANCH[0], OANCH[1] - RANCH[1] + r[dy:dy + 120, dx:dx + 136] = R[:H - dy, :W - dx] if R.shape == (120, 136) else R[:120, :136] + if not g.any(): + continue + rows.append(dict(a=blk["action"], d=blk["dir"], i=i, iou=float((r & g).sum() / max((r | g).sum(), 1)), ratio=float(r.sum() / g.sum()), + outside=int((r & ~g).sum()), missing=int((g & ~r).sum()))) + bias[..., 0] += r & ~g; bias[..., 1] += g & ~r + f = lambda k, rs=rows: float(np.mean([x[k] for x in rs])) + out = dict(frames=len(rows), iou=f("iou"), ratio=f("ratio"), outside=f("outside"), missing=f("missing"), + by_action={str(x): float(np.mean([r["iou"] for r in rows if r["a"] == x])) for x in sorted({r["a"] for r in rows})}, + by_dir={str(x): float(np.mean([r["iou"] for r in rows if r["d"] == x])) for x in range(5)}) + print("frames %d IoU %.3f area ratio %.3f outside %.1f missing %.1f" % (out["frames"], out["iou"], out["ratio"], out["outside"], out["missing"])) + print("by dir:", {k: round(v, 3) for k, v in out["by_dir"].items()}) + print("worst actions:", sorted(((round(v, 3), k) for k, v in out["by_action"].items()))[:6]) + if a.out: + os.makedirs(os.path.dirname(os.path.abspath(a.out)), exist_ok=True); json.dump(out, open(a.out, "w"), indent=1) + if a.bias: + m = bias.max() or 1; im = np.zeros((H, W, 3), np.uint8) + 20 + im[..., 0] = np.clip(20 + 235 * bias[..., 0] / m, 0, 255); im[..., 2] = np.clip(20 + 235 * bias[..., 1] / m, 0, 255) + Image.fromarray(im).resize((W * 4, H * 4), Image.NEAREST).save(a.bias) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/bpy_compat.py b/third_party/UO_Model3D_v13/pipeline/bpy_compat.py new file mode 100644 index 0000000..6131d15 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/bpy_compat.py @@ -0,0 +1,61 @@ +"""Blender version differences used by the pipeline scripts (4.2 ... 5.2). + + from bpy_compat import action_fcurves, find_fcurve, clear_fcurves, new_fcurve, eevee_engine + +Blender 5.0 removed the direct Action.fcurves (an action has slots, layers and strips now: the curves of a slot live in a +"channelbag"). The helpers give the same code one answer on both sides of that change. Blender 5.0 also renamed the engine +'BLENDER_EEVEE_NEXT' back to 'BLENDER_EEVEE'. +""" +import bpy + + +def _bags(action, create=False): + """channelbags of an action in 5.x (one per slot); create=True makes slot / layer / strip when the action is empty""" + if create: + if not action.slots: + action.slots.new(id_type="OBJECT", name="Legacy Slot") + if not action.layers: + action.layers.new("Layer") + layer = action.layers[0] + if not layer.strips: + layer.strips.new(type="KEYFRAME") + strip = layer.strips[0] + return [strip.channelbag(action.slots[0], ensure=True)] + return [cb for layer in action.layers for strip in layer.strips if strip.type == "KEYFRAME" for cb in strip.channelbags] + + +def action_fcurves(action): + """list of all F-curves of the action (a live collection before 5.0, a list of the channelbag curves from 5.0)""" + if hasattr(action, "fcurves"): + return action.fcurves + return [fc for cb in _bags(action) for fc in cb.fcurves] + + +def find_fcurve(action, data_path, index=0): + for fc in action_fcurves(action): + if fc.data_path == data_path and fc.array_index == index: + return fc + return None + + +def clear_fcurves(action, data_path=None): + """remove every F-curve of the action (or only those with the given data path)""" + if hasattr(action, "fcurves"): + for fc in [fc for fc in action.fcurves if data_path is None or fc.data_path == data_path]: + action.fcurves.remove(fc) + return + for cb in _bags(action): + for fc in [fc for fc in cb.fcurves if data_path is None or fc.data_path == data_path]: + cb.fcurves.remove(fc) + + +def new_fcurve(action, data_path, index=0): + if hasattr(action, "fcurves"): + return action.fcurves.new(data_path, index=index) + return _bags(action, create=True)[0].fcurves.new(data_path, index=index) + + +def eevee_engine(): + """identifier of the EEVEE render engine of this Blender""" + ids = [e.identifier for e in bpy.types.RenderSettings.bl_rna.properties["engine"].enum_items] + return "BLENDER_EEVEE_NEXT" if "BLENDER_EEVEE_NEXT" in ids else "BLENDER_EEVEE" diff --git a/third_party/UO_Model3D_v13/pipeline/build.py b/third_party/UO_Model3D_v13/pipeline/build.py new file mode 100644 index 0000000..e8566bc --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/build.py @@ -0,0 +1,231 @@ +"""Assemble the final Blender scene: mesh, rig, weights, UVs, projected texture, actions, UO camera; save + export.""" +import os, sys, math, pickle +import numpy as np +import bpy +from mathutils import Vector, Matrix +import jax.numpy as jnp + +from body import fk, zero_pose, JI, NJ, CANVAS_W, CANVAS_H, ANCHOR_X, ANCHOR_Y +from fit import params_to_shape, pose_from_params +from basemesh import build_base_mesh, symmetrize +from rig import build_armature, apply_pose +from texbake import bake, pull_push_fill +from targets import targets +from vd import ACTIONS_PEOPLE +from bpy_compat import eevee_engine + +OUT = sys.argv[sys.argv.index("--out") + 1] if "--out" in sys.argv else "out" +os.makedirs(OUT, exist_ok=True) +FPS, STEP = 24, 3 # one UO frame every 3 scene frames (8 UO frames / s) + +bpy.ops.wm.read_factory_settings(use_empty=True) +bpy.context.preferences.filepaths.save_version = 0 +sc = bpy.context.scene +sc.render.fps = FPS + +SHAPE = sys.argv[sys.argv.index("--shape") + 1] if "--shape" in sys.argv else "shape_fit.pkl" +sf = pickle.load(open(SHAPE, "rb")) +fixed = {k: jnp.asarray(v) for k, v in sf["fixed"].items()} +S = params_to_shape({k: jnp.asarray(v) for k, v in sf["params"]["shape"].items()}, fixed) +Snp = {k: np.asarray(v, np.float64) for k, v in S.items()} +anim = pickle.load(open("anim_fit.pkl", "rb")) if os.path.exists("anim_fit.pkl") and "--no-anim" not in sys.argv else {} +stand_pp = {k: v[0] for k, v in anim[4]["poses"].items()} if 4 in anim else \ + {k: v[0] for k, v in sf["params"]["poses"].items()} + +# ------------------------------------------------------------------ mesh +v, faces, parts, P = build_base_mesh(S, subdiv=2) +v, mirror, ok = symmetrize(v) +mirror = np.where(ok, mirror, np.arange(len(v))) +me = bpy.data.meshes.new("UO_Body") +me.from_pydata(v.tolist(), [], faces) +me.update() +me.use_mirror_x = True +for p in me.polygons: + p.use_smooth = True +body = bpy.data.objects.new("UO_Body", me) +sc.collection.objects.link(body) + +# ------------------------------------------------------------------ rig + weights +arm, bone_joint = build_armature(S, np.asarray(P)) +bpy.ops.object.select_all(action="DESELECT") +body.select_set(True); arm.select_set(True) +bpy.context.view_layer.objects.active = arm +bpy.ops.object.parent_set(type="ARMATURE_AUTO") +arm["uo_body_id"] = 0x190 + +# ------------------------------------------------------------------ UVs +bpy.ops.object.select_all(action="DESELECT") +bpy.context.view_layer.objects.active = body +body.select_set(True) +bpy.ops.object.mode_set(mode="EDIT") +bpy.ops.mesh.select_all(action="SELECT") +bpy.ops.uv.smart_project(angle_limit=math.radians(60), island_margin=0.006, scale_to_bounds=False) +bpy.ops.object.mode_set(mode="OBJECT") + +# ------------------------------------------------------------------ texture projection (stand pose) +def posed_vertices(rot, trans): + apply_pose(arm, bone_joint, rot, trans) + bpy.context.view_layer.update() + dg = bpy.context.evaluated_depsgraph_get() + ev = body.evaluated_get(dg) + m = ev.to_mesh() + out = np.array([x.co[:] for x in m.vertices]) + ev.to_mesh_clear() + return out + +pose = pose_from_params({k: jnp.asarray(v_) for k, v_ in stand_pp.items()}) +posed = posed_vertices(np.asarray(pose["rot"]), np.asarray(pose["trans"])) +loops_v = np.zeros(len(me.loops), np.int64); me.loops.foreach_get("vertex_index", loops_v) +uv = np.zeros(len(me.loops) * 2); me.uv_layers.active.data.foreach_get("uv", uv); uv = uv.reshape(-1, 2) +tris, tri_uv = [], [] +for poly in me.polygons: + ls = list(poly.loop_indices) + for k in range(1, len(ls) - 1): + tri = [ls[0], ls[k], ls[k + 1]] + tris.append(loops_v[tri]); tri_uv.append(uv[tri]) +tris = np.array(tris); tri_uv = np.array(tri_uv) +spr = [s for s in targets(4)[0]] +TEX = 1024 +tex, wt, cover = bake(tris, tri_uv, posed, mirror, spr, float(Snp["theta"]), float(Snp["scale"]), size=TEX) +print("texture coverage: %.1f%% of UV area" % (100 * wt[cover].mean())) +filled = pull_push_fill(tex, wt) +SKIN_RAMP = [(0.0, (0.10, 0.06, 0.04)), (0.45, (0.55, 0.37, 0.27)), (0.8, (0.93, 0.74, 0.60)), (1.0, (1.0, 0.90, 0.80))] + + +def apply_partial_hue(rgb): + """UO 'partial hue': grey pixels are recoloured by the hue ramp, coloured pixels (loincloth) kept.""" + g = rgb.mean(-1) + sat = (rgb.max(-1) - rgb.min(-1)) / np.maximum(rgb.max(-1), 1e-6) + xs = [p for p, _ in SKIN_RAMP] + ramp = np.stack([np.interp(g, xs, [c[i] for _, c in SKIN_RAMP]) for i in range(3)], -1) + f = np.clip((sat - 0.10) / 0.10, 0, 1)[..., None] + return ramp * (1 - f) + rgb * f + + +def save_image(name, rgb01): + im = bpy.data.images.new(name, TEX, TEX, alpha=False) + px = np.ones((TEX, TEX, 4), np.float32) + px[..., :3] = np.clip(rgb01[::-1], 0, 1) + im.pixels.foreach_set(px.ravel()) + im.filepath_raw = os.path.abspath(os.path.join(OUT, name + ".png")) + im.file_format = "PNG" + im.save() + return im + + +grey = filled / 255.0 +body_px = grey[wt > 0].mean(-1) +grey = np.clip(grey * (0.88 / np.percentile(body_px, 92)), 0, 1) # normalise brightness +img_grey = save_image("UO_Body_Texture_grey", grey) +img_col = save_image("UO_Body_Texture", apply_partial_hue(grey)) + +# rest pose back +apply_pose(arm, bone_joint, np.zeros((NJ, 3)), np.zeros(3)) + +# ------------------------------------------------------------------ material +# Default: coloured texture. Alternative node chain kept in the material: grey UO texture -> skin ramp +# (mimics how the UO client hues the grey body); switch by connecting "Hue mix" to Base Color. +mat = bpy.data.materials.new("UO_Skin") +mat.use_nodes = True +nt = mat.node_tree +bsdf = nt.nodes["Principled BSDF"] +bsdf.inputs["Roughness"].default_value = 0.7 +tc = nt.nodes.new("ShaderNodeTexImage"); tc.image = img_col; tc.location = (-500, 350); tc.label = "Skin (coloured)" +nt.links.new(tc.outputs["Color"], bsdf.inputs["Base Color"]) +tg = nt.nodes.new("ShaderNodeTexImage"); tg.image = img_grey; tg.location = (-1300, -50); tg.label = "UO grey (hue-able)" +tg.image.colorspace_settings.name = "sRGB" +ramp = nt.nodes.new("ShaderNodeValToRGB"); ramp.location = (-950, -50); ramp.label = "Skin hue" +cr = ramp.color_ramp +while len(cr.elements) > 1: + cr.elements.remove(cr.elements[-1]) +cr.elements[0].position = SKIN_RAMP[0][0]; cr.elements[0].color = (*SKIN_RAMP[0][1], 1) +for pos, c in SKIN_RAMP[1:]: + e = cr.elements.new(pos); e.color = (*c, 1) +bw = nt.nodes.new("ShaderNodeRGBToBW"); bw.location = (-1100, -250) +nt.links.new(tg.outputs["Color"], bw.inputs["Color"]) +nt.links.new(bw.outputs["Val"], ramp.inputs["Fac"]) +sep = nt.nodes.new("ShaderNodeSeparateColor"); sep.mode = "HSV"; sep.location = (-1100, -400) +nt.links.new(tg.outputs["Color"], sep.inputs["Color"]) +mr = nt.nodes.new("ShaderNodeMapRange"); mr.location = (-900, -400) +mr.inputs["From Min"].default_value = 0.10; mr.inputs["From Max"].default_value = 0.20 +nt.links.new(sep.outputs[1], mr.inputs["Value"]) +hm = nt.nodes.new("ShaderNodeMix"); hm.data_type = "RGBA"; hm.location = (-650, -150); hm.label = "Hue mix" +nt.links.new(mr.outputs["Result"], hm.inputs["Factor"]) +nt.links.new(ramp.outputs["Color"], hm.inputs[6]) +nt.links.new(tg.outputs["Color"], hm.inputs[7]) +me.materials.append(mat) + +# ------------------------------------------------------------------ actions +arm.animation_data_create() +first_action = None +for a in sorted(anim): + poses = anim[a]["poses"] + F = poses["trans"].shape[0] + act = bpy.data.actions.new(f"{a:02d}_{ACTIONS_PEOPLE[a]}") + act.use_fake_user = True + arm.animation_data.action = act + cyc = a in (0, 1, 2, 3, 23, 24) + keys = list(range(F)) + ([0] if cyc and F > 1 else []) + for ki, i in enumerate(keys): + pp = pose_from_params({k: jnp.asarray(v_[i]) for k, v_ in poses.items()}) + apply_pose(arm, bone_joint, np.asarray(pp["rot"]), np.asarray(pp["trans"])) + fr = 1 + ki * STEP + for pb in arm.pose.bones: + pb.keyframe_insert("rotation_quaternion", frame=fr, group=pb.name) + if pb.parent is None: + pb.keyframe_insert("location", frame=fr, group=pb.name) + act["uo_action"] = a + act["uo_frames"] = F + act.frame_range = (1, 1 + (len(keys) - 1) * STEP) + if first_action is None or a == 4: + first_action = act +arm.animation_data.action = anim and bpy.data.actions.get("00_walk_unarmed") or first_action +apply_pose(arm, bone_joint, np.zeros((NJ, 3)), np.zeros(3)) + +# ------------------------------------------------------------------ UO camera (orthographic, matches sprite projection) +theta, scale = float(Snp["theta"]), float(Snp["scale"]) +cam = bpy.data.cameras.new("UO_Camera"); cam.type = "ORTHO" +cam.ortho_scale = CANVAS_W / scale +cam.sensor_fit = "HORIZONTAL" +co = bpy.data.objects.new("UO_Camera", cam) +sc.collection.objects.link(co) +up = Vector((0, math.sin(theta), math.cos(theta))) +view = Vector((0, math.cos(theta), -math.sin(theta))) # looking direction +center_px_up = (ANCHOR_Y - CANVAS_H / 2) / scale +center_px_x = (CANVAS_W / 2 - ANCHOR_X) / scale +target = up * center_px_up + Vector((center_px_x, 0, 0)) +co.location = target - view * 10 +co.rotation_euler = view.to_track_quat("-Z", "Y").to_euler() +sc.camera = co +sc.render.resolution_x, sc.render.resolution_y = CANVAS_W, CANVAS_H +sc.render.film_transparent = True +sc.render.filter_size = 0.5 +# direction control: custom property on the rig drives its Z rotation (UO file direction 0..4, 5..7 = mirrored) +arm["uo_direction"] = 0 +arm.id_properties_ui("uo_direction").update(min=0, max=4) +fc = arm.driver_add("rotation_euler", 2) +fc.driver.type = "SCRIPTED" +var = fc.driver.variables.new(); var.name = "d"; var.type = "SINGLE_PROP" +var.targets[0].id = arm; var.targets[0].data_path = '["uo_direction"]' +fc.driver.expression = "-d*pi/4" +sun = bpy.data.lights.new("UO_Sun", "SUN"); sun.energy = 3.0 +so = bpy.data.objects.new("UO_Sun", sun); so.rotation_euler = (math.radians(40), 0, math.radians(-30)) +sc.collection.objects.link(so) +w = bpy.data.worlds.new("World"); sc.world = w; w.use_nodes = True +w.node_tree.nodes["Background"].inputs[1].default_value = 0.8 +sc.render.engine = eevee_engine() + +# metadata +sc["uo_theta_deg"] = math.degrees(theta) +sc["uo_px_per_m"] = scale +sc.frame_start, sc.frame_end = 1, 1 + 9 * STEP + +txt = bpy.data.texts.new("render_uo_sprites.py") +txt.from_string(open("render_uo_sprites.py").read()) + +pickle.dump(dict(v=v, faces=faces, mirror=mirror, tris=tris, tri_uv=tri_uv), open(os.path.join(OUT, "mesh_cache.pkl"), "wb")) +for im in (img_col, img_grey): + im.pack() + im.filepath = "//" + im.name + ".png" +bpy.ops.wm.save_as_mainfile(filepath=os.path.abspath(os.path.join(OUT, "UO_Body_0x190.blend"))) +print("saved blend") diff --git a/third_party/UO_Model3D_v13/pipeline/build_originals.py b/third_party/UO_Model3D_v13/pipeline/build_originals.py new file mode 100644 index 0000000..fab97c1 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/build_originals.py @@ -0,0 +1,26 @@ +"""Pack the original UO body frames (canvas-aligned 136x120, anchor 68,86) as + 1) an atlas PNG for the shader projection, 2) a JSON (per tile base64(zlib(RGBA))) for the render script.""" +import json, zlib, base64, numpy as np +from PIL import Image +from targets import targets +COLS, TW, TH = 35, 136, 120 +tiles, k = {}, 0 +frames = {} +for a in range(35): + T = targets(a) + for d in range(5): + for i in range(len(T)): + tiles["%d,%d,%d" % (a, i, d)] = (k % COLS, k // COLS); frames[(a, i, d)] = T[i, d]; k += 1 +ROWS = (k + COLS - 1) // COLS +atlas = np.zeros((ROWS * TH, COLS * TW, 4), np.uint8) +enc = {} +for (a, i, d), img in frames.items(): + c, r = tiles["%d,%d,%d" % (a, i, d)] + rgba = img.copy(); rgba[..., 3] = np.where(img[..., 3] > 127, 255, 0); rgba[rgba[..., 3] == 0] = 0 + atlas[r * TH:(r + 1) * TH, c * TW:(c + 1) * TW] = rgba + enc["%d,%d,%d" % (a, i, d)] = base64.b64encode(zlib.compress(rgba.tobytes(), 9)).decode() +Image.fromarray(atlas).save("UO_Original_Atlas.png", optimize=True) +json.dump(dict(cols=COLS, rows=ROWS, tile=[TW, TH], anchor=[68, 86], tiles=tiles, frames=enc, + format="key 'action,frame,dir' -> base64(zlib(uint8 RGBA 120x136)); tiles: key -> [col,row] in the atlas"), + open("uo_original_frames.json", "w")) +print("tiles", k, "atlas", atlas.shape) diff --git a/third_party/UO_Model3D_v13/pipeline/check_clav.py b/third_party/UO_Model3D_v13/pipeline/check_clav.py new file mode 100644 index 0000000..03aa04f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/check_clav.py @@ -0,0 +1,17 @@ +import bpy, pickle, numpy as np, sys +import jax.numpy as jnp +bpy.ops.wm.open_mainfile(filepath="out_ct/UO_Body_0x190.blend") +import os; os.environ["UO_DELTA"] = "refine_infl.pkl" +from posefit_mesh import posed +P = pickle.load(open("test_clav_poses.pkl", "rb")) +sc = bpy.context.scene; rig = bpy.data.objects["UO_Rig"]; body = bpy.data.objects["UO_Body"] +rig["uo_direction"] = 0 +for a, name in ((17, "17_spell_area"), (4, "04_stand")): + rig.animation_data.action = bpy.data.actions[name] + for i in range(P[a]["poses"]["trans"].shape[0]): + sc.frame_set(1 + 3 * i) + dg = bpy.context.evaluated_depsgraph_get(); ev = body.evaluated_get(dg); me = ev.to_mesh() + co = np.zeros(len(me.vertices) * 3); me.vertices.foreach_get("co", co); ev.to_mesh_clear() + M = np.array(body.matrix_world); co = co.reshape(-1, 3) @ M[:3, :3].T + M[:3, 3] + X = np.asarray(posed({k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()})) + np.array([0, 0, sc["uo_anchor_height"]]) + print(name, i, "max |blender - fit| = %.2f mm" % (np.abs(co - X).max() * 1000)) diff --git a/third_party/UO_Model3D_v13/pipeline/clav_test.py b/third_party/UO_Model3D_v13/pipeline/clav_test.py new file mode 100644 index 0000000..00199bc --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/clav_test.py @@ -0,0 +1,73 @@ +"""Experiment: would a movable shoulder (clavicle) help raised-arm frames? Per-frame free shoulder offsets +(chest frame, both sides) vs. a control refit with the same iterations. Scored by true raster IoU.""" +import sys, pickle, numpy as np +import jax, jax.numpy as jnp, optax +from posefit_mesh import * +from posefit_mesh import _posed_j +P = pickle.load(open("final_poses_v6.pkl", "rb")) +FR = [(9, 6), (9, 5), (17, 4), (17, 3), (26, 2), (29, 2), (12, 3), (16, 4), (4, 0), (0, 3)] +ARMB = {s: np.array([JI[joint_of[b]] in (JI["shoulder." + s], JI["elbow." + s], JI["wrist." + s]) for b in md["bones"]]) for s in "LR"} +ML = jnp.asarray(ARMB["L"], jnp.float32); MR = jnp.asarray(ARMB["R"], jnp.float32) + + +def posed_ext(pp, off): + pose = pose_from_params(pp) + Pj, R = fk(S, pose) + Rb = R[BONE_JOINT] + Rc = R[JI["chest"]] + tb = Pj[BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, P0[BONE_JOINT]) + tb = tb + ML[:, None] * (Rc @ off[0])[None] + MR[:, None] * (Rc @ off[1])[None] + X = jnp.einsum("bij,vj->vbi", Rb, V0) + tb[None] + return jnp.einsum("vb,vbi->vi", W, X) + + +def terms(X, dto, bpx, bm): + ins = 0.0; cov = 0.0 + for d in range(5): + p = project(X, d) + ins += jnp.mean(jnp.where(LEGV, bilinear(dto[d, 0], p), bilinear(dto[d, 1], p)) ** 2) + dist = jnp.sqrt(jnp.min(jnp.sum((bpx[d][:, None, :] - p[None, :, :]) ** 2, -1), 1) + 1e-9) + cov += jnp.sum(bm[d] * jax.nn.relu(dist - 0.7) ** 2) / (jnp.sum(bm[d]) + 1.0) + return 4.0 * ins + cov + + +def loss(v, nb, dto, bpx, bm, woff): + pp, off = v["pp"], v["off"] + l = terms(posed_ext(pp, off), dto, bpx, bm) + 200.0 * limit_penalty(pp) + 0.02 * natural_prior(pp) + l += 0.02 * (jnp.sum((pp["ball"] - nb["ball"]) ** 2) + jnp.sum((pp["hinge"] - nb["hinge"]) ** 2)) + return l + woff * jnp.sum(off ** 2) + + +vg = jax.jit(jax.value_and_grad(loss)) + + +def run(pp0, dto, bpx, bm, free): + v = {"pp": {k: jnp.asarray(x) for k, x in pp0.items()}, "off": jnp.zeros((2, 3))} + nb = dict(v["pp"]) + opt = optax.adam(optax.exponential_decay(0.01, 300, 0.3)); st = opt.init(v) + for _ in range(300): + _, g = vg(v, nb, dto, bpx, bm, 30.0) + if not free: + g["off"] = jnp.zeros_like(g["off"]) + up, st = opt.update(g, st, v); v = optax.apply_updates(v, up) + return v + + +def iou(v, m): + X = posed_ext(v["pp"], v["off"]); r = [] + for d in range(5): + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H) + r.append((mk & m[d]).sum() / max((mk | m[d]).sum(), 1)) + return np.mean(r) + + +cache = {} +for a, i in FR: + if a not in cache: + cache[a] = prepare(a) + F, dto, bpx, bm, m = cache[a] + pp0 = {k: np.asarray(x[i]) for k, x in P[a]["poses"].items()} + base = iou({"pp": {k: jnp.asarray(x) for k, x in pp0.items()}, "off": jnp.zeros((2, 3))}, m[i]) + c = run(pp0, dto[i], bpx[i], bm[i], False); f = run(pp0, dto[i], bpx[i], bm[i], True) + print(f"a{a} f{i}: now {base:.3f} control {iou(c, m[i]):.3f} with shoulder offsets {iou(f, m[i]):.3f} " + f"off L {np.round(np.asarray(f['off'][0])*100,1)} cm R {np.round(np.asarray(f['off'][1])*100,1)} cm", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/compare.py b/third_party/UO_Model3D_v13/pipeline/compare.py new file mode 100644 index 0000000..595c255 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/compare.py @@ -0,0 +1,91 @@ +"""Render the rigged model through UO_Camera and build side-by-side GIFs: original sprite | 3D model.""" +import bpy, sys, os +import numpy as np +from PIL import Image + +blend = sys.argv[sys.argv.index("--blend") + 1] +out = sys.argv[sys.argv.index("--out") + 1] +acts = [int(a) for a in sys.argv[sys.argv.index("--actions") + 1].split(",")] +os.makedirs(out, exist_ok=True) +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) +from targets import targets +from vd import ACTIONS_PEOPLE + +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(blend)) +sc = bpy.context.scene +sc.render.engine = "CYCLES"; sc.cycles.samples = 16; sc.cycles.device = "CPU" +sc.render.resolution_x, sc.render.resolution_y = 136, 120 +sc.render.film_transparent = True +sc.cycles.filter_width = float(sys.argv[sys.argv.index("--filter") + 1]) if "--filter" in sys.argv else 1.0 +MATTE = "--no-matte" not in sys.argv + + +def uo_matte(rgba): + """UO sprites: anti-aliased render over black, then 1-bit alpha -> dark edge pixels.""" + a = rgba[..., 3:4] / 255.0 + out = rgba.copy() + out[..., :3] = rgba[..., :3] * a + out[..., 3] = np.where(a[..., 0] >= 0.5, 255, 0) + # UO art has a dark 1-px outline (outer ring ~0.38 of the next ring's brightness) + m = out[..., 3] > 0 + inner = m.copy() + inner[1:] &= m[:-1]; inner[:-1] &= m[1:]; inner[:, 1:] &= m[:, :-1]; inner[:, :-1] &= m[:, 1:] + ring = m & ~inner + out[ring, :3] *= OUTLINE + return out + + +OUTLINE = float(sys.argv[sys.argv.index("--outline") + 1]) if "--outline" in sys.argv else 0.38 +rig = bpy.data.objects["UO_Rig"] +tmp = os.path.abspath(os.path.join(out, "_tmp.png")) +ZOOM = 3 +BG = np.array([48, 52, 60], float) + + +def comp(rgba): + a = rgba[..., 3:4] / 255.0 + return BG * (1 - a) + rgba[..., :3] * a + + +for a in acts: + name = f"{a:02d}_{ACTIONS_PEOPLE[a]}" + act = bpy.data.actions.get(name) + if act is None: + continue + rig.animation_data.action = act + T = targets(a) + F = len(T) + # crop to union bbox of sprites (+ margin) + m = T[..., 3].max((0, 1)) > 0 + ys, xs = np.nonzero(m) + y0, y1, x0, x1 = max(ys.min() - 6, 0), min(ys.max() + 7, 120), max(xs.min() - 6, 0), min(xs.max() + 7, 136) + frames = [] + ious = [] + errs = [] + for i in range(F): + cols = [] + for d in range(5): + rig["uo_direction"] = d + rig.update_tag() + sc.frame_set(1 + i * 3) + sc.render.filepath = tmp + bpy.ops.render.render(write_still=True) + r = np.array(Image.open(tmp).convert("RGBA")).astype(float) + if MATTE: + r = uo_matte(r) + s = T[i, d].astype(float) + ma, mb = r[..., 3] > 127, s[..., 3] > 127 + ious.append((ma & mb).sum() / max((ma | mb).sum(), 1)) + both = ma & mb + if both.any(): + errs.append(np.abs(r[..., :3][both] - s[..., :3][both]).mean()) + pair = np.concatenate([comp(s)[y0:y1, x0:x1], comp(r)[y0:y1, x0:x1]], 0) + cols.append(pair) + cols.append(np.full((pair.shape[0], 2, 3), 90.0)) + img = np.concatenate(cols[:-1], 1).astype(np.uint8) + im = Image.fromarray(img) + frames.append(im.resize((im.width * ZOOM, im.height * ZOOM), Image.NEAREST)) + dur = 125 if F > 1 else 1000 + frames[0].save(os.path.join(out, f"compare_{name}.gif"), save_all=True, append_images=frames[1:], duration=dur, loop=0) + frames[0].save(os.path.join(out, f"compare_{name}_f0.png")) + print("gif", name, "silhouette IoU %.3f" % np.mean(ious), "mean colour error %.1f/255" % np.mean(errs), flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/compare2.py b/third_party/UO_Model3D_v13/pipeline/compare2.py new file mode 100644 index 0000000..e5681b3 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/compare2.py @@ -0,0 +1,56 @@ +"""Render the BODY layer with render_uo_layer.py (UO look, horse holdout, UO post-process) and build +side-by-side GIFs (original sprite | model) + metrics for the given actions.""" +import bpy, sys, os +import numpy as np +from PIL import Image + +blend = sys.argv[sys.argv.index("--blend") + 1] +out = os.path.abspath(sys.argv[sys.argv.index("--out") + 1]) +ACT_IDS = [int(a) for a in sys.argv[sys.argv.index("--actions") + 1].split(",")] +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) +from targets import targets +from vd import ACTIONS_PEOPLE + +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(blend)) +sc = bpy.context.scene +sc.render.engine = "CYCLES"; sc.cycles.samples = 16; sc.cycles.device = "CPU" +NAMES = [f"{a:02d}_{ACTIONS_PEOPLE[a]}" for a in ACT_IDS] +src = bpy.data.texts["render_uo_layer.py"].as_string() +import re +src = re.sub(r'(?m)^LAYER = "clothing"', 'LAYER = "body"', src, count=1) # the settings line, not the header +src = re.sub(r'(?m)^ONLY = \[\]', "ONLY = %r" % NAMES, src, count=1) +src = re.sub(r'(?m)^EXACT_BODY = True', "EXACT_BODY = False", src, count=1) # the 3D model itself, not the original +src = src.replace('WRITE_VD = True', 'WRITE_VD = False').replace('OUT_DIR = "//uo_render/"', 'OUT_DIR = %r' % (out + "/")) +exec(compile(src, "render_uo_layer.py", "exec")) +BG = np.array([48, 52, 60], float) + + +def comp(rgba): + a = rgba[..., 3:4] / 255.0 + return BG * (1 - a) + rgba[..., :3] * a + + +os.makedirs(out, exist_ok=True) +for a, name in zip(ACT_IDS, NAMES): + T = targets(a) + m = T[..., 3].max((0, 1)) > 0 + ys, xs = np.nonzero(m) + y0, y1, x0, x1 = max(ys.min() - 6, 0), min(ys.max() + 7, 120), max(xs.min() - 6, 0), min(xs.max() + 7, 136) + frames, ious, errs = [], [], [] + for i in range(len(T)): + cols = [] + for d in range(5): + r = np.array(Image.open(os.path.join(out, "body", "frames", name, "dir%d" % d, "%02d.png" % i)).convert("RGBA")).astype(float) + s = T[i, d].astype(float) + ma, mb = r[..., 3] > 127, s[..., 3] > 127 + ious.append((ma & mb).sum() / max((ma | mb).sum(), 1)) + both = ma & mb + if both.any(): + errs.append(np.abs(r[..., :3][both] - s[..., :3][both]).mean()) + cols.append(np.concatenate([comp(s)[y0:y1, x0:x1], comp(r)[y0:y1, x0:x1]], 0)) + cols.append(np.full((cols[-1].shape[0], 2, 3), 90.0)) + im = Image.fromarray(np.concatenate(cols[:-1], 1).astype(np.uint8)) + frames.append(im.resize((im.width * 3, im.height * 3), Image.NEAREST)) + frames[0].save(os.path.join(out, f"compare_{name}.gif"), save_all=True, append_images=frames[1:], + duration=125 if len(frames) > 1 else 1000, loop=0) + print("gif", name, "silhouette IoU %.3f" % np.mean(ious), "mean colour error %.1f/255" % np.mean(errs), flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/corr_fit.py b/third_party/UO_Model3D_v13/pipeline/corr_fit.py new file mode 100644 index 0000000..f19b7af --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/corr_fit.py @@ -0,0 +1,163 @@ +"""Per-frame corrective shapes: rest-space vertex offsets D (a Blender shape key per UO frame) so that the +rasterised silhouette (pixel centre rule) in all 5 UO views equals the sprite: nothing outside, nothing missing. + +Loss per view (px units): + inside : every projected vertex lies inside the pixel-square union of the sprite (signed distance, margin) + reach : every outward pixel side of the sprite (its midpoint) has a projected vertex within ~0.3 px + repel : after a raster check, vertices are pushed away from pixel centres the model covers but the sprite lacks + reg : Laplacian smoothness and magnitude of D +Poses are fixed (final pose file). usage: python corr_fit.py 4 0 9 --poses final_poses_v10.pkl --out corr_A.pkl""" +import sys, os, time, pickle +import numpy as np +import jax, jax.numpy as jnp, optax +from scipy.ndimage import distance_transform_edt +os.environ.setdefault("UO_DELTA", "refine_infl.pkl") +from posefit_mesh import (md, pose_from_params, fk, S, W, P0, BONE_JOINT, project, tris, targets, horse_masks, HORSE_OF, + LEGV, CANVAS_W, CANVAS_H, raster_vec, V0, JI) +POSES = sys.argv[sys.argv.index("--poses") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +ACTS = [int(a) for k, a in enumerate(sys.argv[1:], 1) if a.isdigit() and sys.argv[k - 1] not in ("--poses", "--out")] +ITERS = int(os.environ.get("UO_CITERS", "400")) +ROUNDS = int(os.environ.get("UO_CROUNDS", "3")) +SUP = 4 +VIEWS = [int(v) for v in os.environ.get("UO_CVIEWS", "0,1,2,3,4").split(",")] +NT = 700 # max boundary targets per view +NR = 64 # max repel points per view +NC = 1400 # max candidate (near-boundary) vertices per view for the reach term +P = pickle.load(open(POSES, "rb")) +NV = V0.shape[0] +ARM_L = jnp.asarray([JI[j] for j in ()]) if False else None +E = set() +for f in md["faces"]: + for a_, b_ in zip(f, f[1:] + f[:1]): + E.add((min(a_, b_), max(a_, b_))) +E = np.array(sorted(E)) +deg = jnp.asarray(np.maximum(np.bincount(E.ravel(), minlength=NV), 1).astype(np.float32)) +EI, EJ = jnp.asarray(E[:, 0]), jnp.asarray(E[:, 1]) +import posefit_mesh as PM + + +def posed_with(pp, V): + pose = pose_from_params(pp) + Pj, R = fk(S, pose) + Rb = R[BONE_JOINT] + tb = Pj[BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, P0[BONE_JOINT]) + if "clav" in pp: + Rc = R[JI["chest"]] + tb = tb + PM.ARM_L[:, None] * (Rc @ pp["clav"][0])[None] + PM.ARM_R[:, None] * (Rc @ pp["clav"][1])[None] + X = jnp.einsum("bij,vj->vbi", Rb, V) + tb[None] + return jnp.einsum("vb,vbi->vi", W, X) + + +def sdf_sq(mask): + """signed distance (px, + outside) to the boundary of the union of pixel squares, sampled on a SUPx grid""" + m4 = np.kron(mask, np.ones((SUP, SUP), bool)) + return ((distance_transform_edt(~m4) - distance_transform_edt(m4)) / SUP).astype(np.float32) + + +def bilin(img, p): + x = jnp.clip(p[:, 0] * SUP - 0.5, 0, img.shape[1] - 1.001); y = jnp.clip(p[:, 1] * SUP - 0.5, 0, img.shape[0] - 1.001) + x0 = jnp.floor(x).astype(int); y0 = jnp.floor(y).astype(int); fx, fy = x - x0, y - y0 + return (img[y0, x0] * (1 - fx) * (1 - fy) + img[y0, x0 + 1] * fx * (1 - fy) + img[y0 + 1, x0] * (1 - fx) * fy + + img[y0 + 1, x0 + 1] * fx * fy) + + +def targets_of(mask, unknown): + pts = [] + H_, W_ = mask.shape + for dy, dx in ((-1, 0), (1, 0), (0, -1), (0, 1)): + nb = np.zeros_like(mask); nbu = np.zeros_like(mask) + ys, xs = np.nonzero(mask) + ny, nx = ys + dy, xs + dx + ok = (ny >= 0) & (ny < H_) & (nx >= 0) & (nx < W_) + outside = np.ones(len(ys), bool); outside[ok] = ~mask[ny[ok], nx[ok]] + hid = np.zeros(len(ys), bool); hid[ok] = unknown[ny[ok], nx[ok]] + sel = outside & ~hid + pts.append(np.stack([xs[sel] + 0.5 + 0.5 * dx, ys[sel] + 0.5 + 0.5 * dy], 1)) + return np.concatenate(pts, 0).astype(np.float32) + + +def loss_fn(Dpx, pp, sdf_r, sdf_a, tg, tm, rp, rm, w_rep, mounted, cand, cmask): + D = Dpx / 36.0 + X = posed_with(pp, V0 + D) + lin = 0.0; lcov = 0.0; lrep = 0.0 + for d in VIEWS: + p = project(X, d) + s = jnp.where(LEGV & mounted, bilin(sdf_a[d], p), bilin(sdf_r[d], p)) + lin += jnp.mean(jax.nn.relu(s + 0.08) ** 2) * 50.0 + jnp.max(jax.nn.relu(s + 0.08)) * 0.5 + pc = p[cand[d]] + (1.0 - cmask[d])[:, None] * 1e4 # padded candidates pushed far away + dist = jnp.sqrt(jnp.min(jnp.sum((tg[d][:, None, :] - pc[None, :, :]) ** 2, -1), 1) + 1e-9) + lcov += jnp.sum(tm[d] * jax.nn.relu(dist - 0.3) ** 2) / (jnp.sum(tm[d]) + 1.0) * 20.0 + dr = jnp.sqrt(jnp.sum((rp[d][:, None, :] - pc[None, :, :]) ** 2, -1) + 1e-9) + lrep += jnp.sum(rm[d][:, None] * jax.nn.relu(0.8 - dr) ** 2) * w_rep + lap = Dpx - (jax.ops.segment_sum(Dpx[EJ], EI, NV) + jax.ops.segment_sum(Dpx[EI], EJ, NV)) / deg[:, None] + reg = jnp.sum(lap ** 2) * float(os.environ.get("UO_CLAP", "0.05")) + jnp.sum(Dpx ** 2) * 0.0005 + return lin + lcov + lrep + reg, (lin, lcov, lrep) + + +vg = jax.jit(jax.value_and_grad(loss_fn, has_aux=True)) + + +def raster_check(Dpx, pp, masks, unknown): + X = posed_with(pp, V0 + jnp.asarray(Dpx) / 36.0) + red = blue = area = 0; blue_pts = [] + for d in range(5): + if d not in VIEWS: + blue_pts.append(np.zeros((0, 2), np.float32)); continue + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H) & ~unknown[d] + s = masks[d] + b = mk & ~s; r = s & ~mk + red += r.sum(); blue += b.sum(); area += s.sum() + ys, xs = np.nonzero(b); blue_pts.append(np.stack([xs + 0.5, ys + 0.5], 1).astype(np.float32)) + return red, blue, area, blue_pts + + +res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} +for a in ACTS: + T = targets(a); F = len(T); M = T[..., 3] > 127 + hid = (horse_masks(a, F) & ~M) if a in HORSE_OF else np.zeros_like(M) + mounted = jnp.asarray(a in HORSE_OF) + for i in range(F): + t0 = time.time() + pp = {k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()} + sdf_r = jnp.asarray(np.stack([sdf_sq(M[i, d]) for d in range(5)])) + sdf_a = jnp.asarray(np.stack([sdf_sq(M[i, d] | hid[i, d]) for d in range(5)])) + tg = np.zeros((5, NT, 2), np.float32); tm = np.zeros((5, NT), np.float32) + for d in range(5): + t = targets_of(M[i, d], hid[i, d]) + if len(t) > NT: + t = t[np.linspace(0, len(t) - 1, NT).astype(int)] + tg[d, :len(t)] = t; tm[d, :len(t)] = 1 + rp = np.zeros((5, NR, 2), np.float32); rm = np.zeros((5, NR), np.float32) + r0, b0, area, _ = raster_check(np.zeros((NV, 3)), pp, M[i], hid[i]) + Dpx = jnp.zeros((NV, 3), jnp.float32) + for rnd in range(ROUNDS): + Xc = np.asarray(posed_with(pp, V0 + Dpx / 36.0)) + cand = np.zeros((5, NC), np.int32); cmask = np.zeros((5, NC), np.float32) + for d in range(5): + pc = np.asarray(project(jnp.asarray(Xc), d)) + sd = np.asarray(bilin(sdf_r[d], jnp.asarray(pc))) + idx = np.nonzero(np.abs(sd) < 4.0)[0] + if len(idx) > NC: + idx = idx[np.argsort(np.abs(sd[idx]))[:NC]] + cand[d, :len(idx)] = idx; cmask[d, :len(idx)] = 1 + opt = optax.adam(optax.exponential_decay(0.05, ITERS, 0.2)); st = opt.init(Dpx) + args = (pp, sdf_r, sdf_a, jnp.asarray(tg), jnp.asarray(tm), jnp.asarray(rp), jnp.asarray(rm), 5.0, mounted, + jnp.asarray(cand), jnp.asarray(cmask)) + for it in range(ITERS): + (l, aux), g = vg(Dpx, *args) + up, st = opt.update(g, st, Dpx); Dpx = optax.apply_updates(Dpx, up) + r1, b1, _, bpts = raster_check(np.asarray(Dpx), pp, M[i], hid[i]) + if r1 + b1 == 0 or rnd == ROUNDS - 1: + break + for d in range(5): # remember offending pixel centres, keep previous ones too + old = rp[d][rm[d] > 0] + allp = np.concatenate([old, bpts[d]], 0)[:NR] + rp[d] = 0; rm[d] = 0; rp[d, :len(allp)] = allp; rm[d, :len(allp)] = 1 + res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} + res[(a, i)] = dict(D=(np.asarray(Dpx) / 36.0).astype(np.float32), before=(int(r0), int(b0)), after=(int(r1), int(b1)), + area=int(area)) + pickle.dump(res, open(OUT, "wb")) + print(f"a{a:2d} f{i}: missing {r0:4d} -> {r1:3d} outside {b0:4d} -> {b1:3d} (area {area}, " + f"IoU {1-(r0+b0)/(area+b0):.3f} -> {1-(r1+b1)/(area+b1):.3f}) max|D| {np.abs(np.asarray(Dpx)).max():.2f}px " + f"rounds {rnd+1} {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/corr_fit3.py b/third_party/UO_Model3D_v13/pipeline/corr_fit3.py new file mode 100644 index 0000000..3d01c11 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/corr_fit3.py @@ -0,0 +1,130 @@ +"""Stage 3: pixel-level refinement of the per-frame corrections, aligned with the rasteriser (pixel-centre rule). +Every pixel the model covers but the sprite lacks pushes EACH covering triangle off that pixel centre (barycentric +exclusion); every sprite pixel the model misses pulls its nearest triangle over the pixel centre (inclusion). +Stage-1 terms keep the rest in place. Starts from a previous corrections file (UO_CINIT). +usage: UO_CINIT=corr_all.pkl python corr_fit3.py 4 0 --poses final_poses_v10.pkl --out corr3_A.pkl""" +import sys, os, time, pickle +import numpy as np +import jax, jax.numpy as jnp, optax +os.environ.setdefault("UO_DELTA", "refine_infl.pkl") +sys.argv_saved = list(sys.argv) +from posefit_mesh import (md, pose_from_params, fk, S, W, P0, BONE_JOINT, project, tris, targets, horse_masks, HORSE_OF, + LEGV, CANVAS_W, CANVAS_H, V0, JI) +import posefit_mesh as PM +import corr_fit_core as CF + +POSES = sys.argv[sys.argv.index("--poses") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +ACTS = [int(a) for k, a in enumerate(sys.argv[1:], 1) if a.isdigit() and sys.argv[k - 1] not in ("--poses", "--out")] +FRAMES = [int(x) for x in os.environ["UO_CFRAMES"].split(",")] if os.environ.get("UO_CFRAMES") else None +INIT = pickle.load(open(os.environ["UO_CINIT"], "rb")) +ROUNDS = int(os.environ.get("UO_C3ROUNDS", "8")); ITERS = int(os.environ.get("UO_C3ITERS", "150")) +NP = 512 # max (pixel, triangle) pairs per view +P = pickle.load(open(POSES, "rb")) +TRI = jnp.asarray(tris) + + +def bary_min(p, t, c): + """min barycentric coordinate of point c in projected triangle t (p: projected vertices)""" + A, B, C = p[TRI[t, 0]], p[TRI[t, 1]], p[TRI[t, 2]] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + den = jnp.where(jnp.abs(den) < 1e-6, 1e-6, den) + l0 = ((B[:, 1] - C[:, 1]) * (c[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (c[:, 1] - C[:, 1])) / den + l1 = ((C[:, 1] - A[:, 1]) * (c[:, 0] - C[:, 0]) + (A[:, 0] - C[:, 0]) * (c[:, 1] - C[:, 1])) / den + return jnp.minimum(jnp.minimum(l0, l1), 1 - l0 - l1) + + +def loss_fn(Dpx, pp, sdf_r, sdf_a, tg, tm, mounted, cand, cmask, ex_t, ex_c, ex_m, in_t, in_c, in_m): + base, _ = CF.loss_fn(Dpx, pp, sdf_r, sdf_a, tg, tm, jnp.zeros((5, 1, 2)), jnp.zeros((5, 1)), 0.0, mounted, cand, cmask) + X = CF.posed_with(pp, V0 + Dpx / 36.0) + lex = 0.0; lin = 0.0 + for d in range(5): + p = project(X, d) + lex += jnp.sum(ex_m[d] * jax.nn.relu(bary_min(p, ex_t[d], ex_c[d]) + 0.03) ** 2) * float(os.environ.get("UO_WEX", "400")) + lin += jnp.sum(in_m[d] * jax.nn.relu(0.03 - bary_min(p, in_t[d], in_c[d])) ** 2) * float(os.environ.get("UO_WIN", "400")) + return base + lex + lin, (lex, lin) + + +vg = jax.jit(jax.value_and_grad(loss_fn, has_aux=True)) + + +def raster_ids(P2): + """per pixel centre: list of covering triangle ids (all layers)""" + cover = {} + mn = np.floor(P2.min(1)).astype(int); mx = np.ceil(P2.max(1)).astype(int) + A, B, C = P2[:, 0], P2[:, 1], P2[:, 2] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + ok = np.abs(den) > 1e-12; size = np.clip(mx - mn, 0, 16) + ids = [] + for dy in range(int(size[:, 1].max()) + 1): + for dx in range(int(size[:, 0].max()) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px = mn[t, 0] + dx; py = mn[t, 1] + dy; cx, cy = px + 0.5, py + 0.5 + l0 = ((B[t, 1] - C[t, 1]) * (cx - C[t, 0]) + (C[t, 0] - B[t, 0]) * (cy - C[t, 1])) / den[t] + l1 = ((C[t, 1] - A[t, 1]) * (cx - C[t, 0]) + (A[t, 0] - C[t, 0]) * (cy - C[t, 1])) / den[t] + k = (l0 >= -1e-4) & (l1 >= -1e-4) & (1 - l0 - l1 >= -1e-4) & (px >= 0) & (py >= 0) & (px < CANVAS_W) & (py < CANVAS_H) + ids.append(np.stack([py[k], px[k], t[k]], 1)) + return np.concatenate(ids, 0) + + +def pairs_for(P2, s, unknown): + """exclusion pairs (blue pixel, covering triangle) and inclusion pairs (red pixel, nearest triangle)""" + ids = raster_ids(P2) + cov = np.zeros(s.shape, bool); cov[ids[:, 0], ids[:, 1]] = True; cov &= ~unknown + blue = cov & ~s; red = s & ~cov + sel = blue[ids[:, 0], ids[:, 1]] + ex = ids[sel] + ex_c = np.stack([ex[:, 1] + 0.5, ex[:, 0] + 0.5], 1); ex_t = ex[:, 2] + ry, rx = np.nonzero(red) + cen = P2.mean(1) + in_t = np.array([np.argmin(((cen - [x + 0.5, y + 0.5]) ** 2).sum(1)) for y, x in zip(ry, rx)], int) + in_c = np.stack([rx + 0.5, ry + 0.5], 1) if len(rx) else np.zeros((0, 2)) + return (ex_t, ex_c), (in_t, in_c), int(blue.sum()), int(red.sum()) + + +def pad(t, c): + tt = np.zeros(NP, np.int32); cc = np.zeros((NP, 2), np.float32); mm = np.zeros(NP, np.float32) + n = min(len(t), NP); tt[:n] = t[:n]; cc[:n] = c[:n]; mm[:n] = 1 + return tt, cc, mm + + +res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} +for a in ACTS: + T = targets(a); F = len(T); M = T[..., 3] > 127 + hid = (horse_masks(a, F) & ~M) if a in HORSE_OF else np.zeros_like(M) + mounted = jnp.asarray(a in HORSE_OF) + for i in range(F): + if FRAMES is not None and i not in FRAMES: + continue + t0 = time.time() + pp = {k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()} + sdf_r, sdf_a, tg, tm = CF.frame_data(M[i], hid[i]) + Dpx = jnp.asarray(INIT[(a, i)]["D"] * 36.0) + hist = [] + best = None + for rnd in range(ROUNDS + 1): + X = np.asarray(CF.posed_with(pp, V0 + Dpx / 36.0)) + data = [pairs_for(np.asarray(project(jnp.asarray(X), d))[tris], M[i, d], hid[i, d]) for d in range(5)] + nb, nr = sum(x[2] for x in data), sum(x[3] for x in data) + hist.append((nr, nb)) + if best is None or nb + nr < best[0]: + best = (nb + nr, np.asarray(Dpx), nr, nb) + if rnd == ROUNDS or nb + nr == 0: + break + ex = [pad(*x[0]) for x in data]; inc = [pad(*x[1]) for x in data] + cand, cmask = CF.candidates(pp, Dpx, sdf_r) + args = (pp, sdf_r, sdf_a, tg, tm, mounted, cand, cmask, + jnp.asarray(np.stack([e[0] for e in ex])), jnp.asarray(np.stack([e[1] for e in ex])), jnp.asarray(np.stack([e[2] for e in ex])), + jnp.asarray(np.stack([e[0] for e in inc])), jnp.asarray(np.stack([e[1] for e in inc])), jnp.asarray(np.stack([e[2] for e in inc]))) + opt = optax.adam(optax.exponential_decay(float(os.environ.get("UO_C3LR", "0.02")), ITERS, 0.3)); st = opt.init(Dpx) + for it in range(ITERS): + (l, aux), g = vg(Dpx, *args) + up, st = opt.update(g, st, Dpx); Dpx = optax.apply_updates(Dpx, up) + _, Dbest, nr, nb = best + area = int(M[i].sum()) + res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} + res[(a, i)] = dict(D=(Dbest / 36.0).astype(np.float32), after=(nr, nb), area=area, hist=hist) + pickle.dump(res, open(OUT, "wb")) + r0, b0 = hist[0] + print(f"a{a:2d} f{i}: missing {r0:3d} -> {nr:3d} outside {b0:3d} -> {nb:3d} IoU {1-(r0+b0)/(area+b0):.3f} -> " + f"{1-(nr+nb)/(area+nb):.3f} {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/corr_fit34.py b/third_party/UO_Model3D_v13/pipeline/corr_fit34.py new file mode 100644 index 0000000..f58102b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/corr_fit34.py @@ -0,0 +1,96 @@ +"""Stages 3+4 of the per-frame corrections, raster-aligned (pixel-centre rule): + stage 3: refine the shared 3D correction D of each frame (all 5 views) with pixel-level triangle terms + stage 4: for each view d an extra correction E_d (a shape key active only in that UO direction) using only view d +usage: UO_CINIT=corr_all.pkl python corr_fit34.py 4 0 --poses final_poses_v10.pkl --out corr34_A.pkl""" +import sys, os, time, pickle +import numpy as np +import jax, jax.numpy as jnp, optax +os.environ.setdefault("UO_DELTA", "refine_infl.pkl") +from posefit_mesh import project, tris, targets, horse_masks, HORSE_OF, LEGV, V0 +import corr_fit_core as CF +from corr_fit_core import raster_ids, pairs_for, pad, bary_min, NP + +POSES = sys.argv[sys.argv.index("--poses") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +ACTS = [int(a) for k, a in enumerate(sys.argv[1:], 1) if a.isdigit() and sys.argv[k - 1] not in ("--poses", "--out")] +FRAMES = [int(x) for x in os.environ["UO_CFRAMES"].split(",")] if os.environ.get("UO_CFRAMES") else None +INIT = pickle.load(open(os.environ["UO_CINIT"], "rb")) +R3, I3 = int(os.environ.get("UO_R3", "8")), int(os.environ.get("UO_I3", "100")) +R4, I4 = int(os.environ.get("UO_R4", "8")), int(os.environ.get("UO_I4", "80")) +P = pickle.load(open(POSES, "rb")) +NV = V0.shape[0] + + +def loss_fn(E, Dfix, pp, sdf_r, sdf_a, tg, tm, mounted, cand, cmask, ex_t, ex_c, ex_m, in_t, in_c, in_m, wv, wreg): + Dpx = Dfix + E + X = CF.posed_with(pp, V0 + Dpx / 36.0) + l = 0.0 + for d in range(5): + p = project(X, d) + s = jnp.where(LEGV & mounted, CF.bilin(sdf_a[d], p), CF.bilin(sdf_r[d], p)) + lin = jnp.mean(jax.nn.relu(s + 0.08) ** 2) * 50.0 + pc = p[cand[d]] + (1.0 - cmask[d])[:, None] * 1e4 + dist = jnp.sqrt(jnp.min(jnp.sum((tg[d][:, None, :] - pc[None, :, :]) ** 2, -1), 1) + 1e-9) + lcov = jnp.sum(tm[d] * jax.nn.relu(dist - 0.3) ** 2) / (jnp.sum(tm[d]) + 1.0) * 20.0 + lex = jnp.sum(ex_m[d] * jax.nn.relu(bary_min(p, ex_t[d], ex_c[d]) + 0.03) ** 2) * 1500.0 + linc = jnp.sum(in_m[d] * jax.nn.relu(0.03 - bary_min(p, in_t[d], in_c[d])) ** 2) * 200.0 + l += wv[d] * (lin + lcov + lex + linc) + lap = E - (jax.ops.segment_sum(E[CF.EJ], CF.EI, NV) + jax.ops.segment_sum(E[CF.EI], CF.EJ, NV)) / CF.deg[:, None] + return l + wreg * (jnp.sum(lap ** 2) * 0.015 + jnp.sum(E ** 2) * 0.0005) + + +vg = jax.jit(jax.value_and_grad(loss_fn)) + + +def optimise(E0, Dfix, pp, fd, mounted, M_, hid_, views, rounds, iters, lr=0.01): + """alternate raster checks and optimisation; keep the best result (fewest wrong pixels in `views`)""" + sdf_r, sdf_a, tg, tm = fd + wv = jnp.asarray([1.0 if d in views else 0.0 for d in range(5)]) + E = jnp.asarray(E0); best = None; hist = [] + for rnd in range(rounds + 1): + X = np.asarray(CF.posed_with(pp, V0 + (Dfix + E) / 36.0)) + data = [pairs_for(np.asarray(project(jnp.asarray(X), d))[tris], M_[d], hid_[d]) for d in range(5)] + nb = sum(data[d][2] for d in views); nr = sum(data[d][3] for d in views); hist.append((nr, nb)) + if best is None or nb + nr < best[0]: + best = (nb + nr, np.asarray(E), nr, nb) + if rnd == rounds or nb + nr == 0: + break + ex = [pad(*x[0]) for x in data]; inc = [pad(*x[1]) for x in data] + cand, cmask = CF.candidates(pp, Dfix + E, sdf_r) + args = (jnp.asarray(Dfix), pp, sdf_r, sdf_a, tg, tm, mounted, cand, cmask, + jnp.asarray(np.stack([e[0] for e in ex])), jnp.asarray(np.stack([e[1] for e in ex])), jnp.asarray(np.stack([e[2] for e in ex])), + jnp.asarray(np.stack([e[0] for e in inc])), jnp.asarray(np.stack([e[1] for e in inc])), jnp.asarray(np.stack([e[2] for e in inc])), + wv, 1.0) + opt = optax.adam(optax.exponential_decay(lr, iters, 0.3)); st = opt.init(E) + for it in range(iters): + l, g = vg(E, *args) + up, st = opt.update(g, st, E); E = optax.apply_updates(E, up) + return best, hist + + +res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} +for a in ACTS: + T = targets(a); F = len(T); M = T[..., 3] > 127 + hid = (horse_masks(a, F) & ~M) if a in HORSE_OF else np.zeros_like(M) + mounted = jnp.asarray(a in HORSE_OF) + for i in range(F): + if FRAMES is not None and i not in FRAMES: + continue + t0 = time.time() + pp = {k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()} + fd = CF.frame_data(M[i], hid[i]) + D1 = INIT[(a, i)]["D"] * 36.0 + zero = np.zeros_like(D1) + (_, E3, nr3, nb3), h3 = optimise(zero, D1, pp, fd, mounted, M[i], hid[i], range(5), R3, I3) # stage 3 (shared) + D3 = D1 + E3 + Ed, per = {}, [] + for d in range(5): # stage 4 (per view) + (_, E4, nr4, nb4), h4 = optimise(zero, D3, pp, fd, mounted, M[i], hid[i], [d], R4, I4) + Ed[d] = (E4 / 36.0).astype(np.float32); per.append((nr4, nb4)) + area = int(M[i].sum()); r0, b0 = h3[0] + nr = sum(p[0] for p in per); nb = sum(p[1] for p in per) + res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} + res[(a, i)] = dict(D=(D3 / 36.0).astype(np.float32), Ed=Ed, stage3=(nr3, nb3), per_view=per, area=area) + pickle.dump(res, open(OUT, "wb")) + print(f"a{a:2d} f{i}: stage1 {1-(r0+b0)/(area+b0):.3f} stage3 {1-(nr3+nb3)/(area+nb3):.3f} per-view {1-(nr+nb)/(area+nb):.3f} " + f"(missing {nr}, outside {nb}) {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/corr_fit_core.py b/third_party/UO_Model3D_v13/pipeline/corr_fit_core.py new file mode 100644 index 0000000..3dee2f8 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/corr_fit_core.py @@ -0,0 +1,193 @@ +"""(library version of corr_fit.py) Per-frame corrective shapes: rest-space vertex offsets D (a Blender shape key per UO frame) so that the +rasterised silhouette (pixel centre rule) in all 5 UO views equals the sprite: nothing outside, nothing missing. + +Loss per view (px units): + inside : every projected vertex lies inside the pixel-square union of the sprite (signed distance, margin) + reach : every outward pixel side of the sprite (its midpoint) has a projected vertex within ~0.3 px + repel : after a raster check, vertices are pushed away from pixel centres the model covers but the sprite lacks + reg : Laplacian smoothness and magnitude of D +Poses are fixed (final pose file). usage: python corr_fit.py 4 0 9 --poses final_poses_v10.pkl --out corr_A.pkl""" +import sys, os, time, pickle +import numpy as np +import jax, jax.numpy as jnp, optax +from scipy.ndimage import distance_transform_edt +os.environ.setdefault("UO_DELTA", "refine_infl.pkl") +from posefit_mesh import (md, pose_from_params, fk, S, W, P0, BONE_JOINT, project, tris, targets, horse_masks, HORSE_OF, + LEGV, CANVAS_W, CANVAS_H, raster_vec, V0, JI) +ITERS = int(os.environ.get("UO_CITERS", "400")) +ROUNDS = int(os.environ.get("UO_CROUNDS", "3")) +SUP = 4 +VIEWS = [int(v) for v in os.environ.get("UO_CVIEWS", "0,1,2,3,4").split(",")] +NT = 700 # max boundary targets per view +NR = 64 # max repel points per view +NC = 1400 # max candidate (near-boundary) vertices per view for the reach term +NV = V0.shape[0] +ARM_L = jnp.asarray([JI[j] for j in ()]) if False else None +E = set() +for f in md["faces"]: + for a_, b_ in zip(f, f[1:] + f[:1]): + E.add((min(a_, b_), max(a_, b_))) +E = np.array(sorted(E)) +deg = jnp.asarray(np.maximum(np.bincount(E.ravel(), minlength=NV), 1).astype(np.float32)) +EI, EJ = jnp.asarray(E[:, 0]), jnp.asarray(E[:, 1]) +import posefit_mesh as PM + + +def posed_with(pp, V): + pose = pose_from_params(pp) + Pj, R = fk(S, pose) + Rb = R[BONE_JOINT] + tb = Pj[BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, P0[BONE_JOINT]) + if "clav" in pp: + Rc = R[JI["chest"]] + tb = tb + PM.ARM_L[:, None] * (Rc @ pp["clav"][0])[None] + PM.ARM_R[:, None] * (Rc @ pp["clav"][1])[None] + X = jnp.einsum("bij,vj->vbi", Rb, V) + tb[None] + return jnp.einsum("vb,vbi->vi", W, X) + + +def sdf_sq(mask): + """signed distance (px, + outside) to the boundary of the union of pixel squares, sampled on a SUPx grid""" + m4 = np.kron(mask, np.ones((SUP, SUP), bool)) + return ((distance_transform_edt(~m4) - distance_transform_edt(m4)) / SUP).astype(np.float32) + + +def bilin(img, p): + x = jnp.clip(p[:, 0] * SUP - 0.5, 0, img.shape[1] - 1.001); y = jnp.clip(p[:, 1] * SUP - 0.5, 0, img.shape[0] - 1.001) + x0 = jnp.floor(x).astype(int); y0 = jnp.floor(y).astype(int); fx, fy = x - x0, y - y0 + return (img[y0, x0] * (1 - fx) * (1 - fy) + img[y0, x0 + 1] * fx * (1 - fy) + img[y0 + 1, x0] * (1 - fx) * fy + + img[y0 + 1, x0 + 1] * fx * fy) + + +def targets_of(mask, unknown): + pts = [] + H_, W_ = mask.shape + for dy, dx in ((-1, 0), (1, 0), (0, -1), (0, 1)): + nb = np.zeros_like(mask); nbu = np.zeros_like(mask) + ys, xs = np.nonzero(mask) + ny, nx = ys + dy, xs + dx + ok = (ny >= 0) & (ny < H_) & (nx >= 0) & (nx < W_) + outside = np.ones(len(ys), bool); outside[ok] = ~mask[ny[ok], nx[ok]] + hid = np.zeros(len(ys), bool); hid[ok] = unknown[ny[ok], nx[ok]] + sel = outside & ~hid + pts.append(np.stack([xs[sel] + 0.5 + 0.5 * dx, ys[sel] + 0.5 + 0.5 * dy], 1)) + return np.concatenate(pts, 0).astype(np.float32) + + +def loss_fn(Dpx, pp, sdf_r, sdf_a, tg, tm, rp, rm, w_rep, mounted, cand, cmask): + D = Dpx / 36.0 + X = posed_with(pp, V0 + D) + lin = 0.0; lcov = 0.0; lrep = 0.0 + for d in VIEWS: + p = project(X, d) + s = jnp.where(LEGV & mounted, bilin(sdf_a[d], p), bilin(sdf_r[d], p)) + lin += jnp.mean(jax.nn.relu(s + 0.08) ** 2) * 50.0 + jnp.max(jax.nn.relu(s + 0.08)) * 0.5 + pc = p[cand[d]] + (1.0 - cmask[d])[:, None] * 1e4 # padded candidates pushed far away + dist = jnp.sqrt(jnp.min(jnp.sum((tg[d][:, None, :] - pc[None, :, :]) ** 2, -1), 1) + 1e-9) + lcov += jnp.sum(tm[d] * jax.nn.relu(dist - 0.3) ** 2) / (jnp.sum(tm[d]) + 1.0) * 20.0 + dr = jnp.sqrt(jnp.sum((rp[d][:, None, :] - pc[None, :, :]) ** 2, -1) + 1e-9) + lrep += jnp.sum(rm[d][:, None] * jax.nn.relu(0.8 - dr) ** 2) * w_rep + lap = Dpx - (jax.ops.segment_sum(Dpx[EJ], EI, NV) + jax.ops.segment_sum(Dpx[EI], EJ, NV)) / deg[:, None] + reg = jnp.sum(lap ** 2) * float(os.environ.get("UO_CLAP", "0.05")) + jnp.sum(Dpx ** 2) * 0.0005 + return lin + lcov + lrep + reg, (lin, lcov, lrep) + + +vg = jax.jit(jax.value_and_grad(loss_fn, has_aux=True)) + + +def raster_check(Dpx, pp, masks, unknown): + X = posed_with(pp, V0 + jnp.asarray(Dpx) / 36.0) + red = blue = area = 0; blue_pts = [] + for d in range(5): + if d not in VIEWS: + blue_pts.append(np.zeros((0, 2), np.float32)); continue + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H) & ~unknown[d] + s = masks[d] + b = mk & ~s; r = s & ~mk + red += r.sum(); blue += b.sum(); area += s.sum() + ys, xs = np.nonzero(b); blue_pts.append(np.stack([xs + 0.5, ys + 0.5], 1).astype(np.float32)) + return red, blue, area, blue_pts + + + + +def frame_data(Mi, hidi): + sdf_r = jnp.asarray(np.stack([sdf_sq(Mi[d]) for d in range(5)])) + sdf_a = jnp.asarray(np.stack([sdf_sq(Mi[d] | hidi[d]) for d in range(5)])) + tg = np.zeros((5, NT, 2), np.float32); tm = np.zeros((5, NT), np.float32) + for d in range(5): + t = targets_of(Mi[d], hidi[d]) + if len(t) > NT: + t = t[np.linspace(0, len(t) - 1, NT).astype(int)] + tg[d, :len(t)] = t; tm[d, :len(t)] = 1 + return sdf_r, sdf_a, jnp.asarray(tg), jnp.asarray(tm) + + +def candidates(pp, Dpx, sdf_r): + Xc = np.asarray(posed_with(pp, V0 + Dpx / 36.0)) + cand = np.zeros((5, NC), np.int32); cmask = np.zeros((5, NC), np.float32) + for d in range(5): + pc = np.asarray(project(jnp.asarray(Xc), d)) + sd = np.asarray(bilin(sdf_r[d], jnp.asarray(pc))) + idx = np.nonzero(np.abs(sd) < 4.0)[0] + if len(idx) > NC: + idx = idx[np.argsort(np.abs(sd[idx]))[:NC]] + cand[d, :len(idx)] = idx; cmask[d, :len(idx)] = 1 + return jnp.asarray(cand), jnp.asarray(cmask) + + +# ---- pixel-level (raster-aligned) helpers used by stages 3 and 4 +NP = 512 # max (pixel, triangle) pairs per view +TRI = jnp.asarray(tris) + + +def bary_min(p, t, c): + """min barycentric coordinate of point c in projected triangle t (p: projected vertices)""" + A, B, C = p[TRI[t, 0]], p[TRI[t, 1]], p[TRI[t, 2]] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + den = jnp.where(jnp.abs(den) < 1e-6, 1e-6, den) + l0 = ((B[:, 1] - C[:, 1]) * (c[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (c[:, 1] - C[:, 1])) / den + l1 = ((C[:, 1] - A[:, 1]) * (c[:, 0] - C[:, 0]) + (A[:, 0] - C[:, 0]) * (c[:, 1] - C[:, 1])) / den + return jnp.minimum(jnp.minimum(l0, l1), 1 - l0 - l1) + + + +def raster_ids(P2): + """per pixel centre: list of covering triangle ids (all layers)""" + cover = {} + mn = np.floor(P2.min(1)).astype(int); mx = np.ceil(P2.max(1)).astype(int) + A, B, C = P2[:, 0], P2[:, 1], P2[:, 2] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + ok = np.abs(den) > 1e-12; size = np.clip(mx - mn, 0, 16) + ids = [] + for dy in range(int(size[:, 1].max()) + 1): + for dx in range(int(size[:, 0].max()) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px = mn[t, 0] + dx; py = mn[t, 1] + dy; cx, cy = px + 0.5, py + 0.5 + l0 = ((B[t, 1] - C[t, 1]) * (cx - C[t, 0]) + (C[t, 0] - B[t, 0]) * (cy - C[t, 1])) / den[t] + l1 = ((C[t, 1] - A[t, 1]) * (cx - C[t, 0]) + (A[t, 0] - C[t, 0]) * (cy - C[t, 1])) / den[t] + k = (l0 >= -1e-4) & (l1 >= -1e-4) & (1 - l0 - l1 >= -1e-4) & (px >= 0) & (py >= 0) & (px < CANVAS_W) & (py < CANVAS_H) + ids.append(np.stack([py[k], px[k], t[k]], 1)) + return np.concatenate(ids, 0) + + +def pairs_for(P2, s, unknown): + """exclusion pairs (blue pixel, covering triangle) and inclusion pairs (red pixel, nearest triangle)""" + ids = raster_ids(P2) + cov = np.zeros(s.shape, bool); cov[ids[:, 0], ids[:, 1]] = True; cov &= ~unknown + blue = cov & ~s; red = s & ~cov + sel = blue[ids[:, 0], ids[:, 1]] + ex = ids[sel] + ex_c = np.stack([ex[:, 1] + 0.5, ex[:, 0] + 0.5], 1); ex_t = ex[:, 2] + ry, rx = np.nonzero(red) + cen = P2.mean(1) + in_t = np.array([np.argmin(((cen - [x + 0.5, y + 0.5]) ** 2).sum(1)) for y, x in zip(ry, rx)], int) + in_c = np.stack([rx + 0.5, ry + 0.5], 1) if len(rx) else np.zeros((0, 2)) + return (ex_t, ex_c), (in_t, in_c), int(blue.sum()), int(red.sum()) + + +def pad(t, c): + tt = np.zeros(NP, np.int32); cc = np.zeros((NP, 2), np.float32); mm = np.zeros(NP, np.float32) + n = min(len(t), NP); tt[:n] = t[:n]; cc[:n] = c[:n]; mm[:n] = 1 + return tt, cc, mm + + diff --git a/third_party/UO_Model3D_v13/pipeline/delight_bake.py b/third_party/UO_Model3D_v13/pipeline/delight_bake.py new file mode 100644 index 0000000..17b90d4 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/delight_bake.py @@ -0,0 +1,125 @@ +"""Separate albedo from the UO lighting: sprite = albedo * (ambient + diffuse * max(0, n.L)), light fixed to the camera. +Estimates L, ambient, diffuse from all frames and bakes an albedo texture (linear model, sRGB output).""" +import sys, pickle, time +import numpy as np +from scipy.optimize import least_squares +TEX = 1024 +sys.argv = ["bake_all.py"] +src = open("bake_all.py").read() +exec(src.split("def gather(")[0]) # setup: mesh, poses, texel map, cores, colors, raster_vec, vert_normals + + +def srgb2lin(c): + c = c / 255.0 + return np.where(c <= 0.04045, c / 12.92, ((c + 0.055) / 1.055) ** 2.4) + + +def lin2srgb(c): + c = np.clip(c, 0, 1) + return np.where(c <= 0.0031308, c * 12.92, 1.055 * c ** (1 / 2.4) - 0.055) * 255.0 + + +def visible_samples(s, d, X, nrm, Pt, Nt, zcache): + f = np.asarray(FWD[d]); depth = X @ f + if (s, d) not in zcache: + zb = np.full((H * SS, Wc * SS), -np.inf) + pd = (ANCHOR_X + PX_OFF + SC * (X @ np.asarray(RIGHT[d])), ANCHOR_Y - SC * (X @ np.asarray(UP[d]))) + P2 = np.stack(pd, 1) + zt, zx, zy, zbc = raster_vec(P2[tris] * SS, None, Wc * SS, H * SS) + np.maximum.at(zb, (zy, zx), np.einsum("nk,nk->n", zbc, depth[tris[zt]])) + zcache[(s, d)] = zb + zb = zcache[(s, d)] + sx = ANCHOR_X + PX_OFF + SC * (Pt @ np.asarray(RIGHT[d])); sy = ANCHOR_Y - SC * (Pt @ np.asarray(UP[d])) + dz = Pt @ f; facing = Nt @ f + xi, yi = np.floor(sx).astype(int), np.floor(sy).astype(int) + zx_, zy_ = np.clip(np.floor(sx * SS).astype(int), 0, Wc * SS - 1), np.clip(np.floor(sy * SS).astype(int), 0, H * SS - 1) + ok = (xi >= 0) & (xi < Wc) & (yi >= 0) & (yi < H) & (facing > 0.2) + ok &= dz >= zb[zy_, zx_] - 0.015 + ok[ok] &= cores[s, d][yi[ok], xi[ok]] + idx = np.nonzero(ok)[0] + col = srgb2lin(colors[s][d][yi[idx], xi[idx]].astype(np.float64)) + ncam = np.stack([Nt[idx] @ np.asarray(RIGHT[d]), Nt[idx] @ np.asarray(UP[d]), Nt[idx] @ f], 1) + return idx, col, ncam, facing[idx] ** 2 + + +def frame_geom(s): + pp = {k: poses[k][s] for k in ("ball", "hinge", "trans")} + _, X = forward(delta, pp) + X = np.asarray(X); nrm = vert_normals(X) + Pt = np.einsum("nk,nkd->nd", tb, X[tris[tt]]) + Nt = np.einsum("nk,nkd->nd", tb, nrm[tris[tt]]) + Nt /= np.maximum(np.linalg.norm(Nt, axis=1, keepdims=True), 1e-12) + return X, nrm, Pt, Nt + + +# ---- 1) subsample for the light fit +rng = np.random.default_rng(0) +I, C, N, Wt = [], [], [], [] +for s in range(0, NS, 3): + X, nrm, Pt, Nt = frame_geom(s) + for d in range(5): + idx, col, ncam, w = visible_samples(s, d, X, nrm, Pt, Nt, {}) + k = rng.random(len(idx)) < 0.25 + I.append(idx[k]); C.append(col[k]); N.append(ncam[k]); Wt.append(w[k]) +I = np.concatenate(I); C = np.concatenate(C); N = np.concatenate(N); Wt = np.concatenate(Wt) +print("light-fit samples", len(I), f"{time.time()-t0:.0f}s", flush=True) + + +def shading(params, n): + th, ph, amb, dif = params + L = np.array([np.sin(th) * np.cos(ph), np.sin(th) * np.sin(ph), np.cos(th)]) + return amb + dif * np.maximum(n @ L, 0.0) + + +def albedo_from(params): + sh = shading(params, N) + num = np.zeros((NT, 3)); den = np.zeros(NT) + np.add.at(num, I, Wt[:, None] * C * sh[:, None]); np.add.at(den, I, Wt * sh * sh) + return num / np.maximum(den, 1e-9)[:, None], den > 0 + + +params = np.array([0.8, 2.3, 0.4, 0.6]) # initial: light from upper-left-front, 40% ambient +sel = rng.choice(len(I), min(400000, len(I)), replace=False) +for it in range(4): + rho, has = albedo_from(params) + ok = has[I[sel]] + def res(p): + p = np.array([p[0], p[1], p[2], 1.0 - p[2]]) # amb + dif = 1 (scale lives in the albedo) + return (np.sqrt(Wt[sel][ok])[:, None] * (rho[I[sel][ok]] * shading(p, N[sel][ok])[:, None] - C[sel][ok])).ravel() + r = least_squares(res, params[:3], bounds=([0.0, -np.pi, 0.05], [np.pi, np.pi, 0.95])) + params = np.array([r.x[0], r.x[1], r.x[2], 1.0 - r.x[2]]) + th, ph = params[:2] + L = [np.sin(th) * np.cos(ph), np.sin(th) * np.sin(ph), np.cos(th)] + print(f"iter {it}: light dir (camera: right,up,toward) {np.round(L,3)} ambient {params[2]:.3f} diffuse {params[3]:.3f} " + f"rms {np.sqrt(np.mean(r.fun**2)):.4f}", flush=True) + +# ---- 2) full albedo bake (robust, streaming, 2 passes) +def full_pass(prev=None, sigma=0.08): + num = np.zeros((NT, 3)); den = np.zeros(NT) + for s in range(NS): + X, nrm, Pt, Nt = frame_geom(s) + zc = {} + for d in range(5): + idx, col, ncam, w = visible_samples(s, d, X, nrm, Pt, Nt, zc) + sh = shading(params, ncam) + if prev is not None: + diff = np.linalg.norm(prev[idx] * sh[:, None] - col, axis=1) + w = w * np.exp(-0.5 * (diff / sigma) ** 2) + np.add.at(num, idx, w[:, None] * col * sh[:, None]); np.add.at(den, idx, w * sh * sh) + return num / np.maximum(den, 1e-9)[:, None], den + + +alb1, _ = full_pass() +alb2, den = full_pass(alb1) +print("albedo covered %.1f%%" % (100 * (den > 1e-9).mean()), f"{time.time()-t0:.0f}s", flush=True) +tex = np.zeros((TEX, TEX, 3)); wt = np.zeros((TEX, TEX)) +tex[ty, tx] = lin2srgb(alb2); wt[ty, tx] = den > 1e-9 +from texbake import pull_push_fill +from PIL import Image +filled = pull_push_fill(tex, wt) +Image.fromarray(np.clip(filled, 0, 255).astype(np.uint8)).save("UO_Body_Albedo.png") +th, ph = params[:2] +light = dict(L_camera=[float(np.sin(th) * np.cos(ph)), float(np.sin(th) * np.sin(ph)), float(np.cos(th))], + ambient=float(params[2]), diffuse=float(params[3])) +pickle.dump(light, open("uo_light.pkl", "wb")) +print("saved UO_Body_Albedo.png", light, flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/diag_offset.py b/third_party/UO_Model3D_v13/pipeline/diag_offset.py new file mode 100644 index 0000000..4304aa9 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/diag_offset.py @@ -0,0 +1,28 @@ +import sys +sys.argv=['refine_mesh.py','0'] +exec(open('refine_mesh.py').read().split('params = dict(delta=')[0]) +import pickle +from texbake import tri_raster +r=pickle.load(open('refine_mesh.pkl','rb')) +params=dict(delta=jnp.asarray(r['delta']), **{k:jnp.asarray(v) for k,v in r['poses'].items()}) +def raster_mask(q): + m=np.zeros((H,Wc),bool) + def fn(t,xs,ys,bc): m[ys,xs]=True + tri_raster(q[tris],fn,Wc,H) + return m +rng=np.random.default_rng(1); pick=rng.choice(NS,25,replace=False) +proj={} +for s in pick: + pp={k:params[k][s] for k in ('ball','hinge','trans')} + p,_=forward(params['delta'],pp); proj[s]=np.asarray(p) +best=None +for ox in (-1.0,-0.5,0.0,0.5,1.0): + for oy in (-1.0,-0.5,0.0,0.5,1.0): + tot=[0,0] + for s in pick: + for d in range(5): + m=raster_mask(proj[s][d]+np.array([ox,oy])); sm=masks[s,d] + tot[0]+=(m&sm).sum(); tot[1]+=(m|sm).sum() + iou=tot[0]/tot[1]; print(f"offset x {ox:+.1f} y {oy:+.1f} IoU {iou:.4f}", flush=True) + if best is None or iou>best[0]: best=(iou,ox,oy) +print('best',best) diff --git a/third_party/UO_Model3D_v13/pipeline/err_parts.py b/third_party/UO_Model3D_v13/pipeline/err_parts.py new file mode 100644 index 0000000..611f413 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/err_parts.py @@ -0,0 +1,65 @@ +"""Attribute silhouette errors to body parts: red = sprite-only px (nearest model part), blue = model-only px.""" +import sys, pickle, numpy as np, jax, jax.numpy as jnp +from scipy.ndimage import distance_transform_edt +from posefit_mesh import * +from posefit_mesh import _posed_j +from vd import ACTIONS_PEOPLE +P = pickle.load(open(sys.argv[1], "rb")) +ACTS = [int(x) for x in sys.argv[2].split(",")] if len(sys.argv) > 2 else [a for a in range(35) if a not in MOUNTED] +groups = ["head", "neck", "chest", "spine", "pelvis", "upperarm", "forearm", "hand", "thigh", "shin", "foot"] +Wn = np.asarray(md["W"]); bones = md["bones"] +def grp(b): + n = b.split(".")[0] + for g in groups: + if n.startswith(g): return g + return {"shoulder": "upperarm", "clavicle": "chest"}.get(n, n) +bg = [grp(b) for b in bones] +G = sorted(set(bg)); gi = {g: i for i, g in enumerate(G)} +vlab = np.array([gi[bg[j]] for j in Wn.argmax(1)]) +tlab = vlab[tris[:, 0]] +print("groups", G) + +def raster_lab(Pt, lab): + mn = np.floor(Pt.min(1)).astype(int); mx = np.ceil(Pt.max(1)).astype(int) + size = np.clip(mx - mn, 0, 12) + a, b, c = Pt[:, 0], Pt[:, 1], Pt[:, 2] + den = (b[:, 1] - c[:, 1]) * (a[:, 0] - c[:, 0]) + (c[:, 0] - b[:, 0]) * (a[:, 1] - c[:, 1]) + ok = np.abs(den) > 1e-12 + img = np.full((CANVAS_H, CANVAS_W), -1) + for dy in range(int(size[:, 1].max()) + 1): + for dx in range(int(size[:, 0].max()) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px = mn[t, 0] + dx; py = mn[t, 1] + dy; cx, cy = px + 0.5, py + 0.5 + aa, bb, cc, dd = a[t], b[t], c[t], den[t] + l0 = ((bb[:, 1] - cc[:, 1]) * (cx - cc[:, 0]) + (cc[:, 0] - bb[:, 0]) * (cy - cc[:, 1])) / dd + l1 = ((cc[:, 1] - aa[:, 1]) * (cx - cc[:, 0]) + (aa[:, 0] - cc[:, 0]) * (cy - cc[:, 1])) / dd + l2 = 1 - l0 - l1 + k = (l0 >= -1e-4) & (l1 >= -1e-4) & (l2 >= -1e-4) & (px >= 0) & (py >= 0) & (px < CANVAS_W) & (py < CANVAS_H) + img[py[k], px[k]] = lab[t[k]] + return img + +red = np.zeros((35, len(G))); blue = np.zeros((35, len(G))); area = np.zeros(35) +for a in ACTS: + T = targets(a); masks = T[..., 3] > 127; F = len(T) + hidden = (horse_masks(a, F) & ~masks) if a in HORSE_OF else np.zeros_like(masks) + for i in range(F): + X = np.asarray(_posed_j({k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()})) + for d in range(5): + L = raster_lab(np.asarray(project(jnp.asarray(X), d))[tris], tlab) + L[hidden[i, d]] = -1 + mk = L >= 0; s = masks[i, d] + area[a] += s.sum() + b = mk & ~s + np.add.at(blue[a], L[b], 1) + r = s & ~mk + if r.any(): + _, (iy, ix) = distance_transform_edt(~mk, return_indices=True) + np.add.at(red[a], L[iy[r], ix[r]], 1) +tot_r = red.sum(0); tot_b = blue.sum(0) +print("%-10s %8s %8s (pixels, all listed actions)" % ("part", "sprite+", "model+")) +for g in G: + print("%-10s %8d %8d" % (g, tot_r[gi[g]], tot_b[gi[g]])) +print("per action worst part (sprite-only):") +for a in ACTS: + j = red[a].argmax(); k = blue[a].argmax() + print(f"{a:2d} {ACTIONS_PEOPLE[a]:22s} red {red[a].sum()/area[a]:.3f} ({G[j]} {red[a,j]/area[a]:.3f}) blue {blue[a].sum()/area[a]:.3f} ({G[k]} {blue[a,k]/area[a]:.3f})") diff --git a/third_party/UO_Model3D_v13/pipeline/export.py b/third_party/UO_Model3D_v13/pipeline/export.py new file mode 100644 index 0000000..53a95b1 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/export.py @@ -0,0 +1,34 @@ +import bpy, sys, os +blend = sys.argv[sys.argv.index("--blend") + 1] +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(blend)) +base = os.path.splitext(os.path.abspath(blend))[0] +arm = bpy.data.objects["UO_Rig"] +arm.animation_data.action = bpy.data.actions.get("04_stand") or arm.animation_data.action +# exporters understand a plain Principled BSDF with a base-colour texture: bypass the "UO look" mix for export +for m in bpy.data.materials: + if m.use_nodes: + nodes = m.node_tree.nodes + out = next((n for n in nodes if n.type == "OUTPUT_MATERIAL"), None) + bsdf = next((n for n in nodes if n.type == "BSDF_PRINCIPLED"), None) + if out and bsdf: + m.node_tree.links.new(bsdf.outputs["BSDF"], out.inputs["Surface"]) +body = bpy.data.objects["UO_Body"] +if body.data.shape_keys: # per-frame corrective keys only serve the UO renders inside Blender + body.shape_key_clear() +bpy.ops.object.select_all(action="DESELECT") +for name in ("UO_Rig", "UO_Body"): # the body model only (no example clothing, camera or lights) + bpy.data.objects[name].select_set(True) +bpy.context.view_layer.objects.active = bpy.data.objects["UO_Rig"] +bpy.ops.export_scene.gltf( + filepath=base + ".glb", export_format="GLB", use_selection=True, + export_animations=True, export_animation_mode="ACTIONS", export_skins=True, + export_texcoords=True, export_normals=True, export_materials="EXPORT", + export_cameras=False, export_lights=False, export_yup=True, export_apply=False, + export_force_sampling=True, export_optimize_animation_size=False) +bpy.ops.export_scene.fbx( + filepath=base + ".fbx", use_selection=True, object_types={"ARMATURE", "MESH"}, + add_leaf_bones=False, bake_anim=True, bake_anim_use_all_actions=True, + bake_anim_use_nla_strips=False, bake_anim_force_startend_keying=True, + path_mode="COPY", embed_textures=True, primary_bone_axis="Y", secondary_bone_axis="X", + use_armature_deform_only=False, mesh_smooth_type="FACE") +print("exported", base + ".glb", base + ".fbx") diff --git a/third_party/UO_Model3D_v13/pipeline/extract_tiledata.py b/third_party/UO_Model3D_v13/pipeline/extract_tiledata.py new file mode 100644 index 0000000..8435598 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/extract_tiledata.py @@ -0,0 +1,85 @@ +"""Wearable items of the UO client joined with their animation and with the measured extents. + +tiledata.mul (High Seas layout: 0x4000 land tiles of 30 bytes, 0x10000 item tiles of 41 bytes, a 4-byte header before every +32 tiles) gives for every wearable item its animation id and layer. Bodyconv.def says in which file the animation lives +(orig -> anim2 / anim3 / anim4 / anim5 id; no line = same id in anim.mul). equipment_extent.json (measure_equipment_extent.py) +gives the extent of that animation around the anchor. + + python extract_tiledata.py +""" +import json, struct, sys +from collections import defaultdict + +LAYERS = {1: "OneHanded", 2: "TwoHanded", 3: "Shoes", 4: "Pants", 5: "Shirt", 6: "Helm", 7: "Gloves", 8: "Ring", 9: "Talisman", + 10: "Neck", 11: "Hair", 12: "Waist", 13: "InnerTorso", 14: "Bracelet", 16: "FacialHair", 17: "MiddleTorso", + 18: "Earrings", 19: "Arms", 20: "Cloak", 21: "Backpack", 22: "OuterTorso", 23: "OuterLegs", 24: "InnerLegs"} +WEARABLE = 0x00400000 +FILES = ("anim2", "anim3", "anim4", "anim5") +CANVASES = {"136x120": dict(left=68, right=68, up=86, down=34), "256x256": dict(left=128, right=128, up=192, down=64)} + + +def read_items(path): + d = open(path, "rb").read() + off = 512 * (4 + 32 * 30) # land tiles + items = [] + for g in range(0x10000 // 32): + off += 4 + for i in range(32): + flags, weight, quality, misc, unk2, qty, anim, unk3, hue, stack, value, height = struct.unpack_from("= 5 and all(x.lstrip("-").isdigit() for x in t[:5]): + o, *a = [int(x) for x in t[:5]] + for f, v in zip(FILES, a): + if v >= 0: + m[o] = (f, v) + break + return m + + +if __name__ == "__main__": + tdata, bconv, ext_path, out = sys.argv[1:5] + ext = json.load(open(ext_path))["bodies"] + conv = read_bodyconv(bconv) + anims = defaultdict(lambda: dict(layers=set(), items=[])) + for tid, flags, layer, anim, name in read_items(tdata): + if flags & WEARABLE and anim: + a = anims[anim] + a["layers"].add(layer) + a["items"].append((tid, name)) + res = {} + for anim, a in sorted(anims.items()): + src = "%s:%d" % conv.get(anim, ("anim", anim)) + e = ext.get(src) + res[anim] = dict(src=src, layers=sorted(a["layers"]), n_items=len(a["items"]), items=a["items"][:6], + extent={k: e[k] for k in ("left", "right", "up", "down")} if e else None, frames=e["frames"] if e else 0, + complete=bool(e and e["blocks"] == 175)) + stats = {} + print("wearable animation ids: %d, with frames in the client: %d" % (len(res), sum(1 for r in res.values() if r["extent"]))) + for layer in sorted({l for r in res.values() for l in r["layers"]}): + rows = [r for r in res.values() if layer in r["layers"] and r["extent"]] + if not rows: + continue + s = {"animations": len(rows)} + for cname, cv in CANVASES.items(): + out_ = [r for r in rows if any(r["extent"][k] > cv[k] for k in cv)] + s["over_" + cname] = len(out_) + s["max_over_" + cname] = max((max(r["extent"][k] - cv[k] for k in cv) for r in rows), default=0) + stats[LAYERS.get(layer, str(layer))] = s + print("%-12s %3d animations | outside 136x120: %3d (worst +%3d px) | outside 256x256: %2d (worst +%3d px)" % ( + LAYERS.get(layer, layer), s["animations"], s["over_136x120"], s["max_over_136x120"], s["over_256x256"], s["max_over_256x256"])) + out_rows = [(a, r) for a, r in res.items() if r["extent"] and any(r["extent"][k] > CANVASES["256x256"][k] for k in CANVASES["256x256"])] + print("outside 256x256:") + for a, r in out_rows: + print(" anim id %4d (%s) layers %s extent %s items %s" % (a, r["src"], [LAYERS.get(l, l) for l in r["layers"]], r["extent"], [n for _, n in r["items"][:3]])) + json.dump(dict(layers=LAYERS, stats_by_layer=stats, animations={str(a): r for a, r in res.items()}), open(out, "w"), indent=1) diff --git a/third_party/UO_Model3D_v13/pipeline/finalize_v10.py b/third_party/UO_Model3D_v13/pipeline/finalize_v10.py new file mode 100644 index 0000000..be7e132 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/finalize_v10.py @@ -0,0 +1,18 @@ +"""final_poses_v10.pkl = v10pre with the de-jittered actions + quality table (Polish headers like v5).""" +import pickle, numpy as np +from vd import ACTIONS_PEOPLE +pre = pickle.load(open("final_poses_v10pre.pkl", "rb")); v6 = pickle.load(open("final_poses_v9_ref.pkl", "rb")) +out = {a: dict(r) for a, r in pre.items()} +for f in ("posefit_K11.pkl",): + for a, r in pickle.load(open(f, "rb")).items(): + out[a] = dict(r, src=pre[a].get("src", "v9") + "+dejitter") +pickle.dump(out, open("final_poses_v10.pkl", "wb")) +L = ["| # | akcja | IoU najgorszy kier. (śr.) | min | IoU średnie | limity (max) | v9 IoU najgorszy | v9 IoU średnie |", "|---|---|---|---|---|---|---|---|"] +for a in range(35): + r = out[a]["iou"]; o = v6[a]["iou"] + L.append(f"| {a} | {ACTIONS_PEOPLE[a]} | {r[:,0].mean():.3f} | {r[:,0].min():.3f} | {r[:,1].mean():.3f} | {out[a]['limits'].max():.4f} | {o[:,0].mean():.3f} | {o[:,1].mean():.3f} |") +w = np.mean([out[a]["iou"][:, 0].mean() for a in range(35)]); w5 = np.mean([v6[a]["iou"][:, 0].mean() for a in range(35)]) +m = np.mean([out[a]["iou"][:, 1].mean() for a in range(35)]); m5 = np.mean([v6[a]["iou"][:, 1].mean() for a in range(35)]) +L.append(f"| | **średnio** | **{w:.3f}** | | **{m:.3f}** | | {w5:.3f} | {m5:.3f} |") +open("quality_v10.md", "w").write("\n".join(L) + "\n") +print("\n".join(L[-3:])) diff --git a/third_party/UO_Model3D_v13/pipeline/finalize_v6.py b/third_party/UO_Model3D_v13/pipeline/finalize_v6.py new file mode 100644 index 0000000..97c60cf --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/finalize_v6.py @@ -0,0 +1,18 @@ +"""final_poses_v6.pkl = v6pre with the de-jittered actions + quality table (Polish headers like v5).""" +import pickle, numpy as np +from vd import ACTIONS_PEOPLE +pre = pickle.load(open("final_poses_v6pre.pkl", "rb")); v5 = pickle.load(open("final_poses_v5.pkl", "rb")) +out = {a: dict(r) for a, r in pre.items()} +for f in ("posefit_J1.pkl", "posefit_J2.pkl"): + for a, r in pickle.load(open(f, "rb")).items(): + out[a] = dict(r, src=pre[a].get("src", "v5") + "+dejitter") +pickle.dump(out, open("final_poses_v6.pkl", "wb")) +L = ["| # | akcja | IoU najgorszy kier. (śr.) | min | IoU średnie | limity (max) | v5 IoU najgorszy | v5 IoU średnie |", "|---|---|---|---|---|---|---|---|"] +for a in range(35): + r = out[a]["iou"]; o = v5[a]["iou"] + L.append(f"| {a} | {ACTIONS_PEOPLE[a]} | {r[:,0].mean():.3f} | {r[:,0].min():.3f} | {r[:,1].mean():.3f} | {out[a]['limits'].max():.4f} | {o[:,0].mean():.3f} | {o[:,1].mean():.3f} |") +w = np.mean([out[a]["iou"][:, 0].mean() for a in range(35)]); w5 = np.mean([v5[a]["iou"][:, 0].mean() for a in range(35)]) +m = np.mean([out[a]["iou"][:, 1].mean() for a in range(35)]); m5 = np.mean([v5[a]["iou"][:, 1].mean() for a in range(35)]) +L.append(f"| | **średnio** | **{w:.3f}** | | **{m:.3f}** | | {w5:.3f} | {m5:.3f} |") +open("quality_v6.md", "w").write("\n".join(L) + "\n") +print("\n".join(L[-3:])) diff --git a/third_party/UO_Model3D_v13/pipeline/finalize_v7.py b/third_party/UO_Model3D_v13/pipeline/finalize_v7.py new file mode 100644 index 0000000..8475bd4 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/finalize_v7.py @@ -0,0 +1,18 @@ +"""final_poses_v7.pkl = v7pre with the de-jittered actions + quality table (Polish headers like v5).""" +import pickle, numpy as np +from vd import ACTIONS_PEOPLE +pre = pickle.load(open("final_poses_v7pre.pkl", "rb")); v6 = pickle.load(open("final_poses_v6.pkl", "rb")) +out = {a: dict(r) for a, r in pre.items()} +for f in ("posefit_K1.pkl", "posefit_K2.pkl"): + for a, r in pickle.load(open(f, "rb")).items(): + out[a] = dict(r, src=pre[a].get("src", "v6") + "+dejitter") +pickle.dump(out, open("final_poses_v7.pkl", "wb")) +L = ["| # | akcja | IoU najgorszy kier. (śr.) | min | IoU średnie | limity (max) | v6 IoU najgorszy | v6 IoU średnie |", "|---|---|---|---|---|---|---|---|"] +for a in range(35): + r = out[a]["iou"]; o = v6[a]["iou"] + L.append(f"| {a} | {ACTIONS_PEOPLE[a]} | {r[:,0].mean():.3f} | {r[:,0].min():.3f} | {r[:,1].mean():.3f} | {out[a]['limits'].max():.4f} | {o[:,0].mean():.3f} | {o[:,1].mean():.3f} |") +w = np.mean([out[a]["iou"][:, 0].mean() for a in range(35)]); w5 = np.mean([v6[a]["iou"][:, 0].mean() for a in range(35)]) +m = np.mean([out[a]["iou"][:, 1].mean() for a in range(35)]); m5 = np.mean([v6[a]["iou"][:, 1].mean() for a in range(35)]) +L.append(f"| | **średnio** | **{w:.3f}** | | **{m:.3f}** | | {w5:.3f} | {m5:.3f} |") +open("quality_v7.md", "w").write("\n".join(L) + "\n") +print("\n".join(L[-3:])) diff --git a/third_party/UO_Model3D_v13/pipeline/finalize_v8.py b/third_party/UO_Model3D_v13/pipeline/finalize_v8.py new file mode 100644 index 0000000..df76159 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/finalize_v8.py @@ -0,0 +1,18 @@ +"""final_poses_v8.pkl = v8pre with the de-jittered actions + quality table (Polish headers like v5).""" +import pickle, numpy as np +from vd import ACTIONS_PEOPLE +pre = pickle.load(open("final_poses_v8pre.pkl", "rb")); v6 = pickle.load(open("final_poses_v7.pkl", "rb")) +out = {a: dict(r) for a, r in pre.items()} +for f in ("posefit_K8.pkl",): + for a, r in pickle.load(open(f, "rb")).items(): + out[a] = dict(r, src=pre[a].get("src", "v7") + "+dejitter") +pickle.dump(out, open("final_poses_v8.pkl", "wb")) +L = ["| # | akcja | IoU najgorszy kier. (śr.) | min | IoU średnie | limity (max) | v7 IoU najgorszy | v7 IoU średnie |", "|---|---|---|---|---|---|---|---|"] +for a in range(35): + r = out[a]["iou"]; o = v6[a]["iou"] + L.append(f"| {a} | {ACTIONS_PEOPLE[a]} | {r[:,0].mean():.3f} | {r[:,0].min():.3f} | {r[:,1].mean():.3f} | {out[a]['limits'].max():.4f} | {o[:,0].mean():.3f} | {o[:,1].mean():.3f} |") +w = np.mean([out[a]["iou"][:, 0].mean() for a in range(35)]); w5 = np.mean([v6[a]["iou"][:, 0].mean() for a in range(35)]) +m = np.mean([out[a]["iou"][:, 1].mean() for a in range(35)]); m5 = np.mean([v6[a]["iou"][:, 1].mean() for a in range(35)]) +L.append(f"| | **średnio** | **{w:.3f}** | | **{m:.3f}** | | {w5:.3f} | {m5:.3f} |") +open("quality_v8.md", "w").write("\n".join(L) + "\n") +print("\n".join(L[-3:])) diff --git a/third_party/UO_Model3D_v13/pipeline/finalize_v8b.py b/third_party/UO_Model3D_v13/pipeline/finalize_v8b.py new file mode 100644 index 0000000..1b5b551 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/finalize_v8b.py @@ -0,0 +1,18 @@ +"""final_poses_v8.pkl = v8pre with the de-jittered actions + quality table (Polish headers like v5).""" +import pickle, numpy as np +from vd import ACTIONS_PEOPLE +pre = pickle.load(open("final_poses_v8bpre.pkl", "rb")); v6 = pickle.load(open("final_poses_v7.pkl", "rb")) +out = {a: dict(r) for a, r in pre.items()} +for f in ("posefit_K9.pkl",): + for a, r in pickle.load(open(f, "rb")).items(): + out[a] = dict(r, src=pre[a].get("src", "v7") + "+dejitter") +pickle.dump(out, open("final_poses_v8.pkl", "wb")) +L = ["| # | akcja | IoU najgorszy kier. (śr.) | min | IoU średnie | limity (max) | v7 IoU najgorszy | v7 IoU średnie |", "|---|---|---|---|---|---|---|---|"] +for a in range(35): + r = out[a]["iou"]; o = v6[a]["iou"] + L.append(f"| {a} | {ACTIONS_PEOPLE[a]} | {r[:,0].mean():.3f} | {r[:,0].min():.3f} | {r[:,1].mean():.3f} | {out[a]['limits'].max():.4f} | {o[:,0].mean():.3f} | {o[:,1].mean():.3f} |") +w = np.mean([out[a]["iou"][:, 0].mean() for a in range(35)]); w5 = np.mean([v6[a]["iou"][:, 0].mean() for a in range(35)]) +m = np.mean([out[a]["iou"][:, 1].mean() for a in range(35)]); m5 = np.mean([v6[a]["iou"][:, 1].mean() for a in range(35)]) +L.append(f"| | **średnio** | **{w:.3f}** | | **{m:.3f}** | | {w5:.3f} | {m5:.3f} |") +open("quality_v8.md", "w").write("\n".join(L) + "\n") +print("\n".join(L[-3:])) diff --git a/third_party/UO_Model3D_v13/pipeline/finalize_v9.py b/third_party/UO_Model3D_v13/pipeline/finalize_v9.py new file mode 100644 index 0000000..a68495a --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/finalize_v9.py @@ -0,0 +1,18 @@ +"""final_poses_v9.pkl = v9pre with the de-jittered actions + quality table (Polish headers like v5).""" +import pickle, numpy as np +from vd import ACTIONS_PEOPLE +pre = pickle.load(open("final_poses_v9pre.pkl", "rb")); v6 = pickle.load(open("final_poses_v8a_ref.pkl", "rb")) +out = {a: dict(r) for a, r in pre.items()} +for f in ("posefit_K10.pkl",): + for a, r in pickle.load(open(f, "rb")).items(): + out[a] = dict(r, src=pre[a].get("src", "v8") + "+dejitter") +pickle.dump(out, open("final_poses_v9.pkl", "wb")) +L = ["| # | akcja | IoU najgorszy kier. (śr.) | min | IoU średnie | limity (max) | v8 IoU najgorszy | v8 IoU średnie |", "|---|---|---|---|---|---|---|---|"] +for a in range(35): + r = out[a]["iou"]; o = v6[a]["iou"] + L.append(f"| {a} | {ACTIONS_PEOPLE[a]} | {r[:,0].mean():.3f} | {r[:,0].min():.3f} | {r[:,1].mean():.3f} | {out[a]['limits'].max():.4f} | {o[:,0].mean():.3f} | {o[:,1].mean():.3f} |") +w = np.mean([out[a]["iou"][:, 0].mean() for a in range(35)]); w5 = np.mean([v6[a]["iou"][:, 0].mean() for a in range(35)]) +m = np.mean([out[a]["iou"][:, 1].mean() for a in range(35)]); m5 = np.mean([v6[a]["iou"][:, 1].mean() for a in range(35)]) +L.append(f"| | **średnio** | **{w:.3f}** | | **{m:.3f}** | | {w5:.3f} | {m5:.3f} |") +open("quality_v9.md", "w").write("\n".join(L) + "\n") +print("\n".join(L[-3:])) diff --git a/third_party/UO_Model3D_v13/pipeline/fit.py b/third_party/UO_Model3D_v13/pipeline/fit.py new file mode 100644 index 0000000..e7aa61d --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/fit.py @@ -0,0 +1,152 @@ +import numpy as np +import jax +import jax.numpy as jnp +import optax +from body import * + +POS_KEYS = ["hip_w", "hip_drop", "thigh", "shin", "ankle_h", "spine0", "abd", "chest_len", "neck_len", + "sh_x", "sh_z", "uarm", "farm", "hand", "pelvis_r", "abd_r", "chest_r", "head_r", "neck_r", + "uarm_r", "farm_r", "hand_r", "thigh_r", "shin_r", "foot_len", "foot_r"] +FIXED_KEYS = ["scale"] + +# hinge axes (in parent-local rest frame of the joint) +_sa, _ca = np.sin(ARM_REST_ANGLE), np.cos(ARM_REST_ANGLE) +_sl, _cl = np.sin(LEG_REST_ANGLE), np.cos(LEG_REST_ANGLE) +HINGE = { + JI["elbow.L"]: np.array([_ca, 0, _sa]), JI["elbow.R"]: np.array([_ca, 0, -_sa]), + JI["knee.L"]: np.array([_cl, 0, _sl]), JI["knee.R"]: np.array([_cl, 0, -_sl]), +} +HINGE_IDX = sorted(HINGE) +BALL_IDX = [j for j in range(NJ) if j not in HINGE] +HINGE_AX = jnp.asarray(np.stack([HINGE[j] for j in HINGE_IDX]), jnp.float32) + + +def shape_to_params(S): + p = {} + for k, v in S.items(): + if k in FIXED_KEYS: + continue + p[k] = jnp.log(v) if k in POS_KEYS else v + return p + + +CENTER_KEYS = ["pelvis_c", "abd_c", "chest_c", "head_c"] + + +def params_to_shape(p, fixed): + S = dict(fixed) + for k, v in p.items(): + S[k] = jnp.exp(v) if k in POS_KEYS else v + if k in CENTER_KEYS: # bilateral symmetry: torso/head centres on the mid-plane + S[k] = S[k].at[0].set(0.0) + return S + + +# anatomical plausibility bounds (metres); (key, component or None, lo, hi) +BOUNDS = [ + ("neck_y", None, -0.08, 0.02), ("sh_y", None, -0.05, 0.05), + ("chest_len", None, 0.15, 0.30), ("abd", None, 0.10, 0.25), ("spine0", None, 0.05, 0.15), + ("pelvis_c", 1, -0.03, 0.03), ("pelvis_c", 2, -0.04, 0.08), + ("pelvis_r", 0, 0.12, 0.22), ("pelvis_r", 1, 0.08, 0.15), ("pelvis_r", 2, 0.08, 0.15), + ("abd_c", 1, -0.04, 0.02), ("abd_c", 2, 0.03, 0.15), + ("abd_r", 0, 0.11, 0.20), ("abd_r", 1, 0.08, 0.15), ("abd_r", 2, 0.08, 0.16), + ("chest_c", 1, -0.04, 0.02), ("chest_c", 2, 0.05, 0.20), + ("chest_r", 0, 0.14, 0.26), ("chest_r", 1, 0.09, 0.16), ("chest_r", 2, 0.10, 0.20), + ("head_c", 1, -0.06, 0.02), ("head_c", 2, 0.06, 0.14), + ("head_r", 0, 0.07, 0.11), ("head_r", 1, 0.09, 0.13), ("head_r", 2, 0.10, 0.14), + ("neck_len", None, 0.06, 0.16), ("neck_r", None, 0.04, 0.09), + ("hand_r", 0, 0.02, 0.045), ("hand_r", 1, 0.035, 0.06), ("hand_r", 2, 0.07, 0.10), + ("hand", None, 0.15, 0.24), ("foot_len", None, 0.22, 0.30), ("foot_r", 0, 0.03, 0.05), ("foot_r", 1, 0.03, 0.05), + ("heel_y", None, 0.0, 0.07), ("ankle_h", None, 0.06, 0.12), + ("uarm", None, 0.22, 0.34), ("farm", None, 0.20, 0.32), ("thigh", None, 0.34, 0.50), ("shin", None, 0.38, 0.48), + ("hip_w", None, 0.085, 0.13), ("hip_drop", None, 0.03, 0.10), ("sh_x", None, 0.15, 0.24), ("sh_z", None, 0.12, 0.25), + ("uarm_r", 0, 0.045, 0.085), ("uarm_r", 1, 0.04, 0.075), ("farm_r", 0, 0.04, 0.07), ("farm_r", 1, 0.03, 0.055), + ("thigh_r", 0, 0.07, 0.10), ("thigh_r", 1, 0.05, 0.085), ("shin_r", 0, 0.05, 0.085), ("shin_r", 1, 0.035, 0.06), + ("theta", None, 0.35, 0.75), +] + + +def bounds_penalty(S): + pen = 0.0 + for k, i, lo, hi in BOUNDS: + x = S[k] if i is None else S[k][i] + pen += (jax.nn.relu(lo - x) ** 2 + jax.nn.relu(x - hi) ** 2) * 1e4 + # keep a crotch gap: thighs must not overlap at the hips + pen += jax.nn.relu(S["thigh_r"][0] - (S["hip_w"] - 0.005)) ** 2 * 1e4 + return pen + + +TORSO_JOINTS = [JI[n] for n in ("spine", "chest", "neck", "head")] + + +def pose_from_params(pp): + rot = jnp.zeros((NJ, 3), jnp.float32) + rot = rot.at[jnp.array(BALL_IDX)].set(pp["ball"]) + rot = rot.at[jnp.array(HINGE_IDX)].set(pp["hinge"][:, None] * HINGE_AX) + return dict(rot=rot, trans=pp["trans"]) + + +def init_pose_params(kind="stand"): + ball = np.zeros((len(BALL_IDX), 3), np.float32) + bi = {j: i for i, j in enumerate(BALL_IDX)} + ball[bi[JI["shoulder.L"]]] = [0, 0.55, 0] + ball[bi[JI["shoulder.R"]]] = [0, -0.55, 0] + hinge = np.zeros(len(HINGE_IDX), np.float32) + hi = {j: i for i, j in enumerate(HINGE_IDX)} + hinge[hi[JI["elbow.L"]]] = -0.2 + hinge[hi[JI["elbow.R"]]] = -0.2 + hinge[hi[JI["knee.L"]]] = 0.05 + hinge[hi[JI["knee.R"]]] = 0.05 + return dict(ball=jnp.asarray(ball), hinge=jnp.asarray(hinge), trans=jnp.zeros(3, jnp.float32)) + + +def hinge_limit_penalty(h): + hi = {j: i for i, j in enumerate(HINGE_IDX)} + pen = 0.0 + for side in ("L", "R"): + e = h[hi[JI["elbow." + side]]] + k = h[hi[JI["knee." + side]]] + pen += jax.nn.relu(e) ** 2 + jax.nn.relu(-2.6 - e) ** 2 + pen += jax.nn.relu(-k) ** 2 + jax.nn.relu(k - 2.6) ** 2 + return pen + + +def foot_min_z(S, P, R): + (_, _), (ca, cb, ra, rb) = primitives(S, P, R) + # foot cones are the last two entries of each side block; take all cones' lowest points + z = jnp.concatenate([ca[:, 2] - ra, cb[:, 2] - rb]) + return jnp.min(z) + + +def torso_prior(pp): + bi = {j: i for i, j in enumerate(BALL_IDX)} + return sum(jnp.sum(pp["ball"][bi[j]] ** 2) for j in TORSO_JOINTS) + + +def frame_loss(S, pp, alpha, ground_w, pix=None, torso_w=0.0): + """alpha: (5,H,W) target coverage.""" + pose = pose_from_params(pp) + P, R = fk(S, pose) + occ = jnp.stack([render_sil(S, P, R, d, pix=pix) for d in range(5)]) + data = jnp.mean((occ - alpha) ** 2) * 100.0 + reg = 1e-3 * jnp.sum(pp["ball"] ** 2) + 1.0 * hinge_limit_penalty(pp["hinge"]) + torso_w * torso_prior(pp) + mz = foot_min_z(S, P, R) + ground = ground_w * (mz ** 2) * 100.0 + 10.0 * jax.nn.relu(-mz - 0.01) ** 2 * 100 + return data + reg + ground, data + + +def shape_prior(S, S0): + # keep symmetric-ish sane values; weak pull toward init to break degeneracy + pen = 0.0 + for k in POS_KEYS: + pen += 0.02 * jnp.sum((jnp.log(S[k]) - jnp.log(S0[k])) ** 2) + return pen + bounds_penalty(S) + + +def crop_box(alpha_np, margin=8): + """alpha_np (...,H,W) -> (y0,y1,x0,x1) bbox of union of nonzero pixels + margin.""" + m = alpha_np.reshape(-1, *alpha_np.shape[-2:]).max(0) > 0 + ys, xs = np.nonzero(m) + y0, y1 = max(0, ys.min() - margin), min(m.shape[0], ys.max() + 1 + margin) + x0, x1 = max(0, xs.min() - margin), min(m.shape[1], xs.max() + 1 + margin) + return y0, y1, x0, x1 diff --git a/third_party/UO_Model3D_v13/pipeline/foot_z.py b/third_party/UO_Model3D_v13/pipeline/foot_z.py new file mode 100644 index 0000000..254cb1e --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/foot_z.py @@ -0,0 +1,16 @@ +import pickle, numpy as np, jax, jax.numpy as jnp +from posefit_mesh import * +from vd import ACTIONS_PEOPLE +P = pickle.load(open("final_poses_v5.pkl","rb")) +foot_cols=[md["bones"].index(b) for b in md["bones"] if b.split(".")[0]=="foot"] +FV = np.asarray(md["W"])[:,foot_cols].sum(1)>0.5 +pj = jax.jit(posed) +print("rest min z", float(np.asarray(V0)[:,2].min()), "rest foot min z", float(np.asarray(V0)[FV,2].min())) +for a in sorted(P): + p=P[a]["poses"]; F=p["trans"].shape[0] + fz=[];bz=[] + for i in range(F): + X=np.asarray(pj({k:jnp.asarray(v[i]) for k,v in p.items()})) + fz.append(X[FV,2].min()); bz.append(X[:,2].min()) + fz=np.array(fz); bz=np.array(bz) + print(f"{a:2d} {ACTIONS_PEOPLE[a]:24s} foot min {fz.min():+.3f} med {np.median(fz):+.3f} max {fz.max():+.3f} | body min {bz.min():+.3f} trans_z {p['trans'][:,2].min():+.3f}..{p['trans'][:,2].max():+.3f}") diff --git a/third_party/UO_Model3D_v13/pipeline/gross.py b/third_party/UO_Model3D_v13/pipeline/gross.py new file mode 100644 index 0000000..e3f2e21 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/gross.py @@ -0,0 +1,24 @@ +"""Split silhouette errors into 1-px boundary disagreement vs gross (>=2 px deep) errors, per action.""" +import sys, pickle, numpy as np, jax.numpy as jnp +from scipy.ndimage import distance_transform_edt +from posefit_mesh import * +from posefit_mesh import _posed_j +from vd import ACTIONS_PEOPLE +P = pickle.load(open(sys.argv[1], "rb")) +rows = [] +for a in range(35): + T = targets(a); m = T[..., 3] > 127; F = len(T) + hid = (horse_masks(a, F) & ~m) if a in HORSE_OF else np.zeros_like(m) + thin = gross = area = 0; worst = (0, None) + for i in range(F): + X = _posed_j({k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()}) + for d in range(5): + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H) & ~hid[i, d] + s = m[i, d] + red = s & ~mk; blue = mk & ~s + dr = distance_transform_edt(~mk)[red]; db = distance_transform_edt(~s)[blue] + g = (dr > 1.5).sum() + (db > 1.5).sum() + thin += (dr <= 1.5).sum() + (db <= 1.5).sum(); gross += g; area += s.sum() + if g > worst[0]: worst = (g, (i, d)) + rows.append((a, thin / area, gross / area, worst)) + print(f"{a:2d} {ACTIONS_PEOPLE[a]:24s} thin {thin/area:.3f} gross {gross/area:.3f} worst frame/dir {worst[1]} ({worst[0]} px)", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/horse_hull.py b/third_party/UO_Model3D_v13/pipeline/horse_hull.py new file mode 100644 index 0000000..c20e501 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/horse_hull.py @@ -0,0 +1,161 @@ +"""Horse proxy meshes (visual hull from the 5 UO directions of each horse frame), in the rider's coordinate system. +Used as a HOLDOUT when rendering mounted actions: parts of the rider/clothing behind the horse disappear like in UO.""" +import sys, pickle +import numpy as np +from scipy.ndimage import gaussian_filter +from skimage import measure +import jax.numpy as jnp +from body import camera, CANVAS_W, CANVAS_H, ANCHOR_X, ANCHOR_Y +from fit import params_to_shape +sys.path.insert(0, "../vdtool") +import vdtool + +PX_OFF = 0.5 +RES = 0.015 +sf = pickle.load(open("shape_fit.pkl", "rb")) +S = params_to_shape({k: jnp.asarray(v) for k, v in sf["params"]["shape"].items()}, {k: jnp.asarray(v) for k, v in sf["fixed"].items()}) +SC = float(S["scale"]) +CAM = [tuple(np.asarray(c) for c in camera(S, d)) for d in range(5)] +_, horse = vdtool.read_vd("horse200.vd") + +lo = np.array([-0.9, -1.8, -0.05]); hi = np.array([0.9, 1.8, 2.6]) +n = np.ceil((hi - lo) / RES).astype(int) +axes = [lo[i] + (np.arange(n[i]) + 0.5) * RES for i in range(3)] + + +def mask(ha, i, d): + blk = horse[ha * 5 + d] + fr = blk["frames"][i] + rgba = vdtool.frame_rgba(fr, blk["palette"]) + m = np.zeros((CANVAS_H + 200, CANVAS_W + 200), bool) # generous canvas: the horse is big + x0, y0 = ANCHOR_X + 100 - fr["cx"], ANCHOR_Y + 100 - (fr["cy"] + fr["h"]) + m[y0:y0 + fr["h"], x0:x0 + fr["w"]] = rgba[..., 3] > 0 + return m + + +RIDER_FRAME = None # (action, frame) whose evidence carves the proxy; None = all users + + +def _users(ha, i, poses_by_action): + if RIDER_FRAME is not None: + return [RIDER_FRAME] + users = {0: [23], 1: [24], 2: [25, 26, 27, 28, 29]}[ha] + out = [] + for a in users: + if a in poses_by_action: + F = poses_by_action[a]["trans"].shape[0] + out += [(a, k) for k in ([i] if ha in (0, 1) else range(F)) if k < F] + return out + + +def rider_volume(ha, i, poses_by_action): + """Union of the rider's posed body volumes over all mounted frames that use this horse frame (dilated).""" + from scipy.ndimage import binary_dilation, binary_fill_holes + from posefit_mesh import posed + vol = np.zeros(n, bool) + for a, k in _users(ha, i, poses_by_action): + p = poses_by_action[a] + X = np.asarray(posed({q: jnp.asarray(v[k]) for q, v in p.items()})) + idx = np.floor((X - lo) / RES).astype(int) + ok = np.all((idx >= 0) & (idx < n), 1) + shell = np.zeros(n, bool); shell[idx[ok, 0], idx[ok, 1], idx[ok, 2]] = True + shell = binary_dilation(shell, iterations=1) + vol |= binary_fill_holes(shell) + return binary_dilation(vol, iterations=1) + + +def rider_depth_maps(ha, i, poses_by_action): + """For every mounted frame that uses this horse frame: (view, rider sprite mask, rider depth-toward-camera map).""" + from posefit_mesh import posed, md + from targets import targets + tris = np.asarray(md["tris"]) + out = [] + for a, k in _users(ha, i, poses_by_action): + p = poses_by_action[a]; T = targets(a) + X = np.asarray(posed({q: jnp.asarray(v[k]) for q, v in p.items()})) + for d in range(5): + r, u = CAM[d]; f = np.cross(r, u) + P2 = np.stack([ANCHOR_X + PX_OFF + SC * (X @ r), ANCHOR_Y - SC * (X @ u)], 1)[tris] + Z = (X @ f)[tris] + zb = np.full((CANVAS_H, CANVAS_W), -np.inf) + mn = np.floor(P2.min(1)).astype(int); mx = np.ceil(P2.max(1)).astype(int) + A, B, C = P2[:, 0], P2[:, 1], P2[:, 2] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + okt = np.abs(den) > 1e-12 + size = np.clip(mx - mn, 0, 8) + for dy in range(9): + for dx in range(9): + t = np.nonzero(okt & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px = mn[t, 0] + dx; py = mn[t, 1] + dy; cx, cy = px + 0.5, py + 0.5 + l0 = ((B[t, 1] - C[t, 1]) * (cx - C[t, 0]) + (C[t, 0] - B[t, 0]) * (cy - C[t, 1])) / den[t] + l1 = ((C[t, 1] - A[t, 1]) * (cx - C[t, 0]) + (A[t, 0] - C[t, 0]) * (cy - C[t, 1])) / den[t] + l2 = 1 - l0 - l1 + m = (l0 >= -1e-4) & (l1 >= -1e-4) & (l2 >= -1e-4) & (px >= 0) & (py >= 0) & (px < CANVAS_W) & (py < CANVAS_H) + z = l0[m] * Z[t[m], 0] + l1[m] * Z[t[m], 1] + l2[m] * Z[t[m], 2] + np.maximum.at(zb, (py[m], px[m]), z) + out.append((d, T[k, d][..., 3] > 127, zb)) + return out + + +def hull(ha, i, poses_by_action=None, erode=4): + X, Y = np.meshgrid(axes[0], axes[1], indexing="ij") + occ = np.ones(n, bool) + ms = [mask(ha, i, d) for d in range(5)] + for k, z in enumerate(axes[2]): + P = np.stack([X, Y, np.full_like(X, z)], -1) + keep = np.ones(X.shape, bool) + for d in range(5): + r, u = CAM[d] + px = np.floor(ANCHOR_X + 100 + PX_OFF + SC * (P @ r)).astype(int) + py = np.floor(ANCHOR_Y + 100 - SC * (P @ u)).astype(int) + ok = (px >= 0) & (py >= 0) & (px < ms[d].shape[1]) & (py < ms[d].shape[0]) + inside = np.zeros(X.shape, bool) + inside[ok] = ms[d][py[ok], px[ok]] + keep &= inside + occ[:, :, k] = keep + from scipy.ndimage import binary_erosion + if erode > 0: + occ = binary_erosion(occ, iterations=erode) # the hull of 5 same-elevation views is too fat / too tall + elif erode < 0: # fatter than the hull: the exact 2D horse mask clips it at render + from scipy.ndimage import binary_dilation + occ = binary_dilation(occ, iterations=-erode) + if poses_by_action: + occ &= ~rider_volume(ha, i, poses_by_action) # the horse is never where the rider's body is + # where the ORIGINAL rider sprite shows the rider, nothing of the horse is between the camera and the rider + Xg, Yg, Zg = np.meshgrid(axes[0], axes[1], axes[2], indexing="ij") + idx = np.nonzero(occ) + Pv = np.stack([Xg[idx], Yg[idx], Zg[idx]], 1) + carve = np.zeros(len(Pv), bool) + for d, smask, zb in rider_depth_maps(ha, i, poses_by_action): + r, u = CAM[d]; f = np.cross(r, u) + px = np.floor(ANCHOR_X + PX_OFF + SC * (Pv @ r)).astype(int); py = np.floor(ANCHOR_Y - SC * (Pv @ u)).astype(int) + ok = (px >= 0) & (py >= 0) & (px < CANVAS_W) & (py < CANVAS_H) + vis = np.zeros(len(Pv), bool); vis[ok] = smask[py[ok], px[ok]] + zr = np.full(len(Pv), -np.inf); zr[ok] = zb[py[ok], px[ok]] + carve |= vis & (Pv @ f > zr + 0.02) # voxel in front of a visible rider pixel + occ[idx[0][carve], idx[1][carve], idx[2][carve]] = False + print(" carved", int(carve.sum()), "voxels in front of the visible rider", flush=True) + vol = gaussian_filter(occ.astype(np.float32), 1.0) + v, f, _, _ = measure.marching_cubes(vol, 0.5, spacing=(RES, RES, RES)) + return v + lo, f[:, ::-1] + + +poses_by_action = {} +for f_ in sys.argv[1:]: + poses_by_action.update({a: r["poses"] for a, r in pickle.load(open(f_, "rb")).items() if a in range(23, 30)}) +print("rider poses for", sorted(poses_by_action)) +HORSE_OF = {23: 0, 24: 1, 25: 2, 26: 2, 27: 2, 28: 2, 29: 2} +import os +ERODE = int(os.environ.get("UO_ERODE", "-2")) # <0 = dilate; the exact 2D horse mask clips the proxy at render time +HULL_ACTS = [int(x) for x in os.environ.get("UO_HULL_ACTS", "23,24,25,26,27,28,29").split(",")] +HULL_OUT = os.environ.get("UO_HULL_OUT", "horse_hulls.pkl") +out = {} +for a in HULL_ACTS: + F = poses_by_action[a]["trans"].shape[0] + for k in range(F): + RIDER_FRAME = (a, k) + ha = HORSE_OF[a] + v, f = hull(ha, k if ha in (0, 1) else 0, poses_by_action, erode=ERODE) + out[(a, k)] = (v.astype(np.float32), f.astype(np.int32)) + print("rider action", a, "frame", k, "horse action", ha, "faces", len(f), flush=True) +pickle.dump(out, open(HULL_OUT, "wb")) diff --git a/third_party/UO_Model3D_v13/pipeline/identity.py b/third_party/UO_Model3D_v13/pipeline/identity.py new file mode 100644 index 0000000..70e057c --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/identity.py @@ -0,0 +1,43 @@ +import pickle, numpy as np, jax, jax.numpy as jnp, optax +from body import *; from fit import *; from targets import targets +sf=pickle.load(open('shape_fit.pkl','rb')) +S=params_to_shape({k:jnp.asarray(v) for k,v in sf['params']['shape'].items()},{k:jnp.asarray(v) for k,v in sf['fixed'].items()}) +BI={j:i for i,j in enumerate(BALL_IDX)}; HI={j:i for i,j in enumerate(HINGE_IDX)} +MIR=jnp.array([1.0,-1.0,-1.0]) +def swap(pp, balls, hinges): + b,h=pp['ball'],pp['hinge'] + for l in balls: + il,ir=BI[JI[l+'.L']],BI[JI[l+'.R']]; bl,br=b[il],b[ir]; b=b.at[il].set(br*MIR).at[ir].set(bl*MIR) + for l in hinges: + il,ir=HI[JI[l+'.L']],HI[JI[l+'.R']]; hl,hr=h[il],h[ir]; h=h.at[il].set(hr).at[ir].set(hl) + return dict(ball=b,hinge=h,trans=pp['trans']) +VARIANTS={'as_fitted':lambda p:p,'legs_LR':lambda p:swap(p,['hip','ankle'],['knee']), + 'arms_LR':lambda p:swap(p,['shoulder','wrist'],['elbow']), + 'both_LR':lambda p:swap(p,['hip','ankle','shoulder','wrist'],['knee','elbow'])} +def make(a, mounted=False): + T=targets(a); Anp=T[...,3].astype(np.float32)/255 + y0,y1,x0,x1=crop_box(Anp,margin=10); A=jnp.asarray(Anp[...,y0:y1,x0:x1]); pix=PIX[y0:y1,x0:x1] + gw=0.0 if mounted else 1.0 + single=jax.jit(jax.value_and_grad(lambda pp,al: frame_loss(S,pp,al,gw,pix=pix)[0])) + @jax.jit + def views_loss(pp,al): + P,R=fk(S,pose_from_params(pp)) + return jnp.stack([jnp.mean((render_sil(S,P,R,d,pix=pix)-al[d])**2)*100 for d in range(5)]) + def refine(pp,al,n=300): + opt=optax.adam(0.015); st=opt.init(pp) + for _ in range(n): + l,g=single(pp,al); up,st=opt.update(g,st,pp); pp=optax.apply_updates(pp,up) + return pp + return A, refine, views_loss +if __name__=='__main__': + import sys + r1=pickle.load(open('anim_fit_run1.pkl','rb')); r2=pickle.load(open('anim_fit2a.pkl','rb')) + for name,res,a,frames in (('walk',r1,0,[0,5]),('run',r2,2,[0,5])): + A,refine,vl=make(a) + for i in frames: + pp={k:jnp.asarray(v[i]) for k,v in res[a]['poses'].items()} + out=[] + for vn,f in VARIANTS.items(): + q=refine(f(pp),A[i]); l=np.asarray(vl(q,A[i])) + out.append(f"{vn}: front+back {l[0]+l[4]:.2f} all {l.sum():.2f}") + print(name,'frame',i,' | '.join(out), flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/inflate_test.py b/third_party/UO_Model3D_v13/pipeline/inflate_test.py new file mode 100644 index 0000000..b23f71f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/inflate_test.py @@ -0,0 +1,40 @@ +import os, sys, pickle, numpy as np +import jax.numpy as jnp +import posefit_mesh as PM +from posefit_mesh import evaluate, md +fin = pickle.load(open("final_poses.pkl", "rb")) +V = np.asarray(PM.V0) +tris = np.asarray(md["tris"]) +fn = np.cross(V[tris[:, 1]] - V[tris[:, 0]], V[tris[:, 2]] - V[tris[:, 0]]) +N = np.zeros_like(V) +for k in range(3): + np.add.at(N, tris[:, k], fn) +N /= np.maximum(np.linalg.norm(N, axis=1, keepdims=True), 1e-12) +W = np.asarray(md["W"]); b = md["bones"] +foot = W[:, [b.index("foot.L"), b.index("foot.R")]].sum(1) +ACTS = [0, 2, 4, 9, 16, 17, 20, 31, 33] +ank = {} +from posefit_mesh import P0 +from body import JI +for side in ("L", "R"): + ank[side] = np.asarray(P0[JI["ankle." + side]]) +fl = W[:, b.index("foot.L")]; fr = W[:, b.index("foot.R")] +for g, fx in [(0.004, 0), (0.005, 0), (0.007, 0), (0.008, 0), (0.006, 0.10), (0.006, 0.20)]: + Vs = V + N * g + # lengthen feet: push foot vertices forward (-Y) proportionally to how far in front of the ankle they are + for side, wf in (("L", fl), ("R", fr)): + fwd = np.clip(ank[side][1] - V[:, 1], 0, None) + Vs[:, 1] -= fx * fwd * wf + Vn = jnp.asarray(Vs, jnp.float32) + import jax + + def posed_v(pp, Vn=Vn): + pose = PM.pose_from_params(pp) + P, R = PM.fk(PM.S, pose) + Rb = R[PM.BONE_JOINT] + tb = P[PM.BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, PM.P0[PM.BONE_JOINT]) + X = jnp.einsum("bij,vj->vbi", Rb, Vn) + tb[None] + return jnp.einsum("vb,vbi->vi", PM.W, X) + PM._posed_j = jax.jit(posed_v) # fresh function object -> fresh trace with the new rest mesh + r = [evaluate(a, fin[a]["poses"])[0][:, 0].mean() for a in ACTS] + print(f"inflate {g*100:.1f} cm, feet longer by {fx*100:.0f}%: mean worst-IoU {np.mean(r):.4f} ", " ".join(f"{x:.3f}" for x in r), flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/iou_stats.py b/third_party/UO_Model3D_v13/pipeline/iou_stats.py new file mode 100644 index 0000000..fa3006e --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/iou_stats.py @@ -0,0 +1,21 @@ +import pickle, sys, numpy as np, jax, jax.numpy as jnp +from body import *; from fit import *; from targets import targets +from vd import ACTIONS_PEOPLE +sf=pickle.load(open('shape_fit.pkl','rb')) +S=params_to_shape({k:jnp.asarray(v) for k,v in sf['params']['shape'].items()},{k:jnp.asarray(v) for k,v in sf['fixed'].items()}) +res=pickle.load(open(sys.argv[1] if len(sys.argv)>1 else 'anim_fit.pkl','rb')) +@jax.jit +def sil(pp): + P,R=fk(S,pose_from_params(pp)); return jnp.stack([render_sil(S,P,R,d) for d in range(5)]) +out={} +for a in sorted(res): + T=targets(a); F=len(T); worst=[] + for i in range(F): + o=np.asarray(sil({k:jnp.asarray(v[i]) for k,v in res[a]['poses'].items()}))>0.5 + s=T[i][...,3]>127 + iou=[(o[d]&s[d]).sum()/max((o[d]|s[d]).sum(),1) for d in range(5)] + worst.append(min(iou)) + out[a]=worst + flag=' <-- ' + ','.join(str(i) for i,w in enumerate(worst) if w<0.78) if min(worst)<0.78 else '' + print(f"{a:2d} {ACTIONS_PEOPLE[a]:24s} mean-min-IoU {np.mean(worst):.3f} worst {min(worst):.3f}{flag}", flush=True) +pickle.dump(out,open('iou_stats.pkl','wb')) diff --git a/third_party/UO_Model3D_v13/pipeline/jitter.py b/third_party/UO_Model3D_v13/pipeline/jitter.py new file mode 100644 index 0000000..3b2f50a --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/jitter.py @@ -0,0 +1,24 @@ +"""Frame-to-frame rotation changes per joint (degrees); flags spikes where a joint goes A->B->A (jitter).""" +import sys, pickle, numpy as np +from scipy.spatial.transform import Rotation as Rot +from fit import BALL_IDX +from body import JOINTS +from vd import ACTIONS_PEOPLE +P = pickle.load(open(sys.argv[1], "rb")) +names = [JOINTS[j][0] for j in BALL_IDX] +cyc = {0, 1, 2, 3, 23, 24} +for a in sorted(P): + b = P[a]["poses"]["ball"]; F = len(b) + if F < 3: continue + R = [Rot.from_rotvec(b[:, k]) for k in range(b.shape[1])] + worst = [] + for k, n in enumerate(names): + r = R[k] + idx = list(range(F)) + ([0] if a in cyc else []) + step = np.degrees([(r[idx[t + 1]] * r[idx[t]].inv()).magnitude() for t in range(len(idx) - 1)]) + skip = np.degrees([(r[idx[t + 2]] * r[idx[t]].inv()).magnitude() for t in range(len(idx) - 2)]) + # jitter: two big steps whose net change is small + jit = [min(step[t], step[t + 1]) - skip[t] / 2 for t in range(len(skip))] + worst.append((max(jit) if jit else 0, n, int(np.argmax(jit)) + 1 if jit else 0, step.max())) + worst.sort(reverse=True) + print(f"{a:2d} {ACTIONS_PEOPLE[a]:24s}", " ".join(f"{n}@f{f}: jit {j:.0f} (max step {s:.0f})" for j, n, f, s in worst[:3])) diff --git a/third_party/UO_Model3D_v13/pipeline/jitter_fix.py b/third_party/UO_Model3D_v13/pipeline/jitter_fix.py new file mode 100644 index 0000000..259312e --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/jitter_fix.py @@ -0,0 +1,91 @@ +"""Temporal de-jitter: where a joint swings A->B->A between consecutive frames and the silhouettes cannot tell +(true IoU nearly unchanged), replace it by the in-between rotation of its neighbours (brief refit of the frame).""" +import sys, os, pickle, time +import numpy as np +import jax, jax.numpy as jnp, optax +from scipy.spatial.transform import Rotation as Rot, Slerp +from posefit_mesh import * +from posefit_mesh import _posed_j +from fit import BALL_IDX +BASE = sys.argv[sys.argv.index("--base") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +ACTS = [int(a) for k, a in enumerate(sys.argv[1:], 1) if a.isdigit() and sys.argv[k - 1] not in ("--base", "--out")] +THR = float(os.environ.get("UO_JIT_THR", "12")) +base = pickle.load(open(BASE, "rb")) +NAMES = [JOINTS[j][0] for j in BALL_IDX] +CYC = {0, 1, 2, 3, 23, 24} + + +def ious(p, m, hid): + X = _posed_j({k: jnp.asarray(v) for k, v in p.items()}); r = [] + for d in range(5): + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H) & ~hid[d] + r.append((mk & m[d]).sum() / max((mk | m[d]).sum(), 1)) + return np.array(r) + + +def fitter(a): + mounted = jnp.asarray(a in MOUNTED) + + def loss(pp, nb, dto, bpx, bm): + ins, cov = frame_terms(pp, dto, bpx, bm, mounted) + l = 4.0 * ins + cov + 200.0 * limit_penalty(pp) + 0.02 * natural_prior(pp) + return l + 0.3 * (jnp.sum((pp["ball"] - nb["ball"]) ** 2) + jnp.sum((pp["hinge"] - nb["hinge"]) ** 2) + + 20.0 * jnp.sum((pp["trans"] - nb["trans"]) ** 2)) + vg = jax.jit(jax.value_and_grad(loss)) + + def fit(init, dto, bpx, bm, iters=150, lr=0.01): + opt = optax.adam(optax.exponential_decay(lr, iters, 0.3)) + pp = {k: jnp.asarray(v) for k, v in init.items()}; nb = dict(pp); st = opt.init(pp) + for _ in range(iters): + _, g = vg(pp, nb, dto, bpx, bm) + up, st = opt.update(g, st, pp); pp = optax.apply_updates(pp, up) + return {k: np.asarray(v) for k, v in pp.items()}, float(limit_penalty(pp)) + return fit + + +res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} +for a in ACTS: + t0 = time.time() + P = {k: np.array(v) for k, v in base[a]["poses"].items()}; F = P["trans"].shape[0] + if F < 3: + continue + Fr, dto, bpx, bm, m = prepare(a) + hid = (horse_masks(a, F) & ~m) if a in HORSE_OF else np.zeros_like(m) + fit = fitter(a) + changed = [] + for sweep in range(2): + for t in range(F): + if a not in CYC and (t == 0 or t == F - 1): + continue + tp, tn = (t - 1) % F, (t + 1) % F + cand = [] + for k, n in enumerate(NAMES): + if n == "pelvis": + continue + R = Rot.from_rotvec(P["ball"][[tp, t, tn], k]) + s1 = (R[1] * R[0].inv()).magnitude(); s2 = (R[2] * R[1].inv()).magnitude(); sk = (R[2] * R[0].inv()).magnitude() + jit = np.degrees(min(s1, s2) - sk / 2) + if jit > THR: + cand.append((jit, k, n)) + for jit, k, n in sorted(cand, reverse=True): + R = Rot.from_rotvec(P["ball"][[tp, tn], k]) + mid = Slerp([0, 1], R)([0.5]).as_rotvec()[0] + q = {kk: v[t].copy() for kk, v in P.items()}; q["ball"][k] = mid + q2, lim = fit(q, dto[t], bpx[t], bm[t]) + cur = {kk: v[t] for kk, v in P.items()} + i0, i1 = ious(cur, m[t], hid[t]), ious(q2, m[t], hid[t]) + R2 = Rot.from_rotvec(np.stack([P["ball"][tp, k], q2["ball"][k], P["ball"][tn, k]])) + jit2 = np.degrees(min((R2[1] * R2[0].inv()).magnitude(), (R2[2] * R2[1].inv()).magnitude()) - (R2[2] * R2[0].inv()).magnitude() / 2) + ok = lim < 0.01 and i1.mean() > i0.mean() - 0.004 and i1.min() > i0.min() - 0.008 and jit2 < jit - 5 + print(f" a{a} f{t} {n}: jitter {jit:.0f} -> {jit2:.0f} IoU {i0.mean():.3f} -> {i1.mean():.3f} {'ACCEPT' if ok else 'keep'}", flush=True) + if ok: + for kk in P: + P[kk][t] = q2[kk] + changed.append((t, n)) + r, lim = evaluate(a, P, m) + res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} + res[a] = dict(poses=P, iou=r, limits=lim) + pickle.dump(res, open(OUT, "wb")) + r0 = base[a]["iou"] + print(f"action {a:2d} changed {changed} worstIoU {r0[:,0].mean():.3f} -> {r[:,0].mean():.3f} mean {r0[:,1].mean():.3f} -> {r[:,1].mean():.3f} {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/layer_analysis.py b/third_party/UO_Model3D_v13/pipeline/layer_analysis.py new file mode 100644 index 0000000..3c778ba --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/layer_analysis.py @@ -0,0 +1,157 @@ +"""Analysis A: what every wearable layer of the original client looks like next to the body, from the `stand` frames (no Cycles). + + python layer_analysis.py [--files anim,anim2,anim3,anim4,anim5] + +parts.npz comes from `body_part_raster.py ../model/UO_Body_0x190.blend parts.npz --actions 4` (part labels of the 3D body in the stand pose, +canvas 145x133, anchor (75,92)). For every animation of `client/extract/item_animations.json` that has a layer < 25 (and frames in the listed files; default: all of anim, anim2, anim3, anim4, anim5 - the wearable animations in them are the game's originals) +the 5 directions of action 4 (stand), frame 0, are put on a 256x256 canvas (anchor 128,192) next to the original body 400 and measured: + + * z range of the item in the rest pose (m, ground = 0): rows -> z = 0.07 - row / (36 cos 28.4557 deg), mean of the 5 directions (the formula of + `uo_import_item.py` EXTENTS: bottom edge of the lowest and top edge of the highest pixel row); + * cover[part]: share of the pixels of a body part (3D body, nearest part to every body pixel of the ORIGINAL silhouette) that the item covers; + * out[part]: distance (px, 1 px = 1/36 m = 2.78 cm) of every item pixel OUTSIDE the original body silhouette to that silhouette, grouped by the body part nearest + to the pixel: n pixels, p50, p90, max. It is the only place where the thickness of the item can be read from a flat sprite (inside the silhouette the + body is hidden by the item), so it is a lower bound of the standoff of the item from the skin, mostly at arms, legs, hem and neck. +Left / right parts are merged; clavicle, spine, pelvis, chest are `torso`. +""" +import json, mmap, os, struct, sys +import numpy as np +from scipy import ndimage + +HERE = os.path.dirname(os.path.abspath(__file__)) +CW, CH, ANCH = 256, 256, (128, 192) +PXM = 36.0 +COS = np.cos(np.radians(28.4557)) +END = 0x7FFF7FFF +STAND = 4 +GROUP = {"chest": "torso", "spine": "torso", "pelvis": "torso", "clavicle": "torso", "upper_arm": "upper_arm", "forearm": "forearm", "hand": "hand", + "thigh": "thigh", "shin": "shin", "foot": "foot", "head": "head", "neck": "neck"} +ORDER = ["head", "neck", "torso", "upper_arm", "forearm", "hand", "thigh", "shin", "foot"] + + +class Files: + def __init__(self, src): + self.src, self.cache = src, {} + + def get(self, tag): + if tag not in self.cache: + ip, mp = os.path.join(self.src, tag + ".idx"), os.path.join(self.src, tag + ".mul") + if not (os.path.exists(ip) and os.path.exists(mp)): + self.cache[tag] = None + else: + with open(mp, "rb") as f: + self.cache[tag] = (open(ip, "rb").read(), mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ)) + return self.cache[tag] + + +def stand_mask(fl, tag, body, d): + """opaque mask of frame 0 of (stand, dir d) of people / equipment id `body` on the 256x256 canvas, or None""" + f = fl.get(tag) + if f is None: + return None + idx, mm = f + e = 35000 + (body - 400) * 175 + STAND * 5 + d + if 12 * (e + 1) > len(idx): + return None + look, length, _ = struct.unpack_from(" len(mm): + return None + cnt, = struct.unpack_from("> 22) & 0x3FF + dy = (hdr >> 12) & 0x3FF + dx = dx - 0x400 if dx & 0x200 else dx + dy = dy - 0x400 if dy & 0x200 else dy + x, y = ANCH[0] + dx, ANCH[1] + dy # (dx, dy) are relative to the anchor + if 0 <= y < CH: + m[y, max(x, 0):max(min(x + n, CW), 0)] = True + p += n + return m + + +def main(): + args = sys.argv[1:] + files = ["anim", "anim2", "anim3", "anim4", "anim5"] + if "--files" in args: + i = args.index("--files") + files = args[i + 1].split(",") + del args[i:i + 2] + src, parts_npz, out = args + z = np.load(parts_npz) + names = [str(n) for n in z["parts"]] + gname = [GROUP[n.split(".")[0]] for n in names] + lab_small = z["lab"] # (5, 133, 145), anchor (75, 92) + dirs = {int(k[1]): i for i, k in enumerate(z["key"]) if int(k[0]) == STAND and int(k[2]) == 0} + fl = Files(src) + meta = json.load(open(os.path.join(HERE, "..", "client", "extract", "item_animations.json"))) + layer_names = meta["layers"] + + body_mask, plab, near_lab, dist_out = {}, {}, {}, {} + for d in range(5): + B = stand_mask(fl, "anim", 400, d) + L = np.full((CH, CW), -1, np.int16) + s = lab_small[dirs[d]] + L[ANCH[1] - 92:ANCH[1] - 92 + 133, ANCH[0] - 75:ANCH[0] - 75 + 145] = s + G = np.full(L.shape, -1, np.int16) + for pi, g in enumerate(gname): + G[L == pi] = ORDER.index(g) + # nearest 3D part label for every pixel of the canvas + _, (iy, ix) = ndimage.distance_transform_edt(G < 0, return_indices=True) + body_mask[d], plab[d], near_lab[d] = B, G, G[iy, ix] + dist_out[d] = ndimage.distance_transform_edt(~B) # distance to the original silhouette (0 inside) + + res = {} + for key, v in meta["animations"].items(): + lays = [l for l in v["layers"] if l < 25] + tag, _, lid = v["src"].partition(":") + if not lays or not v["frames"] or tag not in files: + continue + ms = [stand_mask(fl, tag, int(lid), d) for d in range(5)] + if any(m is None or not m.any() for m in ms): + continue + zlo = zhi = 0.0 + cover = {g: [] for g in ORDER} + outd = {g: [] for g in ORDER} + for d, m in enumerate(ms): + rows = np.nonzero(m.any(1))[0] + zhi += 0.07 - (rows[0] - ANCH[1]) / (PXM * COS) + zlo += 0.07 - (rows[-1] + 1 - ANCH[1]) / (PXM * COS) + for gi, g in enumerate(ORDER): + sel = (plab[d] == gi) | ((near_lab[d] == gi) & body_mask[d]) + if sel.sum(): + cover[g].append((m & sel).sum() / sel.sum()) + o = m & ~body_mask[d] + for gi, g in enumerate(ORDER): + dd = dist_out[d][o & (near_lab[d] == gi)] + if dd.size: + outd[g].append(dd) + rec = dict(src=v["src"], items=[n for _, n in v["items"]][:3], layers=[layer_names[str(l)] for l in lays], + zlo=round(zlo / 5, 3), zhi=round(zhi / 5, 3), + cover={g: round(float(np.mean(c)), 3) for g, c in cover.items() if c}, + out={}) + for g, ds in outd.items(): + if not ds: + continue + dd = np.concatenate(ds) + rec["out"][g] = dict(n=int(len(dd) / 5), p50=round(float(np.percentile(dd, 50)), 2), p90=round(float(np.percentile(dd, 90)), 2), + max=round(float(dd.max()), 2)) + res[key] = rec + json.dump(dict(canvas=[CW, CH], anchor=ANCH, files=files, animations=res), open(out, "w"), indent=1) + print("%d animations measured" % len(res)) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/layer_analysis_report.py b/third_party/UO_Model3D_v13/pipeline/layer_analysis_report.py new file mode 100644 index 0000000..7c1b2cc --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/layer_analysis_report.py @@ -0,0 +1,34 @@ +"""Per-layer table (markdown) from layer_analysis.py output. python layer_analysis_report.py layer_analysis.json out.md""" +import json, sys +import numpy as np +from layer_analysis import ORDER + +PX_CM = 100 / 36.0 +d = json.load(open(sys.argv[1]))["animations"] +by = {} +for k, r in d.items(): + for l in r["layers"]: + by.setdefault(l, []).append(r) +L = ["# Warstwy ubieralne z klienta: zasięg i odstęp od ciała (poza `stand`, 5 kierunków)", "", + "Źródło: `pipeline/layer_analysis.py` (anim, anim2, anim3, anim4, anim5; %d animacji). 1 px = %.2f cm. Szczegóły: `client/extract/layer_analysis.json`." % (len(d), PX_CM), "", + "## Zasięg wysokości w pozie spoczynkowej (m, podłoga = 0)", "", + "| warstwa | animacji | dół: min / mediana / max | góra: min / mediana / max | przykłady |", "|---|---|---|---|---|"] +for l, rs in sorted(by.items()): + lo, hi = np.array([r["zlo"] for r in rs]), np.array([r["zhi"] for r in rs]) + ex = ", ".join(sorted({n for r in rs for n in r["items"]})[:3]) + L.append("| %s | %d | %.2f / %.2f / %.2f | %.2f / %.2f / %.2f | %s |" % (l, len(rs), lo.min(), np.median(lo), lo.max(), hi.min(), np.median(hi), hi.max(), ex)) +L += ["", "## Pokrycie części ciała (mediana po animacjach, udział pikseli części ciała zakrytych przez przedmiot)", "", + "| warstwa | " + " | ".join(ORDER) + " |", "|---|" + "---|" * len(ORDER)] +for l, rs in sorted(by.items()): + L.append("| %s | " % l + " | ".join("%.2f" % np.median([r["cover"].get(g, 0) for r in rs]) for g in ORDER) + " |") +L += ["", "## Wystawanie poza sylwetkę oryginalnego ciała (cm; p90 odległości pikseli przedmiotu od sylwetki, mediana po animacjach; tylko animacje z ≥ 5 pikselami poza sylwetką na kierunek)", "", + "To dolne oszacowanie odstępu od skóry (wewnątrz sylwetki ciało jest zasłonięte). `—` = przedmiot prawie nie wystaje.", "", + "| warstwa | " + " | ".join(ORDER) + " |", "|---|" + "---|" * len(ORDER)] +for l, rs in sorted(by.items()): + cells = [] + for g in ORDER: + v = [r["out"][g]["p90"] for r in rs if g in r["out"] and r["out"][g]["n"] >= 5] + cells.append("%.1f" % (np.median(v) * PX_CM) if len(v) >= 2 else "—") + L.append("| %s | " % l + " | ".join(cells) + " |") +open(sys.argv[2], "w").write("\n".join(L) + "\n") +print("\n".join(L)) diff --git a/third_party/UO_Model3D_v13/pipeline/lean_probe.py b/third_party/UO_Model3D_v13/pipeline/lean_probe.py new file mode 100644 index 0000000..2684398 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/lean_probe.py @@ -0,0 +1,25 @@ +import sys, pickle, numpy as np, jax.numpy as jnp +from scipy.spatial.transform import Rotation as Rot +from posefit_mesh import * +from posefit_mesh import _posed_j +P = pickle.load(open(sys.argv[1], "rb")); a, i = int(sys.argv[2]), int(sys.argv[3]) +T = targets(a); m = T[..., 3] > 127 +p0 = {k: np.asarray(v[i]) for k, v in P[a]["poses"].items()} +def iou(p): + X = _posed_j({k: jnp.asarray(v) for k, v in p.items()}); r = [] + for d in range(5): + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H); s = m[i, d] + r.append((mk & s).sum() / max((mk | s).sum(), 1)) + return np.round(r, 3), np.mean(r) +def rot(p, joint, axis, deg): + q = {k: v.copy() for k, v in p.items()} + q["ball"][BI[JI[joint]]] = (Rot.from_euler(axis, deg, degrees=True) * Rot.from_rotvec(q["ball"][BI[JI[joint]]])).as_rotvec() + return q +print("base", iou(p0)) +for ax in "xyz": + for j in ("pelvis", "spine", "chest"): + for deg in (-8, -4, 4, 8): + r, mn = iou(rot(p0, j, ax, deg)) + print(ax, j, deg, r, round(mn, 4)) +for dx in (-0.03, -0.015, 0.015, 0.03): + q = {k: v.copy() for k, v in p0.items()}; q["trans"][0] += dx; print("trans x", dx, iou(q)) diff --git a/third_party/UO_Model3D_v13/pipeline/light_data.py b/third_party/UO_Model3D_v13/pipeline/light_data.py new file mode 100644 index 0000000..98fdb83 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/light_data.py @@ -0,0 +1,48 @@ +"""Joins the per-pixel geometry of the 3D body (light_raster.py) with the original UO body frames: one table of pixels that both cover (outline excluded). + + from light_data import load; D = load(["part_0.npz", ...]) +D: dict of arrays (one entry per pixel): action, dir, frame, y, x, N (3), P (3), uv (2), part, lit, ao, rgb (3 uint8, the ORIGINAL pixel), edge (distance in px to the +original silhouette, 1 = outline pixel), plus `parts` and `L`. +""" +import json, os +import numpy as np +from PIL import Image +from scipy import ndimage + +HERE = os.path.dirname(os.path.abspath(__file__)) +ORIG = os.path.join(HERE, "..", "client", "body_0x190_frames") + + +def load(files): + meta = json.load(open(os.path.join(ORIG, "meta.json"))) + names = {b["action"]: "%02d_%s" % (b["action"], b["name"]) for b in meta["blocks"]} + files_of = {(b["action"], b["dir"]): [f["file"] for f in b["frames"]] for b in meta["blocks"]} + out = {k: [] for k in ("action", "dir", "frame", "y", "x", "N", "P", "uv", "part", "lit", "ao", "rgb", "edge")} + parts, L = None, None + for fn in files: + z = np.load(fn) + parts, L = z["parts"], z["L"] + key, fr = z["key"], z["frame"] + starts = np.searchsorted(fr, np.arange(len(key))) + ends = np.searchsorted(fr, np.arange(len(key)), side="right") + for k, (a, d, i) in enumerate(key): + fl = files_of.get((int(a), int(d))) + if not fl or i >= len(fl): + continue + im = np.array(Image.open(os.path.join(ORIG, "frames", names[int(a)], "dir%d" % d, fl[i])).convert("RGBA")) + m = im[..., 3] > 0 + if not m.any(): + continue + dist = ndimage.distance_transform_cdt(m, metric="taxicab") + s = slice(starts[k], ends[k]) + y, x = z["y"][s].astype(int), z["x"][s].astype(int) + ok = m[y, x] + for name, arr in (("y", y), ("x", x), ("N", z["N"][s].astype(np.float32)), ("P", z["P"][s].astype(np.float32)), ("uv", z["uv"][s].astype(np.float32)), + ("part", z["part"][s]), ("lit", z["lit"][s]), ("ao", z["ao"][s])): + out[name].append(arr[ok]) + out["rgb"].append(im[y[ok], x[ok], :3]); out["edge"].append(dist[y[ok], x[ok]].astype(np.int8)) + n = int(ok.sum()) + out["action"].append(np.full(n, a, np.int8)); out["dir"].append(np.full(n, d, np.int8)); out["frame"].append(np.full(n, i, np.int16)) + D = {k: np.concatenate(v) for k, v in out.items()} + D["parts"], D["L"] = parts, L + return D diff --git a/third_party/UO_Model3D_v13/pipeline/light_fit.py b/third_party/UO_Model3D_v13/pipeline/light_fit.py new file mode 100644 index 0000000..99a2876 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/light_fit.py @@ -0,0 +1,116 @@ +"""Light and shadow of the ORIGINAL UO body frames against the 3D body (880 frames of actions 0-22, 30-34, all 5 directions, 495 k pixels). + + python light_raster.py ../model/UO_Body_0x190.blend lr/part_N.npz --actions ... (4 runs, see SESSION_HANDOFF.md session 10) + python -c "import light_data,numpy as np,glob; np.savez('light_table.npz', **light_data.load(sorted(glob.glob('lr/part_*.npz'))))" + python light_fit.py light_table.npz + +Model: light(pixel) = albedo[texel of the UV] * S(pixel), the albedo per texel (96x96 of the UV square) profiled out; S from the normal of the 3D body and the light. +Prints: Lambert in sRGB vs linear light, free light direction (all frames and per direction), model variants (ambient, exponent, wrap, hemisphere, AO, self-shadow), +the residual by self-shadow flag, ambient openness, cosine and body part. +""" +import numpy as np +from scipy import optimize +import sys +D=dict(np.load(sys.argv[1])) +dec=lambda v:np.where(v<=0.04045,v/12.92,((v+0.055)/1.055)**2.4) +m=D['edge']>=2 +N=D['N'][m].astype(float); uv=D['uv'][m]; lit=D['lit'][m]; ao=D['ao'][m]; rgb=D['rgb'][m].astype(float) +lum8=rgb.mean(1) +tex=(np.clip(uv[:,0],0,.999)*96).astype(int)*96+(np.clip(uv[:,1],0,.999)*96).astype(int) # 96x96 texels +ut,inv,cnt=np.unique(tex,return_inverse=True,return_counts=True) +print('pixels',m.sum(),'texels',len(ut),'median samples/texel',np.median(cnt)) +def sph(p): + th,ph=p[0],p[1]; return np.array([np.sin(th)*np.cos(ph),np.sin(th)*np.sin(ph),np.cos(th)]) +def resid(y,S): + # profile out the albedo per texel + num=np.bincount(inv,y*S); den=np.bincount(inv,S*S); a=num/np.maximum(den,1e-12) + return y-a[inv]*S +def run(name,dom,model,p0,bounds=None): + y=dom(lum8) + f=lambda p: resid(y,model(p)) + r=optimize.least_squares(f,p0,bounds=bounds if bounds else (-np.inf,np.inf)) + rms=np.sqrt(np.mean(r.fun**2)); print("%-34s %-6s rms %.4f params %s"%(name,dom.__name__,rms,np.round(r.x,4))); return r +srgb=lambda v:v/255.0 +srgb.__name__="srgb" +lin=lambda v:dec(v/255.0) +lin.__name__="linear" +L0=np.array([0.0012,-0.7572,0.6532]); th0=np.arccos(L0[2]); ph0=np.arctan2(L0[1],L0[0]) +lamb=lambda p: p[2]+(1-p[2])*np.maximum(N@sph(p),0) +fixed=lambda p: 0.0798+0.9202*np.maximum(N@L0,0) +for dom in (srgb,lin): + y=dom(lum8); print("%-34s %-6s rms %.4f"%("current UO_Look (fixed L, amb .0798)",dom.__name__,np.sqrt(np.mean(resid(y,fixed(None))**2)))) + run("free L + ambient",dom,lamb,[th0,ph0,0.08],([0,-10,0],[np.pi,10,1])) +print("---- normalised: share of the variance (after the per-texel albedo) that the light explains") +for dom in (srgb,lin): + y=dom(lum8); base=np.sqrt(np.mean(resid(y,np.ones_like(y))**2)) + cur=np.sqrt(np.mean(resid(y,fixed(None))**2)) + print(dom.__name__,"albedo only rms %.4f | current light rms %.4f | explained %.1f%%"%(base,cur,100*(1-cur**2/base**2))) +# per direction free light (linear domain) +print("---- per direction (linear domain): best L, ambient, rms") +y=lin(lum8) +for d in range(5): + sel=D['dir'][m]==d + inv_d=inv # same texel ids; fit with subset + def fd(p): + S_=p[2]+(1-p[2])*np.maximum(N[sel]@sph(p),0); num=np.bincount(inv[sel],y[sel]*S_,minlength=len(ut)); den=np.bincount(inv[sel],S_*S_,minlength=len(ut)) + return y[sel]-(num/np.maximum(den,1e-12))[inv[sel]]*S_ + r=optimize.least_squares(fd,[th0,ph0,0.08],bounds=([0,-10,0],[np.pi,10,1])) + print("dir",d,"L",np.round(sph(r.x),3),"amb %.3f"%r.x[2],"rms %.4f"%np.sqrt(np.mean(r.fun**2))) + +y=lin(lum8) +c=np.maximum(N@L0,0) +Sbase=0.0798+0.9202*c +def rms(S_): return np.sqrt(np.mean(resid(y,S_)**2)) +print("base (current light) rms %.4f"%rms(Sbase)) +# a per texel from base, ratio per pixel +num=np.bincount(inv,y*Sbase); den=np.bincount(inv,Sbase**2); a=num/den; pred=a[inv]*Sbase +ratio=y/np.maximum(pred,1e-4) +print("---- shadows: ratio original/predicted (median) by self-shadow flag, c bin") +for nm,sel in (("lit (ray to light free)",lit==1),("shadowed by the body itself",lit==0)): + print(" %-30s n %6d median ratio %.3f"%(nm,sel.sum(),np.median(ratio[sel]))) +has_ao=ao<255 +aoq=ao.astype(float)/255 +print("---- ambient occlusion (8 rays, 0.4 m; only every 3rd frame), ratio by openness") +am=np.arange(0,256) +for lo,hi in ((0,.5),(.5,.75),(.75,.9),(.9,1.0001)): + sel=(aoq>=lo)&(aoq=lo)&(aoq=lo)&(c3000: print(" %-12s n %6d ratio median %.3f rel.rms %.3f"%(D['parts'][p],sel.sum(),np.median(ratio[sel]),np.std(ratio[sel]))) +print("---- self-shadow strength: S = amb + (1-amb)*c*(1 if lit else s)") +for s in (0.0,0.2,0.4,0.5,0.6,0.8,1.0): + print(" s=%.1f rms %.4f"%(s,rms(0.0798+0.9202*c*np.where(lit==1,1.0,s)))) +sh=lit==0 +print("shadowed pixels by part:",{str(D['parts'][p]):int(((D['part'][m]==p)&sh).sum()) for p in range(len(D['parts'])) if ((D['part'][m]==p)&sh).sum()>500}) +print("share of pixels much darker than predicted (ratio<0.6):",round(float((ratio<0.6).mean()),3),"; of those flagged self-shadowed:",round(float(sh[ratio<0.6].mean()),3), "(base rate %.3f)"%sh.mean()) +dk=ratio<0.45 +print("pixels very dark (ratio<0.45) n %d: lit-flag share %.3f"%(dk.sum(),(~sh[dk]).mean())) +# shadowed share by action +for a in sorted(set(D['action'][m].tolist())): + s_=D['action'][m]==a + print(" action %2d shadowed %.3f ratio_median_in_shadow %.2f"%(a,sh[s_].mean(), np.median(ratio[s_&sh]) if (s_&sh).sum()>20 else np.nan), end=";" if a%3 else "\n") diff --git a/third_party/UO_Model3D_v13/pipeline/light_items.py b/third_party/UO_Model3D_v13/pipeline/light_items.py new file mode 100644 index 0000000..0ca3384 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/light_items.py @@ -0,0 +1,167 @@ +"""Light / shadow statistics of every wearable animation of the client against the lighting of the 3D body. + + python light_items.py [--stride 2] [--procs 4] + +light_table.npz: the output of `light_data.load` saved with np.savez (pixels of the 3D body that the ORIGINAL body frames also cover: normal, self-shadow flag...). +For every people / equipment animation of client/extract/item_animations.json (layers < 25, in anim..anim5) and every frame of the body table (every `stride`-th +frame; mounted actions are not in the table) the item's pixels that lie on a body-model pixel are taken. The item hugs the body (shirt, armour, trousers...), so the +normal of the BODY at that pixel stands for the normal of the item; loose items (robe, cloak, hair, wings) are poorer proxies - the result is a statistic over +hundreds of animations, not a measurement of one. Per animation (linear light = sRGB decoded, mean of R, G, B): + n pixels used + r2_lam share of the variance of the item's light explained by A * (0.0798 + 0.9202 * max(n.L, 0)) (A fitted; the item's albedo is taken as uniform) + A that albedo + ks, r2_spec the same with + ks * max(n.L, 0)^16 (a metal highlight): ks (in linear light) and the new share explained + hi99, med 99th percentile and median of the item's light; top_c: mean n.L of the brightest 1 % of the pixels + curve median light in the bins of n.L [0, .3, .5, .6, .7, .8, .9, .95, 1] (Lambert: rises about 1.9x from n.L 0.4 to 1) + shadow median of light / (A * S) for pixels the body shadows itself (ray to the UO light blocked) and for the others (lit), with the counts +""" +import json, mmap, os, struct, sys +from multiprocessing import Pool + +import numpy as np + +HERE = os.path.dirname(os.path.abspath(__file__)) +CW, CH, ANCH = 145, 133, (75, 92) +END = 0x7FFF7FFF +dec = lambda v: np.where(v <= 0.04045, v / 12.92, ((v + 0.055) / 1.055) ** 2.4) +_G = {} + + +def init(src, table, stride): + _G["src"], _G["stride"] = src, stride + z = np.load(table) + keep = ("action", "dir", "frame", "y", "x", "N", "lit", "ao", "part") + D = {k: z[k] for k in keep} + order = np.lexsort((D["frame"], D["dir"], D["action"])) + D = {k: v[order] for k, v in D.items()} + code = D["action"].astype(np.int64) * 100000 + D["dir"].astype(np.int64) * 1000 + D["frame"] + u, st = np.unique(code, return_index=True) + en = np.r_[st[1:], len(code)] + _G["D"], _G["frames"] = D, [(int(c // 100000), int(c // 1000 % 100), int(c % 1000), s, e) for c, s, e in zip(u, st, en)] + _G["L"] = np.array([0.00124641, -0.75721306, 0.65316677]) + _G["files"] = {} + + +def open_files(tag): + if tag not in _G["files"]: + ip, mp = os.path.join(_G["src"], tag + ".idx"), os.path.join(_G["src"], tag + ".mul") + if os.path.exists(ip) and os.path.exists(mp): + fh = open(mp, "rb") # kept open for the life of the mmap + _G["files"][tag] = (open(ip, "rb").read(), mmap.mmap(fh.fileno(), 0, access=mmap.ACCESS_READ), fh) + else: + _G["files"][tag] = None + return _G["files"][tag] + + +def decode(idx, mm, body, action, d, i): + """RGB (CH, CW, 3) uint8 and mask of frame i of (action, dir d) of people / equipment id `body` on the canvas of the original body frames, or None""" + e = 35000 + (body - 400) * 175 + action * 5 + d + if 12 * (e + 1) > len(idx): + return None + look, length, _ = struct.unpack_from(" len(mm): + return None + cnt, = struct.unpack_from("= cnt: + return None + pal = np.frombuffer(mm, "> 10) & 31) * 255 // 31, ((pal >> 5) & 31) * 255 // 31, (pal & 31) * 255 // 31], 1).astype(np.uint8) + off, = struct.unpack_from("> 22) & 0x3FF + dy = (hdr >> 12) & 0x3FF + dx = dx - 0x400 if dx & 0x200 else dx + dy = dy - 0x400 if dy & 0x200 else dy + x, y = ANCH[0] + dx, ANCH[1] + dy + if 0 <= y < CH and n > 0: + x0, x1 = max(x, 0), min(x + n, CW) + if x1 > x0: + idxs = np.frombuffer(mm, np.uint8, n, p)[x0 - x:x1 - x] + img[y, x0:x1] = lut[idxs]; m[y, x0:x1] = True + p += n + return img, m + + +def analyse(job): + key, src, name, layers = job + tag, _, lid = src.partition(":") + f = open_files(tag) + if f is None: + return key, None + D, L = _G["D"], _G["L"] + lum, cc, lit, ao = [], [], [], [] + for k, (a, d, i, s, e) in enumerate(_G["frames"]): + if k % _G["stride"]: + continue + r = decode(f[0], f[1], int(lid), a, d, i) + if r is None: + continue + img, m = r + y, x = D["y"][s:e], D["x"][s:e] + sel = m[y, x] + if not sel.any(): + continue + rgb = img[y[sel], x[sel]].astype(np.float64) / 255 + lum.append(dec(rgb).mean(1)); cc.append(np.maximum(D["N"][s:e][sel] @ L, 0)); lit.append(D["lit"][s:e][sel]); ao.append(D["ao"][s:e][sel]) + if not lum or sum(len(v) for v in lum) < 300: + return key, None + y_, c, lit, ao = np.concatenate(lum), np.concatenate(cc), np.concatenate(lit), np.concatenate(ao) + S = 0.0798 + 0.9202 * c + A = float((y_ * S).sum() / (S * S).sum()); res = y_ - A * S + tot = float(((y_ - y_.mean()) ** 2).sum()) + X = np.stack([S, c ** 16], 1); coef, *_ = np.linalg.lstsq(X, y_, rcond=None) + res2 = y_ - X @ coef + hi = y_ >= np.percentile(y_, 99) + sh = lit == 0 + ratio = y_ / np.maximum(A * S, 1e-4) + edges = np.array([0, 0.3, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, 1.01]) + b = np.digitize(c, edges) - 1 + curve = [float(np.median(y_[b == k])) if (b == k).sum() >= 100 else None for k in range(len(edges) - 1)] # median light per bin of n.L + out = dict(name=name, curve=curve, layers=layers, n=int(len(y_)), r2_lam=1 - float((res ** 2).sum()) / tot if tot > 0 else 0.0, A=A, + ks=float(coef[1]), A2=float(coef[0]), r2_spec=1 - float((res2 ** 2).sum()) / tot if tot > 0 else 0.0, + med=float(np.median(y_)), hi99=float(np.percentile(y_, 99)), top_c=float(c[hi].mean()), + shadow=dict(n_shadow=int(sh.sum()), n_lit=int((~sh).sum()), + r_shadow=float(np.median(ratio[sh])) if sh.sum() >= 50 else None, r_lit=float(np.median(ratio[~sh])) if (~sh).sum() >= 50 else None)) + return key, out + + +def main(): + args = sys.argv[1:] + stride, procs = 2, 4 + for fl, nm in (("--stride", "stride"), ("--procs", "procs")): + if fl in args: + i = args.index(fl); v = int(args[i + 1]); del args[i:i + 2] + if nm == "stride": stride = v + else: procs = v + src, table, out = args + meta = json.load(open(os.path.join(HERE, "..", "client", "extract", "item_animations.json"))) + names = meta["layers"] + jobs = [] + for key, v in meta["animations"].items(): + lays = [l for l in v["layers"] if l < 25] + if not lays: + continue + nm = "; ".join(it[1] for it in v["items"][:3]) + jobs.append((key, v["src"], nm, [names.get(str(l), str(l)) for l in lays])) + with Pool(procs, initializer=init, initargs=(src, table, stride)) as pool: + res = {} + for n, (k, r) in enumerate(pool.imap_unordered(analyse, jobs, chunksize=4)): + if r is not None: + res[k] = r + if n % 40 == 0: + print(n, "/", len(jobs), flush=True) + json.dump(res, open(out, "w"), indent=0) + print("animations analysed:", len(res)) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/light_raster.py b/third_party/UO_Model3D_v13/pipeline/light_raster.py new file mode 100644 index 0000000..1b24882 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/light_raster.py @@ -0,0 +1,157 @@ +"""Per-pixel geometry of the pure 3D body for every UO frame, for the light / shadow analysis (no Cycles: pixel-centre rasteriser + BVH rays). + + python light_raster.py ../model/UO_Body_0x190.blend OUT.npz [--actions 0,1,2] [--ao-every 3] + +Canvas of the ORIGINAL body frames (145x133, anchor (75,92), 36 px/m), as body_part_raster.py. For every covered pixel of every frame (mounted +actions 23-29 are left out: the horse proxy hides parts of the body) it stores, in world space (z up, camera at -y): + frame index into `key` (action, direction, frame) y, x pixel + N smooth normal (3) P position (3, m) uv texture coordinate (2) part dominant bone group (int8, `parts`) + lit 1 = the ray from P (+ 3 mm along N) towards the UO light leaves the body without hitting it, 0 = the body shadows itself there + ao share of 8 hemisphere rays of 0.4 m that leave the body (255 = open); only every --ao-every-th frame, 255 elsewhere + L the UO light of the file (node group UO_Look, world space) +`analysis_light.py` joins this with the original frames. Needs: pip install numpy "bpy==4.2.*". +""" +import sys, os +import numpy as np +import bpy +from mathutils import Vector +from mathutils.bvhtree import BVHTree + +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) +import body_part_raster as bpr + +CW, CH, CANCH, STEP = bpr.CW, bpr.CH, bpr.CANCH, bpr.STEP + + +def raster_full(ob, dg, Pm, Vm): + """per pixel: triangle index (-1 none), barycentric weights of corners 0 and 1, plus the evaluated vertex positions / normals / triangles""" + ev = ob.evaluated_get(dg); m2 = ev.to_mesh() + co = np.empty(len(m2.vertices) * 3, np.float32); m2.vertices.foreach_get("co", co); co = co.reshape(-1, 3) + vn = np.empty(len(m2.vertices) * 3, np.float32); m2.vertices.foreach_get("normal", vn); vn = vn.reshape(-1, 3) + m2.calc_loop_triangles() + tri = np.empty(len(m2.loop_triangles) * 3, np.int32); m2.loop_triangles.foreach_get("vertices", tri); tri = tri.reshape(-1, 3) + Mw = np.array(ev.matrix_world); ev.to_mesh_clear() + cow = (np.c_[co, np.ones(len(co))] @ Mw.T)[:, :3]; vnw = vn @ Mw[:3, :3].T + hv = np.c_[cow, np.ones(len(co))] @ Vm.T + h = hv @ Pm.T; ndc = h[:, :2] / h[:, 3:4] + P = np.stack([(ndc[:, 0] + 1) * 0.5 * CW, (1 - ndc[:, 1]) * 0.5 * CH], 1)[tri] + Z = -hv[:, 2][tri] + tid = np.full((CH, CW), -1, np.int32); depth = np.full((CH, CW), np.inf); B0 = np.zeros((CH, CW)); B1 = np.zeros((CH, CW)) + mn = np.floor(P.min(1)).astype(int); mx = np.ceil(P.max(1)).astype(int) + A, B, C = P[:, 0], P[:, 1], P[:, 2] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + ok = np.abs(den) > 1e-12; size = np.clip(mx - mn, 0, 16) + for dy in range(int(size[:, 1].max(initial=0)) + 1): + for dx in range(int(size[:, 0].max(initial=0)) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px_ = mn[t, 0] + dx; py_ = mn[t, 1] + dy; cx, cy = px_ + 0.5, py_ + 0.5 + l0 = ((B[t, 1] - C[t, 1]) * (cx - C[t, 0]) + (C[t, 0] - B[t, 0]) * (cy - C[t, 1])) / den[t] + l1 = ((C[t, 1] - A[t, 1]) * (cx - C[t, 0]) + (A[t, 0] - C[t, 0]) * (cy - C[t, 1])) / den[t] + kk = (l0 >= -1e-4) & (l1 >= -1e-4) & (1 - l0 - l1 >= -1e-4) & (px_ >= 0) & (py_ >= 0) & (px_ < CW) & (py_ < CH) + z = l0[kk] * Z[t[kk], 0] + l1[kk] * Z[t[kk], 1] + (1 - l0[kk] - l1[kk]) * Z[t[kk], 2] + tt, yy, xx, a0, a1 = t[kk], py_[kk], px_[kk], l0[kk], l1[kk] + o = np.argsort(-z) + o = o[z[o] < depth[yy[o], xx[o]]] + depth[yy[o], xx[o]] = z[o]; tid[yy[o], xx[o]] = tt[o]; B0[yy[o], xx[o]] = a0[o]; B1[yy[o], xx[o]] = a1[o] + return tid, B0, B1, cow, vnw, tri + + +def main(): + args = sys.argv[1:] + blend, out = os.path.abspath(args.pop(0)), os.path.abspath(args.pop(0)) + only, ao_every = None, 3 + while args: + f = args.pop(0) + if f == "--actions": + only = {int(x) for x in args.pop(0).split(",")} + elif f == "--ao-every": + ao_every = int(args.pop(0)) + bpy.ops.wm.open_mainfile(filepath=blend) + sc = bpy.context.scene + rig, body = bpy.data.objects["UO_Rig"], bpy.data.objects["UO_Body"] + sc.camera = bpy.data.objects["UO_Camera"]; cd = sc.camera.data + cd.sensor_fit = "HORIZONTAL"; cd.ortho_scale = CW / sc.get("uo_px_per_m", 36.0); cd.shift_x = cd.shift_y = 0.0 + sc.render.resolution_x, sc.render.resolution_y, sc.render.resolution_percentage = CW, CH, 100 + + def anchor_px(): + bpy.context.view_layer.update(); dg = bpy.context.evaluated_depsgraph_get(); cam = sc.camera.evaluated_get(dg) + P = np.array(cam.calc_matrix_camera(dg, x=CW, y=CH)) @ np.array(cam.matrix_world.inverted()) @ np.array([0.0, 0.0, sc.get("uo_anchor_height", 0.07), 1.0]) + return np.array([(P[0] / P[3] + 1) * 0.5 * CW, (1 - P[1] / P[3]) * 0.5 * CH]) + + p0 = anchor_px(); cd.shift_x = cd.shift_y = 0.01; p1 = anchor_px(); k = (p1 - p0) / 0.01 + want = np.array(CANCH, float) + (np.array(sc.get("uo_anchor_px", (68.5, 86.0))) - np.array((68, 86))) + sh = (want - p0) / k; cd.shift_x, cd.shift_y = float(sh[0]), float(sh[1]) + assert np.abs(anchor_px() - want).max() < 1e-3 + + ng = bpy.data.node_groups["UO_Look"] + ldir = next(n for n in ng.nodes if n.type == "COMBXYZ") + L = np.array([ldir.inputs[i].default_value for i in range(3)], float); L /= np.linalg.norm(L) + + names = [g.name for g in body.vertex_groups] + parts = sorted({bpr.part_of(n) for n in names}); pid = {p: i for i, p in enumerate(parts)} + gpart = np.array([pid[bpr.part_of(n)] for n in names]) + me = body.data + Wv = np.zeros((len(me.vertices), len(parts))) + for v in me.vertices: + for g in v.groups: + Wv[v.index, gpart[g.group]] += g.weight + me.calc_loop_triangles() + tri0 = np.array([t.vertices[:] for t in me.loop_triangles]) + tlab = Wv[tri0].sum(1).argmax(1).astype(np.int8) + uvl = me.uv_layers.active.data + tri_uv = np.array([[uvl[l].uv[:] for l in t.loops] for t in me.loop_triangles], np.float32) # (T, 3, 2) + + rng = np.random.default_rng(1) + hemi = rng.normal(size=(8, 3)); hemi[:, 2] = np.abs(hemi[:, 2]); hemi /= np.linalg.norm(hemi, axis=1, keepdims=True) # +z = the normal + + acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) + cols = {k: [] for k in ("frame", "y", "x", "N", "P", "uv", "part", "lit", "ao")} + keys = [] + nfr = 0 + for act in acts: + a = int(act["uo_action"]) + if 23 <= a <= 29 or (only is not None and a not in only): + continue + rig.animation_data.action = act + for d in range(5): + rig["uo_direction"] = d + for i in range(int(act["uo_frames"])): + sc.frame_set(1 + i * STEP); rig.update_tag(); body.update_tag(); bpy.context.view_layer.update() + dg = bpy.context.evaluated_depsgraph_get(); cam = sc.camera.evaluated_get(dg) + Pm = np.array(cam.calc_matrix_camera(dg, x=CW, y=CH)); Vm = np.array(cam.matrix_world.inverted()) + tid, B0, B1, cow, vnw, tri = raster_full(body, dg, Pm, Vm) + Minv = np.array(body.evaluated_get(dg).matrix_world.inverted()) # BVHTree.FromObject works in the object's local space + Mi = Minv[:3, :3] + Lloc = Vector(Mi @ L) + yy, xx = np.nonzero(tid >= 0) + t = tid[yy, xx]; w0, w1 = B0[yy, xx], B1[yy, xx]; w2 = 1 - w0 - w1 + v = tri[t] + P = w0[:, None] * cow[v[:, 0]] + w1[:, None] * cow[v[:, 1]] + w2[:, None] * cow[v[:, 2]] + N = w0[:, None] * vnw[v[:, 0]] + w1[:, None] * vnw[v[:, 1]] + w2[:, None] * vnw[v[:, 2]] + N /= np.maximum(np.linalg.norm(N, axis=1, keepdims=True), 1e-9) + uv = w0[:, None] * tri_uv[t, 0] + w1[:, None] * tri_uv[t, 1] + w2[:, None] * tri_uv[t, 2] + bvh = BVHTree.FromObject(body, dg) + lit = np.zeros(len(t), np.uint8); ao = np.full(len(t), 255, np.uint8) + Pl = (np.c_[P, np.ones(len(P))] @ Minv.T)[:, :3]; Nl = N @ Mi.T + do_ao = (nfr % ao_every == 0) + for j in range(len(t)): + o = Vector(Pl[j] + Nl[j] * 0.003) + lit[j] = 0 if bvh.ray_cast(o, Lloc, 3.0)[0] is not None else 1 + if do_ao: + n = Vector(Nl[j]).normalized(); tt = n.cross(Vector((0, 0, 1)) if abs(n.z) < 0.9 else Vector((1, 0, 0))).normalized(); bb = n.cross(tt) + free = 0 + for h in hemi: + dvec = tt * h[0] + bb * h[1] + n * h[2] + if bvh.ray_cast(o, dvec, 0.4)[0] is None: + free += 1 + ao[j] = int(round(255 * free / 8)) + cols["frame"].append(np.full(len(t), len(keys), np.int32)); cols["y"].append(yy.astype(np.uint8)); cols["x"].append(xx.astype(np.uint8)) + cols["N"].append(N.astype(np.float16)); cols["P"].append(P.astype(np.float16)); cols["uv"].append(uv.astype(np.float16)) + cols["part"].append(tlab[t]); cols["lit"].append(lit); cols["ao"].append(ao) + keys.append((a, d, i)); nfr += 1 + print("action", a, "done", len(keys), "frames", flush=True) + np.savez_compressed(out, key=np.array(keys), parts=np.array(parts), L=L, **{k: np.concatenate(v) for k, v in cols.items()}) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/measure_equipment_extent.py b/third_party/UO_Model3D_v13/pipeline/measure_equipment_extent.py new file mode 100644 index 0000000..e3c556a --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/measure_equipment_extent.py @@ -0,0 +1,91 @@ +"""Extent of every people / equipment animation (body ids >= 400) around the UO anchor point, from anim.idx + anim.mul. + +Only the frame headers are read (centerX, centerY, width, height), so it takes seconds. Per frame, in pixels from the anchor: + left = centerX, right = width - centerX, up = centerY + height, down = -centerY +(the anchor is the pixel (centerX, centerY + height) of the stored frame, see README "Format .vd"; right and down count the anchor +column / row itself, so a canvas W x H with anchor (ax, ay) holds left=ax, right=W-ax, up=ay, down=H-ay). +The client mirrors directions 1..3 into 5..7, so for those left and right are swapped as well. + + python measure_equipment_extent.py [canvas as L,R,U,D, e.g. 128,128,192,64] +Keys of the result are ":", e.g. "anim:527" or "anim4:521" (anim, anim2 .. anim5 are all measured). +""" +import json, mmap, os, struct, sys + +N_ACT, N_DIR = 35, 5 +CUR = dict(left=68, right=68, up=86, down=34) # the 136x120 canvas, anchor (68,86); right / down include the anchor column / row + + +def measure(idx_path, mul_path, tag): + idx = open(idx_path, "rb").read() + n_entries = len(idx) // 12 + res = {} + with open(mul_path, "rb") as f: + mm = mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ) + body = 400 + while 35000 + (body - 400) * 175 + 175 <= n_entries: + base = 35000 + (body - 400) * 175 + ext = dict(left=0, right=0, up=-10**6, down=-10**6) + frames = blocks = 0 + worst = {} + for a in range(N_ACT): + for d in range(N_DIR): + look, length, _ = struct.unpack_from(" len(mm): + continue + blocks += 1 + cnt, = struct.unpack_from(" length: + continue + cx, cy, w, h = struct.unpack_from(" ext[k]: + ext[k] = val + worst[k] = (a, d) + if frames: + res["%s:%d" % (tag, body)] = dict(blocks=blocks, frames=frames, **ext, worst={k: list(v) for k, v in worst.items()}) + body += 1 + return res + + +def need(res, canvas): + """ids whose frames leave the canvas, with the overflow per side""" + out = {} + for b, e in res.items(): + over = {k: e[k] - canvas[k] for k in ("left", "right", "up", "down") if e[k] > canvas[k]} + if over: + out[b] = over + return out + + +if __name__ == "__main__": + src, out = sys.argv[1], sys.argv[2] + res = {} + for tag in ("anim", "anim2", "anim3", "anim4", "anim5"): + ip, mp = os.path.join(src, tag + ".idx"), os.path.join(src, tag + ".mul") + if os.path.exists(ip) and os.path.exists(mp): + r = measure(ip, mp, tag) + print("%-6s %4d animations with frames, %4d complete (35x5)" % (tag, len(r), sum(e["blocks"] == N_ACT * N_DIR for e in r.values()))) + res.update(r) + allmax = {k: max(e[k] for e in res.values()) for k in ("left", "right", "up", "down")} + print("body 400:", {k: res["anim:400"][k] for k in ("left", "right", "up", "down")}) + print("max over everything:", allmax, "at", {k: max(res, key=lambda b: res[b][k]) for k in allmax}) + cvs = [("current 136x120", CUR)] + if len(sys.argv) > 3: + cvs.append(("given", dict(zip(("left", "right", "up", "down"), map(int, sys.argv[3].split(",")))))) + for name, cv in cvs: + n = need(res, cv) + print("%-16s %s: %d animations leave the canvas, worst overflow %s" % (name, cv, len(n), + {k: max(o.get(k, 0) for o in n.values()) if n else 0 for k in ("left", "right", "up", "down")})) + json.dump(dict(canvas_current=CUR, max_all=allmax, bodies=res), open(out, "w"), indent=1) diff --git a/third_party/UO_Model3D_v13/pipeline/merge_anims.py b/third_party/UO_Model3D_v13/pipeline/merge_anims.py new file mode 100644 index 0000000..5a56a0b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/merge_anims.py @@ -0,0 +1,32 @@ +"""Merge per-action pose fits into anim_fit.pkl and write a quality table (worst-view silhouette IoU per frame).""" +import pickle, numpy as np, jax, jax.numpy as jnp +from body import *; from fit import *; from targets import targets +from vd import ACTIONS_PEOPLE +SOURCES = [("anim_fit_run1.pkl", [4, 5, 6, 16, 17, 20, 21, 30, 31, 32, 34]), + ("anim_fit2a.pkl", [0, 1, 2, 3, 7, 9, 10, 11, 15, 18, 33]), + ("anim_fit2b.pkl", [8, 12, 13, 14, 19, 22]), + ("anim_fit2c.pkl", [23, 24, 25, 26, 27, 28, 29])] +sf = pickle.load(open("shape_fit.pkl", "rb")) +S = params_to_shape({k: jnp.asarray(v) for k, v in sf["params"]["shape"].items()}, {k: jnp.asarray(v) for k, v in sf["fixed"].items()}) +@jax.jit +def sil(pp): + P, R = fk(S, pose_from_params(pp)); return jnp.stack([render_sil(S, P, R, d) for d in range(5)]) +final, rows = {}, [] +for f, acts in SOURCES: + r = pickle.load(open(f, "rb")) + for a in acts: + final[a] = dict(poses=r[a]["poses"]) + T = targets(a); w = [] + for i in range(len(T)): + o = np.asarray(sil({k: jnp.asarray(v[i]) for k, v in r[a]["poses"].items()})) > 0.5 + s = T[i][..., 3] > 127 + w.append(min((o[d] & s[d]).sum() / max((o[d] | s[d]).sum(), 1) for d in range(5))) + final[a]["worst_iou"] = w + rows.append((a, ACTIONS_PEOPLE[a], len(T), np.mean(w), np.min(w))) +assert sorted(final) == list(range(35)), sorted(final) +pickle.dump(final, open("anim_fit.pkl", "wb")) +with open("quality_table.md", "w") as fh: + fh.write("| # | akcja | klatek | IoU średnie (najgorszy kierunek) | IoU min |\n|---|---|---|---|---|\n") + for a, n, F, m, mn in sorted(rows): + fh.write(f"| {a} | {n} | {F} | {m:.2f} | {mn:.2f} |\n") +print(open("quality_table.md").read()) diff --git a/third_party/UO_Model3D_v13/pipeline/merge_posefit.py b/third_party/UO_Model3D_v13/pipeline/merge_posefit.py new file mode 100644 index 0000000..6c31684 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/merge_posefit.py @@ -0,0 +1,42 @@ +"""Pick, per action, the best plausible pose set among all fitting runs (mesh-based IoU, anatomical limits).""" +import pickle, os, sys +import numpy as np +from posefit_mesh import evaluate +from vd import ACTIONS_PEOPLE +anim = pickle.load(open("anim_fit.pkl", "rb")); ref = pickle.load(open("refine_mesh.pkl", "rb")) +ridx = {s: i for i, s in enumerate(ref["samples"])} +BASE = os.environ.get("UO_BASE") # previous iteration's final poses (instead of the first-pass fits) + + +def old(a): + if BASE: + return {k: np.asarray(v) for k, v in pickle.load(open(BASE, "rb"))[a]["poses"].items()} + F = anim[a]["poses"]["trans"].shape[0] + return {n: np.stack([ref["poses"][n][ridx[(a, i)]] if (a, i) in ridx else anim[a]["poses"][n][i] for i in range(F)]) for n in ("ball", "hinge", "trans")} +files = [f for f in sys.argv[1:] if os.path.exists(f)] +runs = {f: pickle.load(open(f, "rb")) for f in files} +CACHE = os.environ.get("UO_CACHE", "merge_cache.pkl") +OUTF = os.environ.get("UO_FINAL", "final_poses.pkl") +cache = pickle.load(open(CACHE, "rb")) if os.path.exists(CACHE) else {} +final, table = {}, [] +for a in range(35): + cands = [] + if ("old", a) not in cache: + r, lim = evaluate(a, old(a)); cache[("old", a)] = (r, lim) + r, lim = cache[("old", a)] + cands.append(("old", old(a), r, lim)) + for f, res in runs.items(): + if a in res: + cands.append((f, res[a]["poses"], res[a]["iou"], res[a]["limits"])) + ok = [c for c in cands if c[3].max() < 0.01] or cands + best = max(ok, key=lambda c: c[2][:, 0].mean()) + final[a] = dict(poses=best[1], iou=best[2], limits=best[3], src=best[0]) + table.append((a, ACTIONS_PEOPLE[a], best[0], best[2][:, 0].mean(), best[2][:, 0].min(), best[2][:, 1].mean(), best[3].max(), + cands[0][2][:, 0].mean(), cands[0][3].max())) +pickle.dump(cache, open(CACHE, "wb")) +pickle.dump(final, open(OUTF, "wb")) +with open(os.environ.get("UO_TABLE", "quality_v4.md"), "w") as fh: + fh.write("| # | akcja | IoU najgorszy kier. (śr.) | min | IoU średnie | limity (max) | wcześniej IoU | wcześniej limity |\n|---|---|---|---|---|---|---|---|\n") + for a, n, src, m, mn, mm, lm, om, olm in table: + fh.write(f"| {a} | {n} | {m:.3f} | {mn:.3f} | {mm:.3f} | {lm:.4f} | {om:.3f} | {olm:.3f} |\n") + print(f"{a:2d} {n:24s} src={os.path.basename(src):16s} worst {m:.3f} min {mn:.3f} mean {mm:.3f} lim {lm:.4f} | old {om:.3f} lim {olm:.2f}") diff --git a/third_party/UO_Model3D_v13/pipeline/merge_v6.py b/third_party/UO_Model3D_v13/pipeline/merge_v6.py new file mode 100644 index 0000000..4199894 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/merge_v6.py @@ -0,0 +1,32 @@ +"""v6 merge: base = v5 (+ die actions with the floor term). Search results replace an action when the mean worst-view +IoU improves; floor-polish results replace it when the IoU is (nearly) unchanged (<= 0.003 lower) but less sinks +below the floor. Output: final_poses_v6pre.pkl (then jitter_fix.py -> final).""" +import pickle, numpy as np, jax.numpy as jnp +from posefit_mesh import GROUND, MOUNTED +from posefit_mesh import _posed_j +base = pickle.load(open("final_poses_v6base.pkl", "rb")) +out = {a: dict(r) for a, r in base.items()} + + +def sink(p): + F = p["trans"].shape[0] + return max(float(GROUND - np.asarray(_posed_j({k: jnp.asarray(v[i]) for k, v in p.items()}))[:, 2].min()) for i in range(F)) + + +for f in ("posefit_L1.pkl", "posefit_L2.pkl"): + for a, r in pickle.load(open(f, "rb")).items(): + o = out[a] + if r["limits"].max() < 0.01 and r["iou"][:, 0].mean() > o["iou"][:, 0].mean() + 1e-4: + print(f"{a:2d} search {o['iou'][:,0].mean():.3f} -> {r['iou'][:,0].mean():.3f} ({f})") + out[a] = dict(r, src=f) + else: + print(f"{a:2d} search kept {o['iou'][:,0].mean():.3f} (cand {r['iou'][:,0].mean():.3f})") +for a, r in pickle.load(open("posefit_P3.pkl", "rb")).items(): + o = out[a] + s0, s1 = sink(o["poses"]), sink(r["poses"]) + ok = r["limits"].max() < 0.01 and r["iou"][:, 1].mean() >= o["iou"][:, 1].mean() - 0.003 and s1 < s0 - 0.003 + print(f"{a:2d} floor sink {s0*100:.1f} -> {s1*100:.1f} cm IoU {o['iou'][:,1].mean():.3f} -> {r['iou'][:,1].mean():.3f} {'ACCEPT' if ok else 'keep'}") + if ok: + out[a] = dict(r, src="posefit_P3.pkl") +pickle.dump(out, open("final_poses_v6pre.pkl", "wb")) +print("saved final_poses_v6pre.pkl") diff --git a/third_party/UO_Model3D_v13/pipeline/metal_highlight_fit.py b/third_party/UO_Model3D_v13/pipeline/metal_highlight_fit.py new file mode 100644 index 0000000..e1b93c8 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/metal_highlight_fit.py @@ -0,0 +1,37 @@ +"""Is UO metal matte? Fits sprite = A*(0.0798+0.9202*c) + ks*c^n (c = N.L of the UO light, taken from the replica rendered by test_items.py with the grey +UO_Look material of albedo 0.35) on the interior pixels of 04_stand, 5 directions, for pants 431 (cloth), plate 527 and helm 563 (metal). +Result of session 10: cloth ks = 0; plate/helm ks 0.4-0.6, n 13-20 (linear domain), see SESSION_HANDOFF.md. + + python metal_highlight_fit.py DIR +""" +import os, sys, numpy as np +from PIL import Image +from scipy import ndimage, optimize +HERE=os.path.dirname(os.path.abspath(__file__)); sys.path.insert(0,os.path.join(HERE,"body13")) +from itemframes import canvas, load +S=os.path.abspath(sys.argv[1]) # the --tmp directory of: python test_items.py --items plate,helm,pants --actions 04_stand --tmp DIR +dec=lambda v:np.where(v<=0.04045,v/12.92,((v+0.055)/1.055)**2.4) +def data(item,anim): + bl=load(anim);C=[];P=[] + for d in range(5): + spr=canvas(bl.get((4,d)),0); y0,x0=192-86,128-68 + rr=np.array(Image.open(f"{S}/{item}/clothing/frames/04_stand/dir{d}/00.png").convert("RGBA"))[y0:y0+120,x0:x0+136] + m=ndimage.binary_erosion((rr[...,3]>0)&(spr[...,3]>0),iterations=2) + C.append(rr[m][:,:3].mean(1)); P.append(spr[m][:,:3].mean(1)) + C=np.concatenate(C);P=np.concatenate(P) + c=(dec(C/255)/0.35-0.0798)/0.9202 + return np.clip(c,0,1),P +for item,anim in (("pants",431),("plate",527),("helm",563)): + c,P=data(item,anim) + for name,dom in (("srgb",lambda v:v/255),("linear",lambda v:dec(v/255))): + y=dom(P) + def model(p,c,spec=True): + A,ks,n=p; return A*(0.0798+0.9202*c)+(ks*c**n if spec else 0) + best=None + for n0 in (8,30,100,300): + try: + r=optimize.least_squares(lambda p:model(p,c)-y,[0.3,0.5,n0],bounds=([0,0,1],[1.5,2,2000])) + except Exception as e: continue + if best is None or r.cost 127 +hidden = (horse_masks(a, F) & ~masks) if a in HORSE_OF else np.zeros_like(masks) +m = masks.any((0, 1)); ys, xs = np.nonzero(m); y0, y1, x0, x1 = max(ys.min() - 4, 0), min(ys.max() + 5, CANVAS_H), max(xs.min() - 4, 0), min(xs.max() + 5, CANVAS_W) +rows = [] +for i in range(F): + X = np.asarray(posed({k: jnp.asarray(v[i]) for k, v in res[a]["poses"].items()})) + row = [] + for d in range(5): + mk = raster_vec(np.asarray(project(jnp.asarray(X), d))[tris], CANVAS_W, CANVAS_H) & ~hidden[i, d] + s = masks[i, d] + img = np.full((CANVAS_H, CANVAS_W, 3), 30, np.uint8) + img[hidden[i, d]] = (70, 55, 40) + img[mk & s] = (200, 200, 200); img[s & ~mk] = (235, 60, 60); img[mk & ~s] = (70, 120, 255) + row.append(img[y0:y1, x0:x1]); row.append(np.full((y1 - y0, 2, 3), 90, np.uint8)) + rows.append(np.concatenate(row[:-1], 1)) +im = Image.fromarray(np.concatenate(rows, 0)); im.resize((im.width * 3, im.height * 3), Image.NEAREST).save(out) diff --git a/third_party/UO_Model3D_v13/pipeline/pack_originals.py b/third_party/UO_Model3D_v13/pipeline/pack_originals.py new file mode 100644 index 0000000..fe6d1c0 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/pack_originals.py @@ -0,0 +1,18 @@ +"""Put the original UO body frames into the .blend (enables EXACT_BODY / EXACT_COLORS). +Needs the client file copied here as body400.vd; run build_originals.py first. +usage: python pack_originals.py --blend UO_Body_0x190.blend""" +import bpy, sys, os, json +blend = sys.argv[sys.argv.index("--blend") + 1] +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(blend)) +sc = bpy.context.scene +img = bpy.data.images.get("UO_Original_Atlas") +if img: bpy.data.images.remove(img) +img = bpy.data.images.load(os.path.abspath("UO_Original_Atlas.png")); img.name = "UO_Original_Atlas" +img.colorspace_settings.name = "sRGB"; img.alpha_mode = "STRAIGHT"; img.pack() +mat = bpy.data.objects["UO_Body"].data.materials[0] +mat.node_tree.nodes["UOX_atlas"].image = img +t = bpy.data.texts.get("uo_original_frames.json") or bpy.data.texts.new("uo_original_frames.json") +t.from_string(open("uo_original_frames.json").read()) +sc["uo_exact"] = 1.0 +bpy.ops.wm.save_mainfile() +print("packed") diff --git a/third_party/UO_Model3D_v13/pipeline/param_shape.py b/third_party/UO_Model3D_v13/pipeline/param_shape.py new file mode 100644 index 0000000..d8a067f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/param_shape.py @@ -0,0 +1,104 @@ +"""Parametric body-part shape search scored by the TRUE silhouette IoU (rasterised mesh vs sprites), poses fixed. +Parameters: radial thickness of upper arm / forearm / thigh / shin, hand & head size, foot length & width.""" +import os, sys, pickle, time, json +import numpy as np +import jax, jax.numpy as jnp +from multiprocessing import Pool +os.environ.setdefault("UO_DELTA", "refine_infl.pkl") +from posefit_mesh import (md, defs, P0, pose_from_params, fk, S, W, BONE_JOINT, project, raster_vec, tris, targets, + horse_masks, HORSE_OF, CANVAS_W, CANVAS_H) + +POSES = sys.argv[1] if len(sys.argv) > 1 else "final_poses_v5.pkl" +STEP = int(os.environ.get("UO_FSTEP", "2")) +final = pickle.load(open(POSES, "rb")) +base = np.asarray(md["v"] + pickle.load(open(os.environ["UO_DELTA"], "rb"))["delta"], np.float64) +Wn = np.asarray(md["W"], np.float64); bones = md["bones"] +bd = {d[0]: (np.asarray(d[2], float), np.asarray(d[3], float)) for d in defs} + +PARAMS = ["upper_arm", "forearm", "thigh", "shin", "hand", "head", "foot_len", "foot_w"] + + +def shaped(s): + V = base.copy(); disp = np.zeros_like(V) + for j, b in enumerate(bones): + g = b.split(".")[0] + h, t = bd[b]; u = (t - h) / np.linalg.norm(t - h) + rel = base - h; along = (rel @ u)[:, None] * u; rad = rel - along + if g in ("upper_arm", "forearm", "thigh", "shin"): + dj = (s[g] - 1) * rad + elif g == "hand": + dj = (s["hand"] - 1) * rel + elif g == "head": + c = h + 0.5 * (t - h); dj = (s["head"] - 1) * (base - c) + elif g == "foot": + dj = (s["foot_len"] - 1) * along + (s["foot_w"] - 1) * rad + else: + continue + disp += Wn[:, j:j + 1] * dj + return V + disp + + +@jax.jit +def posed_with(pp, V): + pose = pose_from_params(pp) + P, R = fk(S, pose) + Rb = R[BONE_JOINT] + tb = P[BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, P0[BONE_JOINT]) + X = jnp.einsum("bij,vj->vbi", Rb, V) + tb[None] + return jnp.einsum("vb,vbi->vi", W, X) + + +SAMPLES = [] +MASKS = {} +for a in range(35): + T = targets(a); m = T[..., 3] > 127; F = len(T) + hid = (horse_masks(a, F) & ~m) if a in HORSE_OF else np.zeros_like(m) + for i in range(0, F, STEP): + SAMPLES.append((a, i)); MASKS[(a, i)] = (m[i], hid[i]) + + +def score_proj(item): + (a, i), P2s = item + s, hid = MASKS[(a, i)] + out = [] + for d in range(5): + mk = raster_vec(P2s[d][tris], CANVAS_W, CANVAS_H) & ~hid[d] + out.append((mk & s[d]).sum() / max((mk | s[d]).sum(), 1)) + return out + + +def score(s, pool): + V = jnp.asarray(shaped(s), jnp.float32) + items = [] + for a, i in SAMPLES: + X = posed_with({k: jnp.asarray(v[i]) for k, v in final[a]["poses"].items()}, V) + items.append(((a, i), [np.asarray(project(X, d)) for d in range(5)])) + r = np.array(pool.map(score_proj, items, chunksize=8)) + acts = np.array([a for a, _ in SAMPLES]) + per_act = np.array([r[acts == a].mean() for a in range(35)]) + return per_act.mean(), per_act + + +if __name__ == "__main__": + s = {p: 1.0 for p in PARAMS} + with Pool(4) as pool: + t0 = time.time() + best, pa = score(s, pool) + print("start mean IoU %.4f (%d frames, %.0fs)" % (best, len(SAMPLES), time.time() - t0), flush=True) + for step in (0.10, 0.05, 0.025): + improved = True + while improved: + improved = False + for p in PARAMS: + for sg in (+1, -1): + c = dict(s); c[p] = s[p] + sg * step + v, pa_c = score(c, pool) + if v > best + 1e-4: + best, s, pa = v, c, pa_c; improved = True + print(" %s -> %.3f mean IoU %.4f" % (p, c[p], v), flush=True) + break + print("step %.3f done: %s IoU %.4f" % (step, json.dumps({k: round(v, 3) for k, v in s.items()}), best), flush=True) + json.dump(s, open("param_shape.json", "w")) + V = shaped(s) + pickle.dump(dict(delta=(V - np.asarray(md["v"])).astype(np.float32), params=s), open("refine_param.pkl", "wb")) + print("saved refine_param.pkl", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/patch_final.py b/third_party/UO_Model3D_v13/pipeline/patch_final.py new file mode 100644 index 0000000..05fa7d4 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/patch_final.py @@ -0,0 +1,191 @@ +"""Apply the all-frames refinement to the finished .blend: vertex offsets, refined poses, all-frames texture, +'UO look' material (unlit, grey like the sprites), half-pixel camera correction. Saves a new .blend.""" +import bpy, sys, os, math, pickle +import numpy as np +from mathutils import Vector +import jax.numpy as jnp +from body import JI, NJ, CANVAS_W, CANVAS_H, ANCHOR_X, ANCHOR_Y +from fit import params_to_shape, pose_from_params +from rig import bone_defs, apply_pose +from vd import ACTIONS_PEOPLE +from bpy_compat import clear_fcurves + +SRC = sys.argv[sys.argv.index("--src") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +TEXPNG = sys.argv[sys.argv.index("--tex") + 1] +LIGHT = pickle.load(open(sys.argv[sys.argv.index("--light") + 1], "rb")) if "--light" in sys.argv else None +PERDIR = sys.argv[sys.argv.index("--perdir") + 1] if "--perdir" in sys.argv else None # e.g. UO_Body_Albedo_dir +FINAL = pickle.load(open(sys.argv[sys.argv.index("--poses") + 1], "rb")) if "--poses" in sys.argv else None +os.makedirs(OUT, exist_ok=True) +STEP = 3 +PX_OFF = 0.5 +# the UO anchor lies ~7 cm above the soles of standing frames: lift the animation (and the camera) so that the floor is z = 0 +LIFT = float(sys.argv[sys.argv.index("--lift") + 1]) if "--lift" in sys.argv else 0.070 + +bpy.context.preferences.filepaths.save_version = 0 +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(SRC)) +sc = bpy.context.scene +body = bpy.data.objects["UO_Body"]; arm = bpy.data.objects["UO_Rig"] +sf = pickle.load(open("shape_fit.pkl", "rb")) +S = params_to_shape({k: jnp.asarray(v) for k, v in sf["params"]["shape"].items()}, {k: jnp.asarray(v) for k, v in sf["fixed"].items()}) +Snp = {k: np.asarray(v, np.float64) for k, v in S.items()} +md = pickle.load(open("mesh_data.pkl", "rb")) +ref = pickle.load(open("refine_mesh.pkl", "rb")) +DELTA = pickle.load(open(sys.argv[sys.argv.index("--delta") + 1], "rb"))["delta"] if "--delta" in sys.argv else ref["delta"] +anim = pickle.load(open("anim_fit.pkl", "rb")) + +# 1) rest-pose vertex positions +arm.animation_data.action = None +apply_pose(arm, {d[0]: d[1] for d in bone_defs(Snp, np.zeros((NJ, 3)))}, np.zeros((NJ, 3)), np.zeros(3)) +newv = (md["v"] + DELTA).astype(np.float32) +body.data.vertices.foreach_set("co", newv.ravel()) +body.data.update() + +# 2) texture +img = bpy.data.images.get("UO_Body_Texture") +src = bpy.data.images.load(os.path.abspath(TEXPNG)) +px = np.zeros(src.size[0] * src.size[1] * 4, np.float32); src.pixels.foreach_get(px) +if img is None or tuple(img.size) != tuple(src.size): + img = bpy.data.images.new("UO_Body_Texture", src.size[0], src.size[1], alpha=False) +img.pixels.foreach_set(px) +img.update() +img.pack() +img.filepath = "//UO_Body_Texture.png" +bpy.data.images.remove(src) +old_grey = bpy.data.images.get("UO_Body_Texture_grey") +if old_grey: + bpy.data.images.remove(old_grey) + +# 3) material. The sprites were lit by a light fixed to the UO camera; the texture is the albedo (light removed). +# "UO look" (default) = albedo * (ambient + diffuse * max(0, N.L)) as emission -> renders like the sprites. +# "Lit" = ordinary Principled BSDF for editing / game engines. +theta_ = float(Snp["theta"]) +right_w = Vector((1, 0, 0)); up_w = Vector((0, math.sin(theta_), math.cos(theta_))); tow_w = right_w.cross(up_w) +Lc = LIGHT["L_camera"] if LIGHT else [0.0, 0.2, 0.98] +Lw = (right_w * Lc[0] + up_w * Lc[1] + tow_w * Lc[2]).normalized() +amb = LIGHT["ambient"] if LIGHT else 0.1 +dif = LIGHT["diffuse"] if LIGHT else 0.9 +mat = bpy.data.materials["UO_Skin"] +nt = mat.node_tree +nt.nodes.clear() +N = nt.nodes.new; Lk = nt.links.new +outn = N("ShaderNodeOutputMaterial"); outn.location = (700, 0) +tex = N("ShaderNodeTexImage"); tex.image = img; tex.location = (-900, 100); tex.label = "UO albedo (grey, from all frames)" +bsdf = N("ShaderNodeBsdfPrincipled"); bsdf.location = (-150, 350); bsdf.inputs["Roughness"].default_value = 0.8 +geo = N("ShaderNodeNewGeometry"); geo.location = (-900, -300) +ldir = N("ShaderNodeCombineXYZ"); ldir.location = (-900, -500); ldir.label = "UO light direction (world)" +for i, v in enumerate(Lw): + ldir.inputs[i].default_value = v +dot = N("ShaderNodeVectorMath"); dot.operation = "DOT_PRODUCT"; dot.location = (-650, -350) +mx = N("ShaderNodeMath"); mx.operation = "MAXIMUM"; mx.inputs[1].default_value = 0.0; mx.location = (-450, -350) +mad = N("ShaderNodeMath"); mad.operation = "MULTIPLY_ADD"; mad.location = (-250, -350); mad.label = "ambient + diffuse*cos" +mad.inputs[1].default_value = dif; mad.inputs[2].default_value = amb +mul = N("ShaderNodeMix"); mul.data_type = "RGBA"; mul.blend_type = "MULTIPLY"; mul.location = (-50, -150) +mul.inputs["Factor"].default_value = 1.0 +emis = N("ShaderNodeEmission"); emis.location = (200, -150) +mix = N("ShaderNodeMixShader"); mix.location = (450, 0); mix.label = "UO look" +look = N("ShaderNodeValue"); look.location = (200, 250); look.label = "UO look: 1 = like the sprites, 0 = normal lighting" +look.outputs[0].default_value = 1.0 +Lk(tex.outputs["Color"], bsdf.inputs["Base Color"]) +Lk(geo.outputs["Normal"], dot.inputs[0]); Lk(ldir.outputs["Vector"], dot.inputs[1]) +Lk(dot.outputs["Value"], mx.inputs[0]); Lk(mx.outputs["Value"], mad.inputs[0]) +uo_col = tex.outputs["Color"] +if PERDIR: + # per-direction albedo for the UO render: the rig's "uo_direction" (0..4) picks the texture; other values -> shared + dval = N("ShaderNodeValue"); dval.location = (-1500, -800); dval.label = "UO direction (driver)" + fc = dval.outputs[0].driver_add("default_value") + fc.driver.type = "AVERAGE" + var = fc.driver.variables.new(); var.type = "SINGLE_PROP" + var.targets[0].id_type = "OBJECT"; var.targets[0].id = arm; var.targets[0].data_path = '["uo_direction"]' + for k in range(5): + path = os.path.abspath(f"{PERDIR}{k}.png") + im = bpy.data.images.load(path); im.name = f"UO_Body_Albedo_dir{k}"; im.pack(); im.filepath = f"//UO_Body_Albedo_dir{k}.png" + tk = N("ShaderNodeTexImage"); tk.image = im; tk.location = (-1300, -700 - 260 * k); tk.label = f"albedo seen from UO direction {k}" + cmp = N("ShaderNodeMath"); cmp.operation = "COMPARE"; cmp.location = (-1050, -700 - 260 * k) + cmp.inputs[1].default_value = float(k); cmp.inputs[2].default_value = 0.5 + Lk(dval.outputs[0], cmp.inputs[0]) + mk = N("ShaderNodeMix"); mk.data_type = "RGBA"; mk.location = (-850, -700 - 260 * k) + Lk(cmp.outputs[0], mk.inputs["Factor"]); Lk(uo_col, mk.inputs[6]); Lk(tk.outputs["Color"], mk.inputs[7]) + uo_col = mk.outputs[2] +Lk(uo_col, mul.inputs[6]) +Lk(mad.outputs["Value"], mul.inputs[7]) +Lk(mul.outputs[2], emis.inputs["Color"]) +Lk(look.outputs[0], mix.inputs["Fac"]) +Lk(bsdf.outputs["BSDF"], mix.inputs[1]); Lk(emis.outputs["Emission"], mix.inputs[2]) +Lk(mix.outputs["Shader"], outn.inputs["Surface"]) +ramp = N("ShaderNodeValToRGB"); ramp.location = (-600, 450); ramp.label = "Skin hue (optional, UO-style)" +bw = N("ShaderNodeRGBToBW"); bw.location = (-750, 450) +Lk(tex.outputs["Color"], bw.inputs["Color"]); Lk(bw.outputs["Val"], ramp.inputs["Fac"]) +cr = ramp.color_ramp +cr.elements[0].color = (0.10, 0.06, 0.04, 1); cr.elements[1].color = (1.0, 0.86, 0.74, 1) +sc.view_settings.view_transform = "Standard" # exact sprite colours +sc["uo_light_camera_space"] = list(Lc); sc["uo_light_ambient"] = amb; sc["uo_light_diffuse"] = dif +sun = bpy.data.objects.get("UO_Sun") +if sun: # for the "Lit" branch put the scene sun where the UO light is + sun.rotation_euler = (-Lw).to_track_quat("-Z", "Y").to_euler() + +# 3b) clavicle bones: chest -> clavicle -> upper arm. They do not deform the mesh themselves; their LOCATION moves +# the whole arm chain (shoulder up/out when the arm is raised), fitted per frame like the other joints. +def ensure_clavicles(arm_ob): + if "clavicle.L" in arm_ob.data.bones: + return + bpy.context.view_layer.objects.active = arm_ob + bpy.ops.object.mode_set(mode="EDIT") + eb = arm_ob.data.edit_bones + for s_, sx in (("L", 1.0), ("R", -1.0)): + ua = eb["upper_arm." + s_] + c = eb.new("clavicle." + s_) + c.head = Vector((sx * 0.03, ua.head.y - 0.035, ua.head.z - 0.045)) + c.tail = ua.head.copy() + c.align_roll(Vector((0.0, -1.0, 0.0))) + c.parent = eb["chest"]; c.use_connect = False; c.use_deform = False + ua.parent = c; ua.use_connect = True + bpy.ops.object.mode_set(mode="OBJECT") + + +ensure_clavicles(arm) +CLAV_B = {s_: np.array(arm.data.bones["clavicle." + s_].matrix_local.to_3x3()) for s_ in "LR"} + +# 4) actions: refined poses (non-mounted), fitted poses (mounted) +bone_joint = {d[0]: d[1] for d in bone_defs(Snp, np.zeros((NJ, 3)))} +ref_pose = {} +for k, (a, i) in enumerate(ref["samples"]): + ref_pose[(a, i)] = {n: ref["poses"][n][k] for n in ("ball", "hinge", "trans")} +for a in range(35): + name = f"{a:02d}_{ACTIONS_PEOPLE[a]}" + act = bpy.data.actions[name] + clear_fcurves(act) + arm.animation_data.action = act + F = anim[a]["poses"]["trans"].shape[0] + cyc = a in (0, 1, 2, 3, 23, 24) + keys = list(range(F)) + ([0] if cyc and F > 1 else []) + for ki, i in enumerate(keys): + if FINAL is not None: + pp = {k: v[i] for k, v in FINAL[a]["poses"].items()} + else: + pp = ref_pose.get((a, i)) or {k: v[i] for k, v in anim[a]["poses"].items()} + pose = pose_from_params({k: jnp.asarray(v) for k, v in pp.items()}) + apply_pose(arm, bone_joint, np.asarray(pose["rot"]), np.asarray(pose["trans"]) + np.array([0.0, 0.0, LIFT])) + if "clav" in pp: # offset in the chest frame -> clavicle location in its own rest frame + for k_, s_ in enumerate("LR"): + arm.pose.bones["clavicle." + s_].location = Vector((CLAV_B[s_].T @ np.asarray(pp["clav"][k_], float)).tolist()) + for pb in arm.pose.bones: + pb.keyframe_insert("rotation_quaternion", frame=1 + ki * STEP, group=pb.name) + if pb.parent is None or pb.name.startswith("clavicle."): + pb.keyframe_insert("location", frame=1 + ki * STEP, group=pb.name) +arm.animation_data.action = bpy.data.actions["04_stand"] + +# 5) camera: UO anchor sits on the pixel centre (+0.5 px in x) +theta, scale = float(Snp["theta"]), float(Snp["scale"]) +co = bpy.data.objects["UO_Camera"] +up = Vector((0, math.sin(theta), math.cos(theta))) +view = Vector((0, math.cos(theta), -math.sin(theta))) +target = up * ((ANCHOR_Y - CANVAS_H / 2) / scale) + Vector(((CANVAS_W / 2 - ANCHOR_X - PX_OFF) / scale, 0, LIFT)) +co.location = target - view * 10 +sc["uo_anchor_px"] = [ANCHOR_X + PX_OFF, ANCHOR_Y] +sc["uo_anchor_height"] = LIFT # world height of the UO anchor point (floor = 0) + +txt = bpy.data.texts.get("render_uo_sprites.py") or bpy.data.texts.new("render_uo_sprites.py") +txt.from_string(open("render_uo_sprites.py").read()) +bpy.ops.wm.save_as_mainfile(filepath=os.path.abspath(os.path.join(OUT, "UO_Body_0x190.blend"))) +print("saved", os.path.join(OUT, "UO_Body_0x190.blend")) diff --git a/third_party/UO_Model3D_v13/pipeline/perdir_bake.py b/third_party/UO_Model3D_v13/pipeline/perdir_bake.py new file mode 100644 index 0000000..2dfc66c --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/perdir_bake.py @@ -0,0 +1,29 @@ +"""Per-direction albedo textures (same lighting model), blended with the global albedo where a direction sees little.""" +import sys, pickle, time +import numpy as np +from PIL import Image +sys.argv = ["delight_bake.py"] +src = open("delight_bake.py").read() +exec(src.split("# ---- 1) subsample for the light fit")[0]) +light = pickle.load(open("uo_light.pkl", "rb")) +Lc = np.array(light["L_camera"]); amb, dif = light["ambient"], light["diffuse"] +glob = srgb2lin(np.array(Image.open("UO_Body_Albedo.png").convert("RGB")).astype(np.float64))[ty, tx] +num = np.zeros((5, NT, 3)); den = np.zeros((5, NT)) +for s in range(NS): + X, nrm, Pt, Nt = frame_geom(s) + zc = {} + for d in range(5): + idx, col, ncam, w = visible_samples(s, d, X, nrm, Pt, Nt, zc) + sh = amb + dif * np.maximum(ncam @ Lc, 0) + diff = np.linalg.norm(glob[idx] * sh[:, None] - col, axis=1) + w = w * np.exp(-0.5 * (diff / 0.12) ** 2) + np.add.at(num[d], idx, w[:, None] * col * sh[:, None]); np.add.at(den[d], idx, w * sh * sh) +from texbake import pull_push_fill +for d in range(5): + alb = num[d] / np.maximum(den[d], 1e-9)[:, None] + conf = np.clip(den[d] / 2.0, 0, 1)[:, None] # little evidence -> fall back to the global albedo + mixd = alb * conf + glob * (1 - conf) + tex = np.zeros((TEX, TEX, 3)); wt = np.zeros((TEX, TEX)) + tex[ty, tx] = lin2srgb(mixd); wt[ty, tx] = 1.0 + Image.fromarray(np.clip(pull_push_fill(tex, wt), 0, 255).astype(np.uint8)).save(f"UO_Body_Albedo_dir{d}.png") + print("dir", d, "texels seen %.1f%%" % (100 * (den[d] > 1e-9).mean()), f"{time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/posefit_mesh.py b/third_party/UO_Model3D_v13/pipeline/posefit_mesh.py new file mode 100644 index 0000000..b08694e --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/posefit_mesh.py @@ -0,0 +1,286 @@ +"""Pose fitting on the real skinned mesh (refined rest mesh + skin weights), all frames of an action jointly. + +Loss per frame (5 UO directions): + inside : projected vertices must lie inside the sprite silhouette (distance transform, bilinear) + cover : every sprite boundary pixel must have a projected vertex within ~0.7 px (min-distance, differentiable) + limits : anatomical swing / twist limits per joint (swing-twist decomposition), hinge limits + smooth : temporal smoothness between frames (cyclic for loops) + prior : pull toward a natural pose (small) +""" +import sys, os, time, pickle +import numpy as np +import jax, jax.numpy as jnp, optax +from scipy.ndimage import distance_transform_edt, binary_erosion +from body import * +from fit import params_to_shape, pose_from_params, BALL_IDX, HINGE_IDX, HINGE_AX +from rig import bone_defs +from targets import targets + +sf = pickle.load(open("shape_fit.pkl", "rb")) +S = params_to_shape({k: jnp.asarray(v) for k, v in sf["params"]["shape"].items()}, {k: jnp.asarray(v) for k, v in sf["fixed"].items()}) +md = pickle.load(open("mesh_data.pkl", "rb")) +ref = pickle.load(open("refine_mesh.pkl", "rb")) +DELTA_FILE = os.environ.get("UO_DELTA", "refine_mesh.pkl") # rest-mesh offsets (shape refinement result) +V0 = jnp.asarray(md["v"] + pickle.load(open(DELTA_FILE, "rb"))["delta"], jnp.float32) +W = jnp.asarray(md["W"], jnp.float32) +P0, _ = fk(S, zero_pose()) +defs = bone_defs({k: np.asarray(v) for k, v in S.items()}, np.asarray(P0)) +joint_of = {d[0]: d[1] for d in defs} +BONE_JOINT = np.array([JI[joint_of[b]] for b in md["bones"]]) +CAM = [camera(S, d) for d in range(5)] +RIGHT = jnp.stack([c[0] for c in CAM]); UP = jnp.stack([c[1] for c in CAM]) +SC = S["scale"] +PX_OFF = 0.5 +BI = {j: i for i, j in enumerate(BALL_IDX)} +HI = {j: i for i, j in enumerate(HINGE_IDX)} +MOUNTED = set(range(23, 30)) +CYCLIC = {0, 1, 2, 3, 23, 24} + +# lower-body vertices (ignored by the 'inside' term on mounted frames: the horse hides them in the sprites) +leg_cols = [md["bones"].index(b) for b in md["bones"] if b.split(".")[0] in ("thigh", "shin", "foot", "pelvis")] +LEGV = jnp.asarray(np.asarray(md["W"])[:, leg_cols].sum(1) > 0.5) + +# ---------------------------------------------------------------- anatomical limits +sa, ca = np.sin(ARM_REST_ANGLE), np.cos(ARM_REST_ANGLE) +sl, cl = np.sin(LEG_REST_ANGLE), np.cos(LEG_REST_ANGLE) +# joint: (bone axis in rest frame, max swing deg, max |twist| deg) +LIM = { + "spine": ((0, 0, 1), 35, 30), "chest": ((0, 0, 1), 30, 30), "neck": ((0, 0, 1), 35, 40), "head": ((0, 0, 1), 35, 45), + "shoulder.L": ((sa, 0, -ca), 170, 75), "shoulder.R": ((-sa, 0, -ca), 170, 75), + "wrist.L": ((sa, 0, -ca), 60, 80), "wrist.R": ((-sa, 0, -ca), 60, 80), + "hip.L": ((sl, 0, -cl), 125, 40), "hip.R": ((-sl, 0, -cl), 125, 40), + "ankle.L": ((0, -1, 0), 45, 25), "ankle.R": ((0, -1, 0), 45, 25), +} +LJ = list(LIM) +LIDX = np.array([BI[JI[j]] for j in LJ]) +LAX = jnp.asarray(np.array([np.array(LIM[j][0]) / np.linalg.norm(LIM[j][0]) for j in LJ]), jnp.float32) +LSW = jnp.asarray(np.radians([LIM[j][1] for j in LJ]), jnp.float32) +LTW = jnp.asarray(np.radians([LIM[j][2] for j in LJ]), jnp.float32) + + +def swing_twist(r, a): + th = jnp.sqrt(jnp.sum(r * r) + 1e-12) + w = jnp.cos(th / 2); v = jnp.sin(th / 2) * r / th + twist = 2 * jnp.arctan2(jnp.dot(v, a), w) + twist = jnp.arctan2(jnp.sin(twist), jnp.cos(twist)) + R = rodrigues(r) + swing = jnp.arccos(jnp.clip(jnp.dot(R @ a, a), -1 + 1e-6, 1 - 1e-6)) + return swing, twist + + +def limit_penalty(pp): + b = pp["ball"][LIDX] + sw, tw = jax.vmap(swing_twist)(b, LAX) + pen = jnp.sum(jax.nn.relu(sw - LSW) ** 2) + jnp.sum(jax.nn.relu(jnp.abs(tw) - LTW) ** 2) + # hips: no hyper-extension backwards, limited adduction (thigh direction in the pelvis frame) + for side, sx in (("L", 1.0), ("R", -1.0)): + r = pp["ball"][BI[JI["hip." + side]]] + d = rodrigues(r) @ jnp.array([sx * sl, 0.0, -cl]) + pen += jax.nn.relu(d[1] - 0.45) ** 2 + jax.nn.relu(-sx * d[0] - 0.35) ** 2 + jax.nn.relu(d[2] - 0.6) ** 2 + h = pp["hinge"] + for j in ("elbow.L", "elbow.R"): + e = h[HI[JI[j]]] + pen += jax.nn.relu(e) ** 2 + jax.nn.relu(-2.6 - e) ** 2 + for j in ("knee.L", "knee.R"): + k = h[HI[JI[j]]] + pen += jax.nn.relu(-k) ** 2 + jax.nn.relu(k - 2.6) ** 2 + return pen + + +def natural_prior(pp): + b = pp["ball"] + # everything but the root prefers small rotations (very weak) + pr = jnp.sum(b[1:] ** 2) * 1.0 + if "clav" in pp: # shoulder (clavicle) offsets: small unless the silhouettes need them, at most ~8 cm + n = jnp.sqrt(jnp.sum(pp["clav"] ** 2, -1) + 1e-12) + pr += 1500.0 * jnp.sum(pp["clav"] ** 2) + 50000.0 * jnp.sum(jax.nn.relu(n - 0.08) ** 2) + return pr + + +# ---------------------------------------------------------------- mesh posing / projection +# arm chain bones (upper arm, forearm, hand) per side: they follow the clavicle offset +ARM_L = jnp.asarray([JI[joint_of[b]] in (JI["shoulder.L"], JI["elbow.L"], JI["wrist.L"]) for b in md["bones"]], jnp.float32) +ARM_R = jnp.asarray([JI[joint_of[b]] in (JI["shoulder.R"], JI["elbow.R"], JI["wrist.R"]) for b in md["bones"]], jnp.float32) + + +def posed(pp): + pose = pose_from_params(pp) + P, R = fk(S, pose) + Rb = R[BONE_JOINT] + tb = P[BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, P0[BONE_JOINT]) + if "clav" in pp: # clavicle: the whole arm chain shifts by an offset given in the chest frame + Rc = R[JI["chest"]] + tb = tb + ARM_L[:, None] * (Rc @ pp["clav"][0])[None] + ARM_R[:, None] * (Rc @ pp["clav"][1])[None] + X = jnp.einsum("bij,vj->vbi", Rb, V0) + tb[None] + return jnp.einsum("vb,vbi->vi", W, X) + + +def project(X, d): + return jnp.stack([ANCHOR_X + PX_OFF + SC * (X @ RIGHT[d]), ANCHOR_Y - SC * (X @ UP[d])], -1) + + +def bilinear(img, xy): + x = jnp.clip(xy[:, 0] - 0.5, 0, img.shape[1] - 1.001) + y = jnp.clip(xy[:, 1] - 0.5, 0, img.shape[0] - 1.001) + x0 = jnp.floor(x).astype(int); y0 = jnp.floor(y).astype(int) + fx, fy = x - x0, y - y0 + return (img[y0, x0] * (1 - fx) * (1 - fy) + img[y0, x0 + 1] * fx * (1 - fy) + + img[y0 + 1, x0] * (1 - fx) * fy + img[y0 + 1, x0 + 1] * fx * fy) + + +NB = 260 # boundary pixels per view (padded) + + +GROUND = float(os.environ.get("UO_GROUND", "-0.070")) # sole level of standing frames (the UO anchor is ~7 cm above it) +W_GROUND = float(os.environ.get("UO_W_GROUND", "1.0")) + + +def ground_penalty(X): + """nothing sinks into the floor (0.3 px tolerance), in px^2 like the 'inside' term""" + return jnp.mean(jax.nn.relu((GROUND - X[:, 2]) * SC - 0.3) ** 2) + + +def frame_terms(pp, dto, bpx, bm, mounted): + X = posed(pp) + ins = W_GROUND * 5.0 * ground_penalty(X); cov = 0.0 + for d in range(5): + p = project(X, d) + di = jnp.where(LEGV, bilinear(dto[d, 0], p), bilinear(dto[d, 1], p)) ** 2 + ins += jnp.mean(di) + dist = jnp.sqrt(jnp.min(jnp.sum((bpx[d][:, None, :] - p[None, :, :]) ** 2, -1), 1) + 1e-9) + cov += jnp.sum(bm[d] * jax.nn.relu(dist - 0.7) ** 2) / (jnp.sum(bm[d]) + 1.0) + return ins, cov + + +HORSE_OF = {23: 0, 24: 1, 25: 2, 26: 2, 27: 2, 28: 2, 29: 2} # rider action -> horse (body 0xC8) action +_horse = None + + +def horse_masks(a, F): + """Masks of the horse drawn under the rider (same anchor). Rider pixels hidden by the horse are unknown.""" + global _horse + if _horse is None: + sys.path.insert(0, "../vdtool") + import vdtool + _, _horse = vdtool.read_vd("horse200.vd") + import vdtool + ha = HORSE_OF[a] + out = np.zeros((F, 5, CANVAS_H, CANVAS_W), bool) + for d in range(5): + blk = _horse[ha * 5 + d] + for i in range(F): + fr = blk["frames"][i % len(blk["frames"])] + rgba = vdtool.frame_rgba(fr, blk["palette"]) + x0, y0 = ANCHOR_X - fr["cx"], ANCHOR_Y - (fr["cy"] + fr["h"]) + ys, xs = np.nonzero(rgba[..., 3] > 0) + ys, xs = ys + y0, xs + x0 + ok = (ys >= 0) & (ys < CANVAS_H) & (xs >= 0) & (xs < CANVAS_W) + out[i, d, ys[ok], xs[ok]] = True + return out + + +def prepare(a): + T = targets(a) + F = len(T) + m = T[..., 3] > 127 + allowed = m | horse_masks(a, F) if a in HORSE_OF else m # rider's LOWER body may be hidden behind the horse + dto_a = np.stack([[np.maximum(distance_transform_edt(~allowed[i, d]) - 0.5, 0) for d in range(5)] for i in range(F)]).astype(np.float32) + dto_r = np.stack([[np.maximum(distance_transform_edt(~m[i, d]) - 0.5, 0) for d in range(5)] for i in range(F)]).astype(np.float32) + dto = np.stack([dto_a, dto_r], 2) # (F,5,2,H,W): [allowed for legs/pelvis, rider-only for the rest] + bpx = np.zeros((F, 5, NB, 2), np.float32); bm = np.zeros((F, 5, NB), np.float32) + for i in range(F): + for d in range(5): + edge = m[i, d] & ~binary_erosion(m[i, d]) + ys, xs = np.nonzero(edge) + if len(ys) > NB: + sel = np.linspace(0, len(ys) - 1, NB).astype(int); ys, xs = ys[sel], xs[sel] + n = len(ys) + bpx[i, d, :n] = np.stack([xs + 0.5, ys + 0.5], 1); bm[i, d, :n] = 1 + return F, jnp.asarray(dto), jnp.asarray(bpx), jnp.asarray(bm), m + + +def fit_action(a, init, iters=500, lr=0.01, w_smooth=0.3, w_lim=200.0, w_prior=0.02, log=True): + F, dto, bpx, bm, m = prepare(a) + mounted = jnp.asarray(a in MOUNTED) + cyc = a in CYCLIC + init = {k: jnp.asarray(v) for k, v in init.items()} + + def loss(pp): + ins, cov = jax.lax.map(lambda x: frame_terms(x[0], x[1], x[2], x[3], mounted), + (pp, dto, bpx, bm)) + lim = jax.vmap(limit_penalty)(pp) + pri = jax.vmap(natural_prior)(pp) + sm = 0.0 + if F > 1: + for k in pp: + x = pp[k] + wk = 20.0 if k in ("trans", "clav") else 1.0 + sm += jnp.sum((x[1:] - x[:-1]) ** 2) * wk + if cyc: + sm += jnp.sum((x[0] - x[-1]) ** 2) * wk + total = jnp.sum(4.0 * ins + cov) + w_lim * jnp.sum(lim) + w_prior * jnp.sum(pri) + w_smooth * sm + return total, (jnp.mean(ins), jnp.mean(cov), jnp.sum(lim)) + + vg = jax.jit(jax.value_and_grad(loss, has_aux=True)) + opt = optax.adam(optax.exponential_decay(lr, iters, 0.2)) + pp = init; st = opt.init(pp) + t0 = time.time() + for it in range(iters): + (l, aux), g = vg(pp) + up, st = opt.update(g, st, pp) + pp = optax.apply_updates(pp, up) + if log and (it % 100 == 0 or it == iters - 1): + print(f" a{a} it {it} loss {float(l):.2f} inside {float(aux[0]):.3f} cover {float(aux[1]):.3f} limits {float(aux[2]):.4f} {time.time()-t0:.0f}s", flush=True) + return {k: np.asarray(v) for k, v in pp.items()}, m + + +# ---------------------------------------------------------------- evaluation +from texbake import tri_raster +tris = np.asarray(md["tris"]) + + +def raster_vec(P, W_, H_, maxbox=12): + mn = np.floor(P.min(1)).astype(int); mx = np.ceil(P.max(1)).astype(int) + size = np.clip(mx - mn, 0, maxbox) + a, b, c = P[:, 0], P[:, 1], P[:, 2] + den = (b[:, 1] - c[:, 1]) * (a[:, 0] - c[:, 0]) + (c[:, 0] - b[:, 0]) * (a[:, 1] - c[:, 1]) + ok = np.abs(den) > 1e-12 + img = np.zeros((H_, W_), bool) + for dy in range(int(size[:, 1].max()) + 1): + for dx in range(int(size[:, 0].max()) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px = mn[t, 0] + dx; py = mn[t, 1] + dy + cx, cy = px + 0.5, py + 0.5 + aa, bb, cc, dd = a[t], b[t], c[t], den[t] + l0 = ((bb[:, 1] - cc[:, 1]) * (cx - cc[:, 0]) + (cc[:, 0] - bb[:, 0]) * (cy - cc[:, 1])) / dd + l1 = ((cc[:, 1] - aa[:, 1]) * (cx - cc[:, 0]) + (aa[:, 0] - cc[:, 0]) * (cy - cc[:, 1])) / dd + l2 = 1 - l0 - l1 + k = (l0 >= -1e-4) & (l1 >= -1e-4) & (l2 >= -1e-4) & (px >= 0) & (py >= 0) & (px < W_) & (py < H_) + img[py[k], px[k]] = True + return img + + +_posed_j = jax.jit(posed) +_lim_j = jax.jit(jax.vmap(limit_penalty)) + + +def evaluate(a, poses, masks=None): + """returns per-frame (worst-view IoU, mean IoU) and per-frame limit penalty. + Mounted actions: model pixels that the horse would cover (and the rider sprite does not) are not errors.""" + if masks is None: + masks = targets(a)[..., 3] > 127 + F = masks.shape[0] + hidden = (horse_masks(a, F) & ~masks) if a in HORSE_OF else np.zeros_like(masks) + res = [] + for i in range(F): + pp = {k: jnp.asarray(v[i]) for k, v in poses.items()} + X = np.asarray(_posed_j(pp)) + ious = [] + for d in range(5): + p = np.asarray(project(jnp.asarray(X), d)) + mk = raster_vec(p[tris], CANVAS_W, CANVAS_H) & ~hidden[i, d] + s = masks[i, d] + ious.append((mk & s).sum() / max((mk | s).sum(), 1)) + res.append((min(ious), float(np.mean(ious)))) + lim = np.asarray(_lim_j({k: jnp.asarray(v) for k, v in poses.items()})) + return np.array(res), lim diff --git a/third_party/UO_Model3D_v13/pipeline/posefit_polish.py b/third_party/UO_Model3D_v13/pipeline/posefit_polish.py new file mode 100644 index 0000000..f6cf07a --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/posefit_polish.py @@ -0,0 +1,25 @@ +"""Joint polish of whole actions from a base pose file (all loss terms incl. the ground term).""" +import sys, os, time, pickle +import numpy as np +from posefit_mesh import * +from posefit_mesh import _posed_j + +BASE = sys.argv[sys.argv.index("--base") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +ITERS = int(os.environ.get("UO_ITERS", "300")) +ACTS = [int(a) for a in sys.argv[1:] if a.isdigit() and sys.argv[sys.argv.index(a) - 1] not in ("--base", "--out")] +base = pickle.load(open(BASE, "rb")) +for a in ACTS: + t0 = time.time() + init = {k: np.asarray(v) for k, v in base[a]["poses"].items()} + if os.environ.get("UO_CLAV") and "clav" not in init: # add clavicle offsets (start at 0) + init["clav"] = np.zeros((init["trans"].shape[0], 2, 3), np.float32) + batch, masks = fit_action(a, init, iters=ITERS, lr=float(os.environ.get("UO_LR", "0.004")), log=False) + r, lim = evaluate(a, batch, masks) + res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} + res[a] = dict(poses=batch, iou=r, limits=lim) + pickle.dump(res, open(OUT, "wb")) + X = [np.asarray(_posed_j({k: jnp.asarray(v[i]) for k, v in batch.items()}))[:, 2].min() for i in range(len(r))] + r0 = base[a]["iou"] + print(f"action {a:2d} worstIoU {r0[:,0].mean():.3f} -> {r[:,0].mean():.3f} mean {r0[:,1].mean():.3f} -> {r[:,1].mean():.3f}" + f" lowest z {min(X):+.3f} max limit {lim.max():.4f} {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/posefit_search.py b/third_party/UO_Model3D_v13/pipeline/posefit_search.py new file mode 100644 index 0000000..3553c65 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/posefit_search.py @@ -0,0 +1,138 @@ +"""Local multi-start search for frames stuck in local minima (mostly arms swinging weapons). +For each frame: current pose + random perturbations of ONE arm (shoulder/elbow/wrist) and of the torso, +each optimised; keep the best data fit; then refine the whole action with temporal smoothness. +No left/right swapping: every candidate is a local perturbation of the current (verified) pose.""" +import sys, os, time, pickle +import numpy as np +import jax, jax.numpy as jnp, optax +from posefit_mesh import * + +BASE = sys.argv[sys.argv.index("--base") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +NCAND = int(sys.argv[sys.argv.index("--n") + 1]) if "--n" in sys.argv else 10 +ACTS = [int(a) for k, a in enumerate(sys.argv[1:], 1) if a.isdigit() and sys.argv[k - 1] not in ("--n", "--base", "--out")] +base = pickle.load(open(BASE, "rb")) +res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} +rng = np.random.default_rng(1) + + +def single_fit_fn(a): + mounted = jnp.asarray(a in MOUNTED) + + def loss(pp, nb, dto, bpx, bm, w_nb): + ins, cov = frame_terms(pp, dto, bpx, bm, mounted) + l = 4.0 * ins + cov + 200.0 * limit_penalty(pp) + 0.02 * natural_prior(pp) + l += w_nb * (jnp.sum((pp["ball"] - nb["ball"]) ** 2) + jnp.sum((pp["hinge"] - nb["hinge"]) ** 2) + + 20.0 * jnp.sum((pp["trans"] - nb["trans"]) ** 2)) + return l, (ins, cov) + vg = jax.jit(jax.value_and_grad(loss, has_aux=True)) + ev = jax.jit(loss) + + def fit(init, nb, dto, bpx, bm, iters=250, lr=0.02, w_nb=0.0): + opt = optax.adam(optax.exponential_decay(lr, iters, 0.3)) + pp = {k: jnp.asarray(v) for k, v in init.items()}; st = opt.init(pp) + nbj = {k: jnp.asarray(v) for k, v in nb.items()} + for _ in range(iters): + (l, _), g = vg(pp, nbj, dto, bpx, bm, w_nb) + up, st = opt.update(g, st, pp) + pp = optax.apply_updates(pp, up) + l, (ins, cov) = ev(pp, nbj, dto, bpx, bm, 0.0) + lim = float(limit_penalty(pp)) + return {k: np.asarray(v) for k, v in pp.items()}, float(4.0 * ins + cov), lim + return fit + + +ARM = {"L": ("shoulder.L", "elbow.L", "wrist.L"), "R": ("shoulder.R", "elbow.R", "wrist.R")} + + +from scipy.spatial.transform import Rotation as Rot + + +def yaw_compose(rv, deg): + return (Rot.from_euler("z", deg, degrees=True) * Rot.from_rotvec(rv)).as_rotvec() + + +def twist_candidate(p, deg): + """Turn the upper body by `deg` around the vertical: 1/3 pelvis (legs counter-rotated), 1/3 spine, 1/3 chest.""" + q = {k: v.copy() for k, v in p.items()} + part = deg / 3.0 + q["ball"][BI[JI["pelvis"]]] = yaw_compose(q["ball"][BI[JI["pelvis"]]], part) + for h in ("hip.L", "hip.R"): + q["ball"][BI[JI[h]]] = yaw_compose(q["ball"][BI[JI[h]]], -part) + for j in ("spine", "chest"): + q["ball"][BI[JI[j]]] = yaw_compose(q["ball"][BI[JI[j]]], part) + return q + + +TWISTS = [int(t) for t in os.environ.get("UO_TWISTS", "-90,-60,-30,30,60,90").split(",") if t] +LEANS = [int(t) for t in os.environ.get("UO_LEANS", "").split(",") if t] + + +def roll_compose(rv, deg): + return (Rot.from_euler("y", deg, degrees=True) * Rot.from_rotvec(rv)).as_rotvec() + + +def lean_candidate(p, deg): + """Bend the upper body sideways by `deg` (half spine, half chest), head kept upright.""" + q = {k: v.copy() for k, v in p.items()} + for j in ("spine", "chest"): + q["ball"][BI[JI[j]]] = roll_compose(q["ball"][BI[JI[j]]], deg / 2.0) + q["ball"][BI[JI["neck"]]] = roll_compose(q["ball"][BI[JI["neck"]]], -deg / 2.0) + return q + + +KINDS = [int(k) for k in os.environ.get("UO_KINDS", "0,1,2").split(",")] # 0/1 arm L/R, 2 torso, 3 leg, 4 whole body + + +def perturb(p): + q = {k: v.copy() for k, v in p.items()} + kind = KINDS[rng.integers(0, len(KINDS))] + if kind == 3: # one leg + s_ = "L" if rng.integers(0, 2) == 0 else "R" + q["ball"][BI[JI["hip." + s_]]] += rng.normal(0, 0.5, 3) + q["hinge"][HI[JI["knee." + s_]]] = np.clip(q["hinge"][HI[JI["knee." + s_]]] + rng.normal(0, 0.6), 0.0, 2.5) + q["ball"][BI[JI["ankle." + s_]]] = rng.normal(0, 0.2, 3) + return q + if kind == 4: # whole body orientation + position + q["ball"][BI[JI["pelvis"]]] = (Rot.from_rotvec(rng.normal(0, 0.25, 3)) * Rot.from_rotvec(q["ball"][BI[JI["pelvis"]]])).as_rotvec() + q["trans"] = q["trans"] + rng.normal(0, 0.03, 3) + return q + if kind < 2: # one arm + sh, el, wr = ARM["L" if kind == 0 else "R"] + q["ball"][BI[JI[sh]]] += rng.normal(0, 0.7, 3) + q["hinge"][HI[JI[el]]] = np.clip(q["hinge"][HI[JI[el]]] + rng.normal(0, 0.8), -2.5, 0.0) + q["ball"][BI[JI[wr]]] = rng.normal(0, 0.3, 3) + else: # torso + head + for j in ("spine", "chest", "neck"): + q["ball"][BI[JI[j]]] += rng.normal(0, 0.2, 3) + return q + + +for a in ACTS: + t0 = time.time() + F, dto, bpx, bm, masks = prepare(a) + fit = single_fit_fn(a) + cur = {k: np.asarray(v) for k, v in base[a]["poses"].items()} + if os.environ.get("UO_CLAV") and "clav" not in cur: + cur["clav"] = np.zeros((cur["trans"].shape[0], 2, 3), np.float32) + poses = [] + for i in range(F): + c0 = {k: v[i] for k, v in cur.items()} + best = fit(c0, c0, dto[i], bpx[i], bm[i], iters=150) + starts = [twist_candidate(c0, t) for t in TWISTS] + [lean_candidate(c0, t) for t in LEANS] + [perturb(c0) for _ in range(NCAND)] + if i > 0: + starts.append({k: v for k, v in poses[-1].items()}) # continue from the improved previous frame + for st_ in starts: + p, l, lim = fit(st_, c0, dto[i], bpx[i], bm[i], iters=300) + if lim < 0.01 and l < best[1]: + best = (p, l, lim) + poses.append(best[0]) + batch = {k: np.stack([p[k] for p in poses]) for k in cur} + batch, _ = fit_action(a, batch, iters=200, lr=0.004, log=False) + r, lim = evaluate(a, batch, masks) + res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} + res[a] = dict(poses=batch, iou=r, limits=lim) + pickle.dump(res, open(OUT, "wb")) + r0 = base[a]["iou"] + print(f"action {a:2d} worstIoU {r0[:,0].mean():.3f} -> {r[:,0].mean():.3f} min {r0[:,0].min():.3f} -> {r[:,0].min():.3f}" + f" max limit {lim.max():.4f} {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/posefit_seq.py b/third_party/UO_Model3D_v13/pipeline/posefit_seq.py new file mode 100644 index 0000000..1a99acf --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/posefit_seq.py @@ -0,0 +1,111 @@ +"""Sequential, identity-preserving pose fitting on the skinned mesh. + +For each action: start at the frame most similar to a trusted reference pose (stand / combat stance / previous +result), fit it, then walk frame by frame in both directions (each frame starts from its fitted neighbour), +finally refine all frames jointly with temporal smoothness. Limb identity is never swapped.""" +import sys, time, pickle, os +import numpy as np +import jax, jax.numpy as jnp, optax +from posefit_mesh import * + +OUT = sys.argv[sys.argv.index("--out") + 1] if "--out" in sys.argv else "posefit_seq.pkl" +ACTS = [int(a) for a in sys.argv[1:] if a.isdigit()] +anim = pickle.load(open("anim_fit.pkl", "rb")) +ref = pickle.load(open("refine_mesh.pkl", "rb")) +ridx = {s: i for i, s in enumerate(ref["samples"])} +res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} + + +CUR = os.environ.get("UO_CURRENT") # e.g. final_poses.pkl: warm start from the previous iteration + + +def current(a): + if CUR: + return {k: np.asarray(v) for k, v in pickle.load(open(CUR, "rb"))[a]["poses"].items()} + F = anim[a]["poses"]["trans"].shape[0] + return {n: np.stack([ref["poses"][n][ridx[(a, i)]] if (a, i) in ridx else anim[a]["poses"][n][i] for i in range(F)]) + for n in ("ball", "hinge", "trans")} + + +REF_OF = {9: 7, 10: 7, 11: 7, 18: 7, 20: 7, 31: 7, 30: 7, 15: 7, 12: 8, 13: 8, 14: 8, 19: 8, + 24: 23, 25: 23, 26: 23, 27: 23, 28: 23, 29: 23} + + +REF_FILES = [f for f in ("posefit_A.pkl", "posefit_B.pkl", OUT) if f] + + +def ref_pose(a): + """Trusted start pose: the reference action's refitted result (any worker's file), else the stand.""" + src = REF_OF.get(a, 4 if a not in MOUNTED else 23) + for f in REF_FILES: + if os.path.exists(f): + r = pickle.load(open(f, "rb")) + if src in r and src != a: + return {k: v[0] for k, v in r[src]["poses"].items()}, src + c = current(4) + return {k: v[0] for k, v in c.items()}, 4 + + +def sil_sim(m1, m2): + return (m1 & m2).sum() / max((m1 | m2).sum(), 1) + + +def single_fit_fn(a): + mounted = jnp.asarray(a in MOUNTED) + + def loss(pp, nb, dto, bpx, bm, w_nb): + ins, cov = frame_terms(pp, dto, bpx, bm, mounted) + l = 4.0 * ins + cov + 200.0 * limit_penalty(pp) + 0.02 * natural_prior(pp) + l += w_nb * (jnp.sum((pp["ball"] - nb["ball"]) ** 2) + jnp.sum((pp["hinge"] - nb["hinge"]) ** 2) + + 20.0 * jnp.sum((pp["trans"] - nb["trans"]) ** 2)) + return l, (ins, cov) + vg = jax.jit(jax.value_and_grad(loss, has_aux=True)) + ev = jax.jit(loss) + + def fit(init, nb, dto, bpx, bm, iters=300, lr=0.02, w_nb=0.05): + opt = optax.adam(optax.exponential_decay(lr, iters, 0.3)) + pp = {k: jnp.asarray(v) for k, v in init.items()}; st = opt.init(pp) + nbj = {k: jnp.asarray(v) for k, v in nb.items()} + for _ in range(iters): + (l, _), g = vg(pp, nbj, dto, bpx, bm, w_nb) + up, st = opt.update(g, st, pp) + pp = optax.apply_updates(pp, up) + (l, (ins, cov)) = ev(pp, nbj, dto, bpx, bm, 0.0) + return {k: np.asarray(v) for k, v in pp.items()}, float(4.0 * ins + cov) + return fit + + +for a in ACTS: + t0 = time.time() + F, dto, bpx, bm, masks = prepare(a) + fit = single_fit_fn(a) + rp, src = ref_pose(a) + cur = current(a) + # start frame = the one whose sprites look most like the reference action's first frame + ref_masks = targets(src)[0][..., 3] > 127 + sims = [np.mean([sil_sim(masks[i, d], ref_masks[d]) for d in range(5)]) for i in range(F)] + s0 = int(np.argmax(sims)) + poses = [None] * F + # start frame: from the reference pose and from the previous fit (projected into the limits); keep the better + cands = [rp, {k: v[s0] for k, v in cur.items()}] + best = None + for c in cands: + p, l = fit(c, c, dto[s0], bpx[s0], bm[s0], iters=500, w_nb=0.0) + if best is None or l < best[1]: + best = (p, l) + poses[s0] = best[0] + order = list(range(s0 + 1, F)) + list(range(s0 - 1, -1, -1)) + for i in order: + nbi = i - 1 if i > s0 else i + 1 + p, l = fit(poses[nbi], poses[nbi], dto[i], bpx[i], bm[i]) + # fast motions: the neighbour can be far away -> also start from the earlier (L/R-verified) fit of this frame + p2, l2 = fit({k: v[i] for k, v in cur.items()}, poses[nbi], dto[i], bpx[i], bm[i]) + poses[i] = p if l <= l2 else p2 + batch = {k: np.stack([p[k] for p in poses]) for k in ("ball", "hinge", "trans")} + batch, _ = fit_action(a, batch, iters=250, lr=0.004, log=False) + r, lim = evaluate(a, batch, masks) + res = pickle.load(open(OUT, "rb")) if os.path.exists(OUT) else {} + res[a] = dict(poses=batch, iou=r, limits=lim, start=s0, ref=src) + pickle.dump(res, open(OUT, "wb")) + print(f"action {a:2d} start f{s0} (ref {src}) worstIoU mean {r[:,0].mean():.3f} min {r[:,0].min():.3f} " + f"meanIoU {r[:,1].mean():.3f} max limit pen {lim.max():.4f} {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/preview.py b/third_party/UO_Model3D_v13/pipeline/preview.py new file mode 100644 index 0000000..c744a65 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/preview.py @@ -0,0 +1,33 @@ +import bpy, numpy as np, math +from mathutils import Vector +def setup_scene(res=(360,560)): + sc=bpy.context.scene + sc.render.engine='CYCLES'; sc.cycles.samples=12; sc.cycles.device='CPU' + sc.render.resolution_x, sc.render.resolution_y = res + sc.render.film_transparent=False + w=bpy.data.worlds.new('W'); sc.world=w; w.use_nodes=True + w.node_tree.nodes['Background'].inputs[0].default_value=(0.18,0.19,0.22,1); w.node_tree.nodes['Background'].inputs[1].default_value=0.6 + for name,rot,en in (('Key',(50,0,-35),3.0),('Fill',(60,0,140),1.2)): + l=bpy.data.lights.new(name,'SUN'); l.energy=en + o=bpy.data.objects.new(name,l); o.rotation_euler=[math.radians(a) for a in rot]; sc.collection.objects.link(o) + cam=bpy.data.cameras.new('PrevCam'); cam.type='ORTHO'; cam.ortho_scale=2.1 + co=bpy.data.objects.new('PrevCam',cam); sc.collection.objects.link(co); sc.camera=co + return co +def render_views(path_prefix, center_z=0.95, yaws=(0,45,90,180), elev=8, dist=6): + co=bpy.context.scene.camera + out=[] + for y in yaws: + a=math.radians(y); e=math.radians(elev) + pos=Vector((dist*math.sin(a)*math.cos(e), -dist*math.cos(a)*math.cos(e), center_z+dist*math.sin(e))) + co.location=pos + d=(Vector((0,0,center_z))-pos); co.rotation_euler=d.to_track_quat('-Z','Y').to_euler() + p=f"{path_prefix}_{y}.png"; bpy.context.scene.render.filepath=p + bpy.ops.render.render(write_still=True); out.append(p) + return out +def montage(paths,out): + from PIL import Image + ims=[Image.open(p) for p in paths] + W=sum(i.width for i in ims); H=max(i.height for i in ims) + m=Image.new('RGB',(W,H)); x=0 + for i in ims: m.paste(i,(x,0)); x+=i.width + m.save(out) diff --git a/third_party/UO_Model3D_v13/pipeline/preview_fix.py b/third_party/UO_Model3D_v13/pipeline/preview_fix.py new file mode 100644 index 0000000..4f08b16 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/preview_fix.py @@ -0,0 +1,36 @@ +"""Before/after preview: sprite | v8 overlay | new overlay for one frame, 5 directions, with labels.""" +import sys, pickle, numpy as np, jax.numpy as jnp +from PIL import Image, ImageDraw +from posefit_mesh import * +from posefit_mesh import _posed_j +a, i, out = int(sys.argv[1]), int(sys.argv[2]), sys.argv[3] +A = pickle.load(open("final_poses_v8.pkl", "rb")); B = pickle.load(open(sys.argv[4], "rb")) +T = targets(a); m = T[..., 3] > 127; F = len(T) +hm = horse_masks(a, F) if a in HORSE_OF else np.zeros_like(m) +hid = hm & ~m +ys, xs = np.nonzero((m[i] | hm[i]).any(0)); y0, y1, x0, x1 = max(ys.min() - 3, 0), min(ys.max() + 4, 120), max(xs.min() - 3, 0), min(xs.max() + 4, 136) +def over(P): + X = _posed_j({k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()}); row = []; ious = [] + for d in range(5): + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H) & ~hid[i, d] + img = np.full((120, 136, 3), 30.0); img[hm[i, d]] = (70, 55, 40) + img[mk & m[i, d]] = 200; img[m[i, d] & ~mk] = (230, 60, 60); img[mk & ~m[i, d]] = (70, 120, 255) + row.append(img[y0:y1, x0:x1]); ious.append((mk & m[i, d]).sum() / max((mk | m[i, d]).sum(), 1)) + return row, np.mean(ious) +spr = [] +for d in range(5): + s = T[i, d].astype(float); al = s[..., 3:4] / 255; bg = np.full((120, 136, 3), 30.0); bg[hm[i, d]] = (70, 55, 40) + spr.append((bg * (1 - al) + s[..., :3] * al)[y0:y1, x0:x1]) +ra, ia = over(A); rb, ib = over(B) +sep = np.full((y1 - y0, 2, 3), 90.0) +row = lambda L: np.concatenate(sum([[x, sep] for x in L], [])[:-1], 1) +rows = [row(spr), row(ra), row(rb)] +W_ = rows[0].shape[1]; hs = np.full((2, W_, 3), 90.0) +img = np.concatenate([rows[0], hs, rows[1], hs, rows[2]], 0).astype(np.uint8) +S_ = 4; im = Image.fromarray(img).resize((img.shape[1] * S_, img.shape[0] * S_), Image.NEAREST) +lab = Image.new("RGB", (im.width + 230, im.height), (30, 30, 30)); lab.paste(im, (230, 0)); dr = ImageDraw.Draw(lab) +h = (y1 - y0 + 2) * S_ +for k, t in enumerate(["oryginal UO", f"v8 IoU {ia:.3f}", f"nowe IoU {ib:.3f}"]): + dr.text((10, k * h + h // 2 - 6), t, fill=(235, 235, 235)) +dr.text((10, lab.height - 40), "szary = zgodne", fill=(200, 200, 200)); dr.text((10, lab.height - 26), "czerwony = tylko sprite", fill=(230, 90, 90)); dr.text((10, lab.height - 12), "niebieski = tylko model", fill=(110, 150, 255)) +lab.save(out) diff --git a/third_party/UO_Model3D_v13/pipeline/reeval.py b/third_party/UO_Model3D_v13/pipeline/reeval.py new file mode 100644 index 0000000..aa79f41 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/reeval.py @@ -0,0 +1,10 @@ +"""Re-evaluate pose files with the current UO_DELTA (true raster IoU) -> merged dict with fresh iou/limits.""" +import sys, pickle +from posefit_mesh import evaluate +out = {} +for f in sys.argv[1:-1]: + for a, r in pickle.load(open(f, "rb")).items(): + iou, lim = evaluate(a, r["poses"]) + out[a] = dict(r, iou=iou, limits=lim, src=f) + print(a, f, "%.3f %.3f" % (iou[:, 0].mean(), iou[:, 1].mean()), flush=True) +pickle.dump(out, open(sys.argv[-1], "wb")) diff --git a/third_party/UO_Model3D_v13/pipeline/refine_mesh.py b/third_party/UO_Model3D_v13/pipeline/refine_mesh.py new file mode 100644 index 0000000..dee8724 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/refine_mesh.py @@ -0,0 +1,207 @@ +"""Refine the rigged mesh against ALL sprite frames (2D contour ICP in 5 views per frame). + +Optimises symmetric per-vertex offsets of the rest mesh together with small per-frame pose corrections. +Losses per (frame, view): + inside : every projected vertex must lie inside the sprite silhouette (distance transform, bilinear) + cover : every sprite pixel must be near a projected vertex; uncovered pixels pull the nearest rim vertex + smooth : Laplacian of the offsets, pose-correction prior +""" +import pickle, time, sys +import numpy as np +import jax, jax.numpy as jnp, optax +from scipy.ndimage import distance_transform_edt, binary_erosion +from scipy.spatial import cKDTree +from body import * +from fit import params_to_shape, pose_from_params +from rig import bone_defs +from targets import targets + +ITERS = int(sys.argv[1]) if len(sys.argv) > 1 else 1500 +BATCH = 8 +EXCLUDE = set(range(23, 30)) # mounted: rider sprites have the horse cut out + +sf = pickle.load(open("shape_fit.pkl", "rb")) +S = params_to_shape({k: jnp.asarray(v) for k, v in sf["params"]["shape"].items()}, {k: jnp.asarray(v) for k, v in sf["fixed"].items()}) +anim = pickle.load(open("anim_fit.pkl", "rb")) +md = pickle.load(open("mesh_data.pkl", "rb")) +V0 = jnp.asarray(md["v"], jnp.float32) +W = jnp.asarray(md["W"], jnp.float32) +tris = np.asarray(md["tris"]) +mirror = np.asarray(md["mirror"]) +NV = V0.shape[0] +P0, _ = fk(S, zero_pose()) +defs = bone_defs({k: np.asarray(v) for k, v in S.items()}, np.asarray(P0)) +joint_of = {d[0]: d[1] for d in defs} +BONE_JOINT = np.array([JI[joint_of[b]] for b in md["bones"]]) # in the weight-matrix column order + +# edges for the Laplacian +E = set() +for f in md["faces"]: + for a, b in zip(f, f[1:] + f[:1]): + E.add((min(a, b), max(a, b))) +E = np.array(sorted(E)) +deg = np.bincount(E.ravel(), minlength=NV).astype(np.float32) +EI, EJ = jnp.asarray(E[:, 0]), jnp.asarray(E[:, 1]) +DEG = jnp.asarray(np.maximum(deg, 1.0)) # loose vertices have no edges +MIR = jnp.asarray(mirror) +FLIP = jnp.array([-1.0, 1.0, 1.0]) + +# ---------------------------------------------------------------- samples +samples = [] # (action, frame) +for a in sorted(anim): + if a in EXCLUDE: + continue + for i in range(anim[a]["poses"]["trans"].shape[0]): + samples.append((a, i)) +NS = len(samples) +pose0 = {k: jnp.asarray(np.stack([anim[a]["poses"][k][i] for a, i in samples])) for k in ("ball", "hinge", "trans")} +print("frames", NS, "views", NS * 5, flush=True) +H, Wc = CANVAS_H, CANVAS_W +masks = np.zeros((NS, 5, H, Wc), bool) +cache_t = {} +for s, (a, i) in enumerate(samples): + if a not in cache_t: + cache_t[a] = targets(a) + masks[s] = cache_t[a][i][..., 3] > 127 +DTO = np.stack([[np.maximum(distance_transform_edt(~masks[s, d]) - 0.5, 0) for d in range(5)] for s in range(NS)]).astype(np.float32) +DTO = jnp.asarray(DTO) +CAM = [camera(S, d) for d in range(5)] +RIGHT = jnp.stack([c[0] for c in CAM]); UP = jnp.stack([c[1] for c in CAM]) +FWD = jnp.cross(RIGHT, UP) +SC = S["scale"] + + +def symmetric(delta): + return 0.5 * (delta + delta[MIR] * FLIP) + + +def posed_verts(delta, pp): + pose = pose_from_params(pp) + P, R = fk(S, pose) + Rb = R[BONE_JOINT] # (B,3,3) + tb = P[BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, P0[BONE_JOINT]) + v = V0 + symmetric(delta) + X = jnp.einsum("bij,vj->vbi", Rb, v) + tb[None] + return jnp.einsum("vb,vbi->vi", W, X) + + +PX_OFF = 0.5 # UO anchor sits on the pixel centre (measured: best alignment with +0.5 px in x) + + +def project(X): + x = ANCHOR_X + PX_OFF + SC * (X @ RIGHT.T) # (V,5) + y = ANCHOR_Y - SC * (X @ UP.T) + return jnp.stack([x, y], -1).transpose(1, 0, 2) # (5,V,2) + + +def bilinear(img, xy): + x = jnp.clip(xy[:, 0] - 0.5, 0, img.shape[1] - 1.001) + y = jnp.clip(xy[:, 1] - 0.5, 0, img.shape[0] - 1.001) + x0 = jnp.floor(x).astype(int); y0 = jnp.floor(y).astype(int) + fx, fy = x - x0, y - y0 + return (img[y0, x0] * (1 - fx) * (1 - fy) + img[y0, x0 + 1] * fx * (1 - fy) + + img[y0 + 1, x0] * (1 - fx) * fy + img[y0 + 1, x0 + 1] * fx * fy) + + +@jax.jit +def forward(delta, pp): + X = posed_verts(delta, pp) + return project(X), X + + +def sample_loss(delta, pp, pp0, dto, cv, ct, cm): + """dto (5,H,W); cv (5,K) vertex idx; ct (5,K,2) target px; cm (5,K) mask.""" + X = posed_verts(delta, pp) + p = project(X) + inside = sum(jnp.mean(bilinear(dto[d], p[d]) ** 2) for d in range(5)) + pc = jnp.take_along_axis(p, cv[..., None], axis=1) + cover = jnp.sum(cm * jnp.sum((pc - ct) ** 2, -1)) / (jnp.sum(cm) + 1.0) + prior = sum(jnp.sum((pp[k] - pp0[k]) ** 2) for k in ("ball", "hinge")) * 0.3 + jnp.sum((pp["trans"] - pp0["trans"]) ** 2) * 5.0 + return 4.0 * inside + cover + prior, (inside, cover) + + +def total_loss(params, idx, dto, cv, ct, cm): + delta = params["delta"] + pp = {k: params[k][idx] for k in ("ball", "hinge", "trans")} + p0 = {k: pose0[k][idx] for k in ("ball", "hinge", "trans")} + l, (ins, cov) = jax.vmap(lambda a, b, c, d, e, f: sample_loss(delta, a, b, c, d, e, f), + in_axes=({"ball": 0, "hinge": 0, "trans": 0}, {"ball": 0, "hinge": 0, "trans": 0}, 0, 0, 0, 0))(pp, p0, dto, cv, ct, cm) + d = symmetric(delta) + lap = d - (jax.ops.segment_sum(d[EJ], EI, NV) + jax.ops.segment_sum(d[EI], EJ, NV)) / DEG[:, None] + smooth = jnp.sum(lap ** 2) * 300.0 + jnp.sum(d ** 2) * 0.05 + return jnp.mean(l) + smooth, (jnp.mean(ins), jnp.mean(cov), smooth) + + +vg = jax.jit(jax.value_and_grad(total_loss, has_aux=True)) +K = 400 + + +def correspondences(p, X, s): + """For sample s: uncovered sprite pixels -> nearest rim vertex (per view).""" + cv = np.zeros((5, K), np.int32); ct = np.zeros((5, K, 2), np.float32); cm = np.zeros((5, K), np.float32) + Xn = np.asarray(X) + fn = np.cross(Xn[tris[:, 1]] - Xn[tris[:, 0]], Xn[tris[:, 2]] - Xn[tris[:, 0]]) + nrm = np.zeros_like(Xn) + for k in range(3): + np.add.at(nrm, tris[:, k], fn) + nrm /= np.maximum(np.linalg.norm(nrm, axis=1, keepdims=True), 1e-12) + for d in range(5): + pd = np.asarray(p[d]) + tree = cKDTree(pd) + ys, xs = np.nonzero(masks[s, d]) + pix = np.stack([xs + 0.5, ys + 0.5], 1) + dist, _ = tree.query(pix) + unc = pix[dist > 0.8] + if len(unc) == 0: + continue + rim = np.nonzero(np.abs(nrm @ np.asarray(FWD[d])) < 0.35)[0] + if len(rim) == 0: + continue + _, j = cKDTree(pd[rim]).query(unc) + n = min(len(unc), K) + sel = np.random.choice(len(unc), n, replace=False) if len(unc) > K else np.arange(n) + cv[d, :n] = rim[j[sel]]; ct[d, :n] = unc[sel]; cm[d, :n] = 1.0 + return cv, ct, cm + + +def iou_all(params, n=None): + res = [] + for s in range(NS if n is None else n): + pp = {k: params[k][s] for k in ("ball", "hinge", "trans")} + p, _ = forward(params["delta"], pp) + for d in range(5): + img = np.zeros((H, Wc), bool) + q = np.asarray(p[d]); xi = np.clip(q[:, 0].astype(int), 0, Wc - 1); yi = np.clip(q[:, 1].astype(int), 0, H - 1) + img[yi, xi] = True + from scipy.ndimage import binary_closing, binary_fill_holes + img = binary_fill_holes(binary_closing(img, iterations=1)) + m = masks[s, d] + res.append((img & m).sum() / max((img | m).sum(), 1)) + return float(np.mean(res)) + + +params = dict(delta=jnp.zeros((NV, 3), jnp.float32), **{k: pose0[k] for k in ("ball", "hinge", "trans")}) +opt = optax.adam(optax.exponential_decay(3e-3, ITERS, 0.2)) +st = opt.init(params) +print("IoU before (vertex splat, all frames):", round(iou_all(params), 4), flush=True) +rng = np.random.default_rng(0) +t0 = time.time() +for it in range(ITERS): + idx = rng.choice(NS, BATCH, replace=False) + cvs, cts, cms = [], [], [] + for s in idx: + pp = {k: params[k][s] for k in ("ball", "hinge", "trans")} + p, X = forward(params["delta"], pp) + cv, ct, cm = correspondences(p, X, s) + cvs.append(cv); cts.append(ct); cms.append(cm) + (l, aux), g = vg(params, jnp.asarray(idx), DTO[idx], jnp.asarray(np.stack(cvs)), jnp.asarray(np.stack(cts)), jnp.asarray(np.stack(cms))) + up, st = opt.update(g, st, params) + params = optax.apply_updates(params, up) + if it % 100 == 0 or it == ITERS - 1: + print(f"it {it} loss {float(l):.4f} inside {float(aux[0]):.4f} cover {float(aux[1]):.3f} smooth {float(aux[2]):.4f} " + f"max|d| {float(jnp.abs(symmetric(params['delta'])).max()):.3f} {time.time()-t0:.0f}s", flush=True) +print("IoU after (vertex splat, all frames):", round(iou_all(params), 4), flush=True) +out = dict(delta=np.asarray(symmetric(params["delta"])), samples=samples, + poses={k: np.asarray(params[k]) for k in ("ball", "hinge", "trans")}) +pickle.dump(out, open("refine_mesh.pkl", "wb")) +print("saved refine_mesh.pkl") diff --git a/third_party/UO_Model3D_v13/pipeline/refine_shape2.py b/third_party/UO_Model3D_v13/pipeline/refine_shape2.py new file mode 100644 index 0000000..dea6c79 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/refine_shape2.py @@ -0,0 +1,79 @@ +"""Shape refinement v2: symmetric per-vertex offsets of the rest mesh, poses FIXED to the plausible refit poses, +all 35 actions (mounted ones with the horse-aware masks). Differentiable inside + cover terms (no ICP).""" +import os, sys, time, pickle +import numpy as np +import jax, jax.numpy as jnp, optax +os.environ.setdefault("UO_DELTA", "refine_mesh.pkl") +import posefit_mesh as PM +from posefit_mesh import prepare, pose_from_params, fk, S, W, P0, BONE_JOINT, project, bilinear, md + +ITERS = int(sys.argv[1]) if len(sys.argv) > 1 else 2000 +final = pickle.load(open("final_poses.pkl", "rb")) +base = jnp.asarray(md["v"], jnp.float32) +delta0 = jnp.asarray(pickle.load(open(os.environ["UO_DELTA"], "rb"))["delta"], jnp.float32) +mirror = jnp.asarray(md["mirror"]); FLIP = jnp.array([-1.0, 1.0, 1.0]) +E = set() +for f in md["faces"]: + for a, b in zip(f, f[1:] + f[:1]): + E.add((min(a, b), max(a, b))) +E = np.array(sorted(E)); NV = base.shape[0] +deg = jnp.asarray(np.maximum(np.bincount(E.ravel(), minlength=NV), 1).astype(np.float32)) +EI, EJ = jnp.asarray(E[:, 0]), jnp.asarray(E[:, 1]) + +samples, D, BP, BMK = [], [], [], [] +for a in range(35): + F, dto, bpx, bm, _ = prepare(a) + for i in range(F): + samples.append((a, i)); D.append(dto[i]); BP.append(bpx[i]); BMK.append(bm[i]) +D = jnp.stack(D); BP = jnp.stack(BP); BMK = jnp.stack(BMK) +POSE = {k: jnp.asarray(np.stack([final[a]["poses"][k][i] for a, i in samples])) for k in ("ball", "hinge", "trans")} +NS = len(samples) +print("frames", NS, flush=True) + + +def sym(d): + return 0.5 * (d + d[mirror] * FLIP) + + +def posed_with(pp, V): + pose = pose_from_params(pp) + P, R = fk(S, pose) + Rb = R[BONE_JOINT] + tb = P[BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, P0[BONE_JOINT]) + X = jnp.einsum("bij,vj->vbi", Rb, V) + tb[None] + return jnp.einsum("vb,vbi->vi", W, X) + + +def frame_loss(delta, pp, dto, bpx, bm): + X = posed_with(pp, base + sym(delta)) + ins = 0.0; cov = 0.0 + for d in range(5): + p = project(X, d) + ins += jnp.mean(bilinear(dto[d], p) ** 2) + dist = jnp.sqrt(jnp.min(jnp.sum((bpx[d][:, None, :] - p[None, :, :]) ** 2, -1), 1) + 1e-9) + cov += jnp.sum(bm[d] * jax.nn.relu(dist - 0.7) ** 2) / (jnp.sum(bm[d]) + 1.0) + return ins, cov + + +def loss(delta, idx): + pp = {k: v[idx] for k, v in POSE.items()} + ins, cov = jax.vmap(lambda a, b, c, d: frame_loss(delta, a, b, c, d))(pp, D[idx], BP[idx], BMK[idx]) + d = sym(delta) + lap = d - (jax.ops.segment_sum(d[EJ], EI, NV) + jax.ops.segment_sum(d[EI], EJ, NV)) / deg[:, None] + reg = jnp.sum(lap ** 2) * 300.0 + jnp.sum(d ** 2) * 0.05 + return jnp.mean(4.0 * ins + cov) + reg, (jnp.mean(ins), jnp.mean(cov)) + + +vg = jax.jit(jax.value_and_grad(loss, has_aux=True)) +opt = optax.adam(optax.exponential_decay(2e-3, ITERS, 0.2)) +delta = delta0; st = opt.init(delta) +rng = np.random.default_rng(0); t0 = time.time() +for it in range(ITERS): + idx = jnp.asarray(rng.choice(NS, 8, replace=False)) + (l, aux), g = vg(delta, idx) + up, st = opt.update(g, st, delta) + delta = optax.apply_updates(delta, up) + if it % 250 == 0 or it == ITERS - 1: + print(f"it {it} loss {float(l):.3f} inside {float(aux[0]):.3f} cover {float(aux[1]):.3f} {time.time()-t0:.0f}s", flush=True) +pickle.dump(dict(delta=np.asarray(sym(delta))), open("refine_shape2.pkl", "wb")) +print("saved refine_shape2.pkl") diff --git a/third_party/UO_Model3D_v13/pipeline/refine_shape3.py b/third_party/UO_Model3D_v13/pipeline/refine_shape3.py new file mode 100644 index 0000000..99ca9e3 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/refine_shape3.py @@ -0,0 +1,106 @@ +"""Shape refinement v3: symmetric per-vertex offsets of the rest mesh with the poses FIXED (v5), all 35 actions, +same data terms as the pose fit (lower body may hide behind the horse). Epoch-shuffled batches, small decaying lr.""" +import os, sys, time, pickle +import numpy as np +import jax, jax.numpy as jnp, optax +os.environ.setdefault("UO_DELTA", "refine_infl.pkl") +from posefit_mesh import prepare, pose_from_params, fk, S, W, P0, BONE_JOINT, project, bilinear, md, LEGV, MOUNTED + +ITERS = int(sys.argv[1]) if len(sys.argv) > 1 else 900 +POSES = os.environ.get("UO_POSES", "final_poses_v5.pkl") +OUTF = os.environ.get("UO_SHAPE_OUT", "refine_shape3.pkl") +final = pickle.load(open(POSES, "rb")) +base = jnp.asarray(md["v"], jnp.float32) +delta0 = jnp.asarray(pickle.load(open(os.environ["UO_DELTA"], "rb"))["delta"], jnp.float32) +mirror = jnp.asarray(md["mirror"]); FLIP = jnp.array([-1.0, 1.0, 1.0]) +E = set() +for f in md["faces"]: + for a, b in zip(f, f[1:] + f[:1]): + E.add((min(a, b), max(a, b))) +E = np.array(sorted(E)); NV = base.shape[0] +deg = jnp.asarray(np.maximum(np.bincount(E.ravel(), minlength=NV), 1).astype(np.float32)) +EI, EJ = jnp.asarray(E[:, 0]), jnp.asarray(E[:, 1]) + +samples, D, BP, BMK = [], [], [], [] +for a in range(35): + F, dto, bpx, bm, _ = prepare(a) + for i in range(F): + samples.append((a, i)); D.append(np.asarray(dto[i])); BP.append(np.asarray(bpx[i])); BMK.append(np.asarray(bm[i])) +D = jnp.asarray(np.stack(D)); BP = jnp.asarray(np.stack(BP)); BMK = jnp.asarray(np.stack(BMK)) +POSE = {k: jnp.asarray(np.stack([final[a]["poses"][k][i] for a, i in samples])) for k in ("ball", "hinge", "trans")} +NS = len(samples) +print("frames", NS, flush=True) + + +def sym(d): + return 0.5 * (d + d[mirror] * FLIP) + + +def posed_with(pp, V): + pose = pose_from_params(pp) + P, R = fk(S, pose) + Rb = R[BONE_JOINT] + tb = P[BONE_JOINT] - jnp.einsum("bij,bj->bi", Rb, P0[BONE_JOINT]) + X = jnp.einsum("bij,vj->vbi", Rb, V) + tb[None] + return jnp.einsum("vb,vbi->vi", W, X) + + +def frame_loss(delta, pp, dto, bpx, bm): + X = posed_with(pp, base + sym(delta)) + ins = 0.0; cov = 0.0 + for d in range(5): + p = project(X, d) + ins += jnp.mean(jnp.where(LEGV, bilinear(dto[d, 0], p), bilinear(dto[d, 1], p)) ** 2) + dist = jnp.sqrt(jnp.min(jnp.sum((bpx[d][:, None, :] - p[None, :, :]) ** 2, -1), 1) + 1e-9) + cov += jnp.sum(bm[d] * jax.nn.relu(dist - 0.7) ** 2) / (jnp.sum(bm[d]) + 1.0) + return ins, cov + + +def data_loss(delta, idx): + pp = {k: v[idx] for k, v in POSE.items()} + ins, cov = jax.vmap(lambda a, b, c, d: frame_loss(delta, a, b, c, d))(pp, D[idx], BP[idx], BMK[idx]) + return jnp.mean(4.0 * ins + cov), (jnp.mean(ins), jnp.mean(cov)) + + +def reg_loss(delta): + d = sym(delta) + lap = d - (jax.ops.segment_sum(d[EJ], EI, NV) + jax.ops.segment_sum(d[EI], EJ, NV)) / deg[:, None] + dd = d - delta0 + return jnp.sum(lap ** 2) * 300.0 + jnp.sum(dd ** 2) * 0.5 + + +def loss(delta, idx): + l, aux = data_loss(delta, idx) + return l + reg_loss(delta), aux + + +vg = jax.jit(jax.value_and_grad(loss, has_aux=True)) +dl = jax.jit(data_loss) + + +def full(delta): + tot = np.zeros(3); n = 0 + for s in range(0, NS, 30): + idx = jnp.arange(s, min(s + 30, NS)) + l, (i_, c_) = dl(delta, idx) + k = len(idx); tot += np.array([float(l), float(i_), float(c_)]) * k; n += k + return tot / n + + +BATCH = 30 +opt = optax.adam(optax.exponential_decay(4e-4, ITERS, 0.1)) +delta = delta0; st = opt.init(delta) +rng = np.random.default_rng(0); t0 = time.time() +print("start full data loss %.4f inside %.4f cover %.4f" % tuple(full(delta)), flush=True) +perm = [] +for it in range(ITERS): + if len(perm) < BATCH: + perm = list(rng.permutation(NS)) + idx = jnp.asarray(perm[:BATCH]); perm = perm[BATCH:] + (l, aux), g = vg(delta, idx) + up, st = opt.update(g, st, delta) + delta = optax.apply_updates(delta, up) + if (it + 1) % 150 == 0 or it == ITERS - 1: + print(f"it {it} full data loss %.4f inside %.4f cover %.4f {time.time()-t0:.0f}s" % tuple(full(delta)), flush=True) + pickle.dump(dict(delta=np.asarray(sym(delta))), open(OUTF, "wb")) +print("saved", OUTF) diff --git a/third_party/UO_Model3D_v13/pipeline/render3d_gif.py b/third_party/UO_Model3D_v13/pipeline/render3d_gif.py new file mode 100644 index 0000000..6b945b9 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/render3d_gif.py @@ -0,0 +1,79 @@ +"""3D perspective preview GIFs of UO actions from a built .blend (textured body, floor, horse proxy for mounted). +usage: python render3d_gif.py --blend out_v9/UO_Body_0x190.blend --out gifs3d --actions 0,9,23 [--only-frame N]""" +import bpy, sys, os, math +import numpy as np +from mathutils import Vector +from PIL import Image, ImageDraw +arg = lambda k, d=None: sys.argv[sys.argv.index(k) + 1] if k in sys.argv else d +blend, out = arg("--blend"), os.path.abspath(arg("--out")) +ACTS = [int(x) for x in arg("--actions").split(",")] +ONLY = int(arg("--only-frame", "-1")) +os.makedirs(out, exist_ok=True) +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(blend)) +sc = bpy.context.scene +sc.render.engine = "CYCLES"; sc.cycles.samples = 16; sc.cycles.device = "CPU"; sc.cycles.use_denoising = True +sc.render.resolution_x, sc.render.resolution_y = 360, 420; sc.render.resolution_percentage = 100 +sc.render.film_transparent = False; sc.render.image_settings.file_format = "PNG" +sc.view_settings.view_transform = "Standard" +sc["uo_look"] = 0.0 # normal lighting (Principled BSDF + albedo texture) +rig = bpy.data.objects["UO_Rig"]; rig["uo_direction"] = 0 +if "Clothing" in bpy.data.collections: + for o in bpy.data.collections["Clothing"].all_objects: + o.hide_render = True +w = sc.world or bpy.data.worlds.new("W"); sc.world = w; w.use_nodes = True +w.node_tree.nodes["Background"].inputs[0].default_value = (0.32, 0.34, 0.38, 1); w.node_tree.nodes["Background"].inputs[1].default_value = 0.6 +sun = bpy.data.lights.new("PreviewSun", "SUN"); sun.energy = 3.0; so = bpy.data.objects.new("PreviewSun", sun) +so.rotation_euler = (math.radians(50), 0, math.radians(35)); sc.collection.objects.link(so) +me = bpy.data.meshes.new("Floor"); me.from_pydata([(-4, -4, 0), (4, -4, 0), (4, 4, 0), (-4, 4, 0)], [], [(0, 1, 2, 3)]) +fl = bpy.data.objects.new("Floor", me); sc.collection.objects.link(fl) +fm = bpy.data.materials.new("FloorMat"); fm.use_nodes = True +fb = fm.node_tree.nodes["Principled BSDF"]; fb.inputs["Base Color"].default_value = (0.22, 0.2, 0.18, 1) +fb.inputs["Roughness"].default_value = 1.0 +if "Specular IOR Level" in fb.inputs: + fb.inputs["Specular IOR Level"].default_value = 0.0 +me.materials.append(fm) +hm = bpy.data.materials.get("Horse_Proxy_Mat") +if hm: + hm.use_nodes = True + hm.node_tree.nodes["Principled BSDF"].inputs["Base Color"].default_value = (0.36, 0.24, 0.14, 1) + hm.node_tree.nodes["Principled BSDF"].inputs["Roughness"].default_value = 0.8 +horses = {o.name: o for o in bpy.data.objects if o.name.startswith("Horse_a")} +for o in horses.values(): + o.is_holdout = False; o.hide_render = True +cd = bpy.data.cameras.new("PreviewCam"); cd.lens = 50 +cam = bpy.data.objects.new("PreviewCam", cd); sc.collection.objects.link(cam); sc.camera = cam +lift = float(sc.get("uo_anchor_height", 0.0)) +acts = {int(a["uo_action"]): a for a in bpy.data.actions if "uo_action" in a} +for a in ACTS: + act = acts[a]; rig.animation_data.action = act; F = int(act["uo_frames"]) + mounted = 23 <= a <= 29 + tgt = Vector((0, 0.1 if mounted else 0, 1.25 if mounted else 0.95)); dist = 6.2 if mounted else 4.4 + yaw, el = math.radians(55 if mounted else 35), math.radians(14) + cam.location = tgt + Vector((math.sin(yaw) * math.cos(el), -math.cos(yaw) * math.cos(el), math.sin(el))) * dist + cam.rotation_euler = (tgt - cam.location).to_track_quat("-Z", "Y").to_euler() + cyc = a in (0, 1, 2, 3, 23, 24) + last = 3 * F if (cyc and F > 1) else 3 * (F - 1) + 1 + frames = [ONLY] if ONLY > 0 else list(range(1, last + 1)) if F > 1 else [1] * 24 + ims = [] + for k, f in enumerate(frames): + if F == 1 and ONLY <= 0: # single-frame action: turntable + yk = yaw + 2 * math.pi * k / len(frames) + cam.location = tgt + Vector((math.sin(yk) * math.cos(el), -math.cos(yk) * math.cos(el), math.sin(el))) * dist + cam.rotation_euler = (tgt - cam.location).to_track_quat("-Z", "Y").to_euler() + i = int(round((f - 1) / 3.0)) % F + for o in horses.values(): + o.hide_render = True + h = horses.get("Horse_a%d_f%d" % (a, i)) + if h: h.hide_render = False + sc.frame_set(f) + p = os.path.join(out, "_tmp.png"); sc.render.filepath = p; bpy.ops.render.render(write_still=True) + im = Image.open(p).convert("RGB"); d = ImageDraw.Draw(im) + d.text((8, 8), "%s UO %d/%d" % (act.name, i + 1, F), fill=(240, 240, 240)); ims.append(im) + name = os.path.join(out, "3d_%s.%s" % (act.name, "png" if ONLY > 0 else "gif")) + if F == 1 and ONLY <= 0: + ims[0].save(name, save_all=True, append_images=ims[1:], duration=120, loop=0) + elif ONLY > 0 or len(ims) == 1: + ims[0].save(name.replace(".gif", ".png")) + else: + ims[0].save(name, save_all=True, append_images=ims[1:], duration=42, loop=0) + print("saved", name, flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/render_body_vd.py b/third_party/UO_Model3D_v13/pipeline/render_body_vd.py new file mode 100644 index 0000000..a71227b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/render_body_vd.py @@ -0,0 +1,17 @@ +"""Render the BODY layer of a built .blend for all 35 UO actions x 5 directions and write it to a .vd file.""" +import bpy, sys, os +blend = sys.argv[sys.argv.index("--blend") + 1] +out = os.path.abspath(sys.argv[sys.argv.index("--out") + 1]) +samples = int(sys.argv[sys.argv.index("--samples") + 1]) if "--samples" in sys.argv else 32 +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(blend)) +sc = bpy.context.scene +sc.render.engine = "CYCLES"; sc.cycles.samples = samples; sc.cycles.device = "CPU" +src = bpy.data.texts["render_uo_layer.py"].as_string() +src = src.replace('LAYER = "clothing"', 'LAYER = "body"').replace('OUT_DIR = "//uo_render/"', 'OUT_DIR = %r' % (out + "/")) +src = src.replace('VD_FILE = "//uo_render/%s.vd"', 'VD_FILE = %r' % (out + "/%s.vd")) +layer = sys.argv[sys.argv.index("--layer") + 1] if "--layer" in sys.argv else "body" +src = src.replace('LAYER = "body"', 'LAYER = %r' % layer) +if "--pure" in sys.argv: + src = src.replace("EXACT_BODY = True", "EXACT_BODY = False") +assert "WRITE_VD = True" in src +exec(compile(src, "render_uo_layer.py", "exec")) diff --git a/third_party/UO_Model3D_v13/pipeline/render_check.py b/third_party/UO_Model3D_v13/pipeline/render_check.py new file mode 100644 index 0000000..4573b30 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/render_check.py @@ -0,0 +1,36 @@ +import bpy, sys, os, math, numpy as np +from mathutils import Vector +blend=sys.argv[sys.argv.index('--blend')+1]; out=sys.argv[sys.argv.index('--out')+1] +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(blend)) +sc=bpy.context.scene +arm=bpy.data.objects['UO_Rig'] +act_name = sys.argv[sys.argv.index('--action')+1] if '--action' in sys.argv else None +frame = int(sys.argv[sys.argv.index('--frame')+1]) if '--frame' in sys.argv else 1 +if act_name: arm.animation_data.action=bpy.data.actions[act_name] +else: arm.animation_data.action=None +sc.frame_set(frame) +sc.render.engine='CYCLES'; sc.cycles.samples=16; sc.cycles.device='CPU' +# 1) turntable preview (perspective-free ortho, big) +cam=bpy.data.cameras.new('Prev'); cam.type='ORTHO'; cam.ortho_scale=2.2 +co=bpy.data.objects.new('Prev',cam); sc.collection.objects.link(co) +uo_cam=sc.camera +sc.camera=co; sc.render.resolution_x, sc.render.resolution_y=(380,560); sc.render.film_transparent=False +sc.render.filter_size=1.5 +paths=[] +for yaw in (0,45,90,180): + a=math.radians(yaw); e=math.radians(8); d=6 + pos=Vector((d*math.sin(a)*math.cos(e), -d*math.cos(a)*math.cos(e), 1.0+d*math.sin(e))) + co.location=pos; co.rotation_euler=(Vector((0,0,1.0))-pos).to_track_quat('-Z','Y').to_euler() + p=f"{out}_turn{yaw}.png"; sc.render.filepath=os.path.abspath(p); bpy.ops.render.render(write_still=True); paths.append(p) +from PIL import Image +ims=[Image.open(p).convert('RGB') for p in paths] +m=Image.new('RGB',(sum(i.width for i in ims),ims[0].height)); x=0 +for i in ims: m.paste(i,(x,0)); x+=i.width +m.save(out+'_turntable.png') +# 2) UO camera renders for 5 directions +sc.camera=uo_cam; sc.render.resolution_x, sc.render.resolution_y=(136,120); sc.render.film_transparent=True +sc.render.filter_size=0.5 +uo=[] +for d in range(5): + arm['uo_direction']=d; sc.frame_set(frame) + p=f"{out}_uo{d}.png"; sc.render.filepath=os.path.abspath(p); bpy.ops.render.render(write_still=True); uo.append(p) diff --git a/third_party/UO_Model3D_v13/pipeline/render_overlay.py b/third_party/UO_Model3D_v13/pipeline/render_overlay.py new file mode 100644 index 0000000..4934093 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/render_overlay.py @@ -0,0 +1,23 @@ +"""render_overlay.py action out.png : grey both, red sprite-only, blue render-only, brown = horse sprite""" +import sys, os, numpy as np +from PIL import Image +from targets import targets +from vd import ACTIONS_PEOPLE +root, a, out = sys.argv[1], int(sys.argv[2]), sys.argv[3] +T = targets(a); m = T[..., 3] > 127; F = len(T) +hm = None +if a >= 23 and a <= 29: + from posefit_mesh import horse_masks + hm = horse_masks(a, F) +name = f"{a:02d}_{ACTIONS_PEOPLE[a]}" +rows = [] +for i in range(F): + row = [] + for d in range(5): + r = np.array(Image.open(os.path.join(root, "frames", name, "dir%d" % d, "%02d.png" % i)))[..., 3] > 127 + img = np.full((120, 136, 3), 30, np.uint8) + if hm is not None: img[hm[i, d]] = (70, 55, 40) + img[r & m[i, d]] = 200; img[m[i, d] & ~r] = (230, 60, 60); img[r & ~m[i, d]] = (70, 120, 255) + row.append(img); row.append(np.full((120, 2, 3), 90, np.uint8)) + rows.append(np.concatenate(row[:-1], 1)) +im = Image.fromarray(np.concatenate(rows, 0)); im.resize((im.width * 2, im.height * 2), Image.NEAREST).save(out) diff --git a/third_party/UO_Model3D_v13/pipeline/render_uo_layer.py b/third_party/UO_Model3D_v13/pipeline/render_uo_layer.py new file mode 100644 index 0000000..dcbb4a0 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/render_uo_layer.py @@ -0,0 +1,823 @@ +# UO layer renderer: renders the body or the clothing layer through "UO_Camera" for every UO action, +# 5 directions and every frame, post-processes like UO art and writes PNGs (vdtool layout) and a .vd file. +# Run from Blender's Text Editor (Alt+P). Edit the settings below first. +# +# LAYER = "clothing" : objects in the "Clothing" collection; the body is a HOLDOUT (it hides what is behind it, +# but is not drawn itself) - exactly what an equipment layer in UO must contain. +# LAYER = "body" : only the body (clothing hidden). +# LAYER = "all" : body + clothing together (preview; not a UO layer). +# EXACT_BODY / EXACT_COLORS: use the original UO frames packed in this file (see README) for a pixel-exact body. +# In Blender's window the frames are rendered step by step (uo_job.py), so the window stays alive: progress in the status bar, +# ESC cancels. In background mode (blender -b, the bpy module) it is a plain loop; there create an empty file named STOP in the +# output folder (e.g. uo_render/clothing/STOP) or press Ctrl+C to cancel. Delete STOP before the next run. +# Several runs into the same OUT_DIR add up: e.g. render ONLY = [attacks] with one grip, then ONLY = [others] with +# another; each run writes a .vd with ALL actions rendered so far (delete OUT_DIR to start from scratch). +import bpy, os, json +import numpy as np +from mathutils import Vector +from mathutils.bvhtree import BVHTree + +LAYER = "clothing" +ONLY = [] # e.g. ["04_stand", "00_walk_unarmed"]; empty = all 35 UO actions +OUTLINE = 0.38 # dark 1-px outline like UO art (measured on the original body); 1.0 = off +OUT_DIR = "//uo_render/" # PNG output root (vdtool 'canvas' layout + meta.json) +WRITE_VD = True +VD_FILE = "//uo_render/%s.vd" # %s -> LAYER +STEP = 3 # scene frames between two UO frames +CANVAS = (256, 256) # render size in px (width, height); 36 px/m. The .vd stores every frame cropped to its content +ANCHOR = (128, 192) # UO anchor pixel inside the canvas (world point 0, 0, scene["uo_anchor_height"]). + # 256x256 / (128, 192) holds 444 of the 449 people / equipment animations of the Nelderim client + # (the original body frames are 136x120 with anchor (68, 86); use that pair for the old size) +CLOTHING = "Clothing" # collection with the clothing / equipment meshes +HORSE_HOLDOUT = True # mounted actions: the horse hides what is behind it, clipped to the exact horse sprite +EXACT_COLORS = True # body in the UO look: colours projected from the original UO frames packed in the file +EXACT_BODY = True # body = original UO frames: the "body" layer reproduces the original exactly, and in + # the "clothing" layer the body hides items exactly along the ORIGINAL outline + # (the 3D model only decides what is in front / behind). Turn off for a modified body. +HOLDOUT_MARGIN = 0.01 # m: in the clothing layer the body hides an item only where it is at least this much in + # front of it, so skin poking a few mm through tight armour does not cut holes + # (1 px = 2.8 cm). 0 = plain Cycles holdout (renders every frame twice). +OCCLUDERS = ["head", "upper_arm", "forearm", "hand", "thigh", "shin", "foot"] # body parts that may hide items + # (with HOLDOUT_MARGIN > 0); the torso (pelvis, spine, chest, neck) never does, because + # items are worn over it and a torso poking through is a model error, not an occluder +OWN_PARTS_NEVER_HIDE = True # body parts an item is skinned to (a legs item: thighs, shins, pelvis) never hide it: the item + # wraps them, so their skin in front of the item shell is the item's own edge, not an occluder + # (it cut 1-px strips off the sides of trousers). False = every OCCLUDERS part may hide it +TORSO_HIDE_MARGIN = 0.12 # m: the torso (pelvis, spine, chest, neck, clavicle) hides an item only where the item is at least this + # much behind it: a cloak hangs behind the body, so the chest must hide it; shells worn over the + # torso (up to ~3 cm thick) are never hidden. 0 = the torso never hides anything. + # Only when a cloak (cloth chains "cloak_*") is worn: UO draws other items over the torso even where + # they are behind it (a sleeve of an arm behind the chest), and hiding them cost 0.02-0.07 IoU +DESPECKLE = 28 # clothing: single dark pixels inside the item darker than their neighbours by more + # than this (0-255) take the colour around them - deep sculpt details / rivets that + # turn into black dots at UO size. 0 = off +FILL_HOLES = 4 # px: holes INSIDE an item (fully surrounded by it) up to this size are filled - skin + # poking through or a gap in the item mesh, not a real occluder. 0 = off +BODY_GAP = 0.006 # m: every frame, parts of the bound items closer than this to the arms, hands, legs or + # head of the posed body are pushed out (smoothly) before rendering - otherwise a forearm + # poking through a sleeve in motion cuts a hole in the item. Cloth-baked frames have their + # own fix (uo_cloth_bake FIX_GAP). 0 = off +MIN_PIECE = 8 # px: detached bits of the item smaller than this are removed (collar or cuff rims cut + # off by the head or a hand read as dirt at UO size); the biggest piece always stays. 0 = off + + +OW, OH, OANCHOR = 136, 120, (68, 86) # size and anchor of the ORIGINAL UO body frames (atlas, horse masks) +W, H = CANVAS +DX, DY = ANCHOR[0] - OANCHOR[0], ANCHOR[1] - OANCHOR[1] # where the original frames sit inside the canvas + +sc = bpy.context.scene +rig = bpy.data.objects["UO_Rig"] +body = bpy.data.objects["UO_Body"] +clothes = [o for o in bpy.data.collections[CLOTHING].all_objects if o.type == "MESH"] if CLOTHING in bpy.data.collections else [] + +# items baked by uo_cloth_bake.py: their cloth simulation replaces the bound pose in the actions it covers +CLOTH = {} +for o in clothes: + if o.get("uo_cloth"): + p = bpy.path.abspath(o["uo_cloth"]) + base = o.data.shape_keys.key_blocks[0].data if o.data.shape_keys else o.data.vertices + co = np.empty(len(o.data.vertices) * 3, np.float32); base.foreach_get("co", co) + sig = np.array([len(o.data.vertices), float(np.abs(co.astype(np.float64)).sum())]) + d = np.load(p) if os.path.exists(p) else None + if d is not None and "item_sig" in d.files and np.allclose(d["item_sig"], sig, rtol=1e-5): + CLOTH[o.name] = {k: d[k] for k in d.files} + print("render_uo_layer: %s uses its cloth bake %s" % (o.name, p)) + elif d is not None: + print("render_uo_layer: %s changed after its cloth bake - rendered as bound (bake it again)" % o.name) + else: + print("render_uo_layer: cloth bake of %s not found (%s) - rendered as bound" % (o.name, p)) + + +def cloth_show(o, a, i): + """baked cloth shape of UO action a, frame i on item o (shape key 'uo_cloth', Armature off); else the bound item""" + c = CLOTH.get(o.name) + arm = [m for m in o.modifiers if m.type == "ARMATURE"] + key = o.data.shape_keys.key_blocks.get("uo_cloth") if o.data.shape_keys else None + if c is None or ("a%d_f%d" % (a, i)) not in c: + for m in arm: + m.show_viewport = m.show_render = True + if key: + key.value = 0.0 + return + co = c["a%d_f%d" % (a, i)].astype(np.float64); tris, fi = c["tris"], c["fi"] + A, B, C = co[tris[:, 0]], co[tris[:, 1]], co[tris[:, 2]] + e1 = B - A; e1 /= np.maximum(np.linalg.norm(e1, axis=1, keepdims=True), 1e-12) + n = np.cross(B - A, C - A); n /= np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12) + fr = np.stack([e1, np.cross(n, e1), n], 1)[fi] + pos = (co[tris[fi]] * c["bc"][..., None]).sum(1) + np.einsum("nk,nkj->nj", c["off"], fr) + if "fix_node" in c and ("d%d_f%d_i" % (a, i)) in c: # pushed out of the real body after the simulation + Dn = np.zeros((int(c["fix_node"].max()) + 1, 3)); Dn[c["d%d_f%d_i" % (a, i)]] = c["d%d_f%d_v" % (a, i)] + pos += Dn[c["fix_node"]] + if key is None: + if o.data.shape_keys is None: + o.shape_key_add(name="Basis", from_mix=False) + key = o.shape_key_add(name="uo_cloth", from_mix=False) + key.data.foreach_set("co", pos.astype(np.float32).ravel()); key.value = 1.0 + for m in arm: + m.show_viewport = m.show_render = False + o.data.update() + + +# BODY_GAP: bound items pushed out of the posed limbs / head, per UO frame (shape key "uo_fix", Armature off) +FIX_MESH, FIX_CACHE, FIX_ON, FIX_ADDED = {}, {}, {}, set() + + +def fix_mesh(o): + """welded nodes (UV-seam splits move together, so a fix never tears the item open), their edges and degrees""" + if o.name not in FIX_MESH: + co = np.empty(len(o.data.vertices) * 3, np.float32); o.data.vertices.foreach_get("co", co) + key = np.round(co.reshape(-1, 3).astype(np.float64) / 1e-5).astype(np.int64) + _, first, node = np.unique(key, axis=0, return_index=True, return_inverse=True); node = node.ravel() + E = np.empty(len(o.data.edges) * 2, np.int32); o.data.edges.foreach_get("vertices", E) + E = np.unique(np.sort(node[E.reshape(-1, 2)], 1), axis=0); E = E[E[:, 0] != E[:, 1]] + FIX_MESH[o.name] = (first, node, E, np.bincount(E.ravel(), minlength=len(first)).astype(float)) + return FIX_MESH[o.name] + + +def push_out(X, bvh, E, deg, gap): + """displacement that keeps the points X (body space) `gap` outside the body parts in bvh; spread over the item""" + D = np.zeros_like(X); look = np.arange(len(X)); reach = 0.1 + for it in range(12): + P = X + D; need = np.zeros(len(X)); N = np.zeros_like(X); near = [] + for i in look: + p = Vector(P[i]); loc, nrm, fi, dist = bvh.find_nearest(p, reach) + if loc is not None: + near.append(i); sd = (p - loc).dot(nrm) + if sd < gap: + need[i] = gap - sd; N[i] = nrm + if it == 0: + look = np.array(near, int); reach = gap + 0.05 + if not (need > 1e-4).any(): + break + D += need[:, None] * N + if it < 11: + for _ in range(2): + acc = np.zeros_like(D) + np.add.at(acc, E[:, 0], D[E[:, 1]]); np.add.at(acc, E[:, 1], D[E[:, 0]]) + D = np.where(deg[:, None] > 0, 0.5 * D + 0.5 * acc / np.maximum(deg, 1)[:, None], D) + look = np.union1d(look, np.nonzero(np.abs(D).max(1) > 1e-5)[0]) + return D + + +def fix_off(o): + st = FIX_ON.pop(o.name, None) + if st is None: + return + kb = o.data.shape_keys.key_blocks + kb["uo_fix"].value = 0.0 + for name, mute in st["mute"].items(): + kb[name].mute = mute + for m, (v, r) in st["arm"]: + m.show_viewport, m.show_render = v, r + o.data.update() + + +def fix_on(o, pos): + if o.data.shape_keys is None: + o.shape_key_add(name="Basis", from_mix=False); FIX_ADDED.add(o.name) + kb = o.data.shape_keys.key_blocks + key = kb.get("uo_fix") or o.shape_key_add(name="uo_fix", from_mix=False) + key.data.foreach_set("co", pos.astype(np.float32).ravel()); key.value = 1.0 + others = [k for k in list(kb)[1:] if k.name != "uo_fix"] + arm = [m for m in o.modifiers if m.type == "ARMATURE"] + FIX_ON[o.name] = dict(mute={k.name: k.mute for k in others}, arm=[(m, (m.show_viewport, m.show_render)) for m in arm]) + for k in others: + k.mute = True # the posed shape already contains them + for m in arm: + m.show_viewport = m.show_render = False + o.data.update() + + +def evaluated_co(ob, dg): + ev = ob.evaluated_get(dg); me = ev.to_mesh() + co = np.empty(len(me.vertices) * 3, np.float32); me.vertices.foreach_get("co", co) + return ev, me, co.reshape(-1, 3).astype(np.float64) + + +def body_fix(a, i): + """BODY_GAP for UO frame i of action a: the pose does not depend on the direction, so each frame is solved once""" + items = [o for o in clothes if not o.hide_render and not (o.name in CLOTH and ("a%d_f%d" % (a, i)) in CLOTH[o.name])] + for o in items: + fix_off(o) + if not items: + return + bpy.context.view_layer.update(); dg = bpy.context.evaluated_depsgraph_get() + todo = [o for o in items if (o.name, a, i) not in FIX_CACHE] + if todo: + eb, me, bco = evaluated_co(body, dg) + me.calc_loop_triangles() + tri = np.empty(len(me.loop_triangles) * 3, np.int32); me.loop_triangles.foreach_get("vertices", tri) + tri = tri.reshape(-1, 3); Bi = np.array(eb.matrix_world.inverted()); eb.to_mesh_clear() + if len(OCCLUDER_TRIS) == len(tri): + tri = tri[OCCLUDER_TRIS] # arms, hands, legs, head: the parts that cut holes + bvh = BVHTree.FromPolygons([Vector(p) for p in bco], tri.tolist()) + for o in items: + first, node, E, deg = fix_mesh(o) + ev, me, co = evaluated_co(o, dg); Mw = np.array(ev.matrix_world); ev.to_mesh_clear() + if len(co) != len(node): + FIX_CACHE[(o.name, a, i)] = None # a modifier changes the vertex count: left as bound + continue + if (o.name, a, i) not in FIX_CACHE: + M = Bi @ Mw + D = push_out(co[first] @ M[:3, :3].T + M[:3, 3], bvh, E, deg, BODY_GAP) @ np.linalg.inv(M[:3, :3]).T + idx = np.nonzero(np.abs(D).max(1) > 2e-4)[0] + FIX_CACHE[(o.name, a, i)] = (idx.astype(np.int32), D[idx].astype(np.float32)) if len(idx) else None + c = FIX_CACHE[(o.name, a, i)] + if c is not None: + Dn = np.zeros((len(first), 3)); Dn[c[0]] = c[1] + fix_on(o, co + Dn[node]) + + +def fix_clear(): + for o in clothes: + fix_off(o) + sk = o.data.shape_keys + if sk and "uo_fix" in sk.key_blocks: + o.shape_key_remove(sk.key_blocks["uo_fix"]) + if o.name in FIX_ADDED and o.data.shape_keys and len(o.data.shape_keys.key_blocks) == 1: + o.shape_key_clear() + + + +for o in clothes: # left over from a run that crashed: back to the bound item + if o.data.shape_keys and "uo_fix" in o.data.shape_keys.key_blocks: + o.shape_key_remove(o.data.shape_keys.key_blocks["uo_fix"]) + for m in o.modifiers: + if m.type == "ARMATURE": + m.show_viewport = m.show_render = True +writer = bpy.data.texts["uo_vd_writer.py"].as_module() + +if sc.render.engine != "CYCLES": # holdout, exact modes and UO shading are set up for Cycles + print("render_uo_layer: render engine %s -> CYCLES" % sc.render.engine) + sc.render.engine = "CYCLES" +if not bpy.context.preferences.filepaths.use_scripts_auto_execute: + print("render_uo_layer: NOTE - 'Auto Run Python Scripts' is off; if the body looks wrong, enable it " + "(Preferences > Save & Load) and reopen the file") +sc.camera = bpy.data.objects["UO_Camera"] +sc.render.resolution_x, sc.render.resolution_y = W, H +sc.render.resolution_percentage = 100 +sc.cycles.device = "CPU" # 1 sample on a 256x256 frame: a GPU only adds device start-up / kernel loading to every one of the + # thousands of render calls (slow, and the window looks frozen); the CPU is faster here +sc.render.dither_intensity = 0.0 # Blender's 8-bit dither is +-1 noise that depends on the pixel position: it would change + # with the canvas / anchor and spoil the "exact" colours of EXACT_COLORS + + +def to_canvas(a, fill=0): + """array of an original 120x136 frame -> CANVAS size, the anchors aligned (identity for 136x120 / (68, 86))""" + out = np.full((H, W) + a.shape[2:], fill, a.dtype) + y0, y1, x0, x1 = max(DY, 0), min(DY + OH, H), max(DX, 0), min(DX + OW, W) + if y1 > y0 and x1 > x0: + out[y0:y1, x0:x1] = a[y0 - DY:y1 - DY, x0 - DX:x1 - DX] + return out + + +def anchor_px(): + """continuous pixel position of the world anchor point in the CANVAS render (pixel i covers [i, i+1))""" + bpy.context.view_layer.update(); dg = bpy.context.evaluated_depsgraph_get(); cam = sc.camera.evaluated_get(dg) + P = np.array(cam.calc_matrix_camera(dg, x=W, y=H)) @ np.array(cam.matrix_world.inverted()) @ \ + np.array([0.0, 0.0, sc.get("uo_anchor_height", 0.07), 1.0]) + return np.array([(P[0] / P[3] + 1) * 0.5 * W, (1 - P[1] / P[3]) * 0.5 * H]) + + +def place_camera(): + """UO_Camera for CANVAS: 36 px/m and the anchor point on ANCHOR (the original frames put it at scene uo_anchor_px = + (68.5, 86.0), i.e. in the middle of pixel column 68, on the top edge of row 86). Returns the old settings.""" + cd = sc.camera.data + old = (cd.sensor_fit, cd.ortho_scale, cd.shift_x, cd.shift_y) + cd.sensor_fit = "HORIZONTAL" + cd.ortho_scale = W / sc.get("uo_px_per_m", 36.0) + cd.shift_x = cd.shift_y = 0.0 + p0 = anchor_px(); cd.shift_x = cd.shift_y = 0.01; p1 = anchor_px() + k = (p1 - p0) / 0.01 # px per unit of shift (x and y are independent) + off = np.array(sc.get("uo_anchor_px", (OANCHOR[0] + 0.5, OANCHOR[1] + 0.0))) - np.array(OANCHOR) + want = np.array(ANCHOR, float) + off + sh = (want - p0) / k + cd.shift_x, cd.shift_y = [0.0 if abs(s * kk) < 1e-3 else float(s) for s, kk in zip(sh, k)] # the 136x120 frame: exactly the file's camera + err = np.abs(anchor_px() - want).max() + if err > 1e-3: + raise RuntimeError("render_uo_layer: camera does not put the anchor on %s (off by %.4f px)" % (ANCHOR, err)) + return old + + +def atlas_map(w, h, dx, dy): + """The body material (UO_Skin, nodes UOX_*) reads the atlas of original frames with the window coordinates of the 136x120 + frame. Two Math nodes (UOC_x, UOC_y) turn the window coordinates of a w x h canvas into those of the original frame, + which sits at offset (dx, dy) in it. Identity for 136x120 / (68, 86).""" + for m in bpy.data.materials: + nt = m.node_tree + if not nt or "UOX_sep" not in nt.nodes: + continue + for name, src, dst, dst_in, mul, add in ( + ("UOC_x", "X", "UOX_u0", 1, w / OW, -dx / OW), + ("UOC_y", "Y", "UOX_v0", 0, h / OH, 1 - h / OH + dy / OH)): + n = nt.nodes.get(name) + if n is None: + n = nt.nodes.new("ShaderNodeMath"); n.name = n.label = name; n.operation = "MULTIPLY_ADD" + n.location = (nt.nodes[dst].location.x - 200, nt.nodes[dst].location.y + 120) + nt.links.new(nt.nodes["UOX_sep"].outputs[src], n.inputs[0]) + nt.links.new(n.outputs[0], nt.nodes[dst].inputs[dst_in]) + n.inputs[1].default_value, n.inputs[2].default_value = mul, add + + +cam_state = place_camera() +atlas_map(W, H, DX, DY) +sc.render.film_transparent = True +sc.render.image_settings.file_format = "PNG" +sc.render.image_settings.color_mode = "RGBA" +sc.view_settings.view_transform = "Standard" +sc["uo_look"] = 1.0 # UO lighting (see node group "UO_Look") +sc["uo_exact"] = 1.0 if (EXACT_COLORS and "UO_Original_Atlas" in bpy.data.images) else 0.0 # no atlas -> model colours +EXACT_ANY = EXACT_COLORS or EXACT_BODY +if EXACT_ANY and sc.render.engine == "CYCLES": + sc.cycles.pixel_filter_type = "BOX" # one sample point per pixel centre, like the UO art (no blur) + sc.cycles.filter_width = 0.01 + sc.cycles.use_denoising = False + sc.cycles.samples = 1 # 1 sample = exactly the pixel centre (the UO shading is noise-free) +ORIG = {} +if EXACT_ANY and "uo_original_frames.json" in bpy.data.texts: + import base64, zlib + ORIG = json.loads(bpy.data.texts["uo_original_frames.json"].as_string()) + + +def original(a, i, d): + """original UO body frame (uint8 RGBA, CANVAS size, anchor aligned) or None""" + v = ORIG.get("frames", {}).get("%d,%d,%d" % (a, i, d)) if ORIG else None + if v is None: + return None + return to_canvas(np.frombuffer(zlib.decompress(base64.b64decode(v)), np.uint8).reshape(OH, OW, 4)) + + +def set_tile(a, i, d): + t = ORIG.get("tiles", {}).get("%d,%d,%d" % (a, i, d)) if ORIG else None + sc["uo_tile_col"], sc["uo_tile_row"] = (t if t else (0, 0)) + +horses = {o.name: o for o in bpy.data.objects if o.name.startswith("Horse_")} +for o in horses.values(): + o.hide_render = True + o.is_holdout = True + + +HORSE_MASKS = {} # exact horse sprite silhouettes: only there can the horse hide anything +if "uo_horse_masks.json" in bpy.data.texts: + import base64, zlib + for k, v in json.loads(bpy.data.texts["uo_horse_masks.json"].as_string())["masks"].items(): + bits = np.unpackbits(np.frombuffer(zlib.decompress(base64.b64decode(v)), np.uint8))[:OH * OW] + HORSE_MASKS[tuple(int(x) for x in k.split(","))] = to_canvas(bits.reshape(OH, OW).astype(bool), False) + + +def set_horse(a, i): + for o in horses.values(): + o.hide_render = True + o = horses.get("Horse_a%d_f%d" % (a, i)) if HORSE_HOLDOUT else None + if o is not None: # the horse proxy made for exactly this mounted frame + o.hide_render = False + + +state = dict(holdout=body.is_holdout, body_hide=body.hide_render, cloth={o.name: o.hide_render for o in clothes}, + action=rig.animation_data.action, direction=rig.get("uo_direction", 0), pose=rig.data.pose_position) +rig.data.pose_position = "POSE" # the actions only play in Pose Position +body.hide_render = False +body.is_holdout = LAYER == "clothing" +for o in clothes: + o.hide_render = LAYER == "body" +if LAYER == "clothing" and not any(not o.hide_render for o in clothes): + raise RuntimeError("No visible meshes in the 'Clothing' collection") + + +def uo_post(px, keep=None): + """float RGBA (h,w,4), straight alpha -> UO look: over black, 1-bit alpha, dark outline. Returns uint8 RGBA. + keep: pixels that already carry original UO colours (no extra outline).""" + a = px[..., 3:4] + rgb = px[..., :3] * a + m = px[..., 3] >= 0.5 + inner = m.copy() + inner[1:] &= m[:-1]; inner[:-1] &= m[1:]; inner[:, 1:] &= m[:, :-1]; inner[:, :-1] &= m[:, 1:] + edge = m & ~inner + if keep is not None: + edge &= ~keep + rgb[keep & m] = px[..., :3][keep & m] + rgb[edge] *= OUTLINE + out = np.zeros(px.shape, np.uint8) + out[..., :3] = np.clip(rgb * 255 + 0.5, 0, 255).astype(np.uint8) + out[..., 3] = m * 255 + out[~m, :3] = 0 + return out + + +def render_px(): + sc.render.filepath = tmp + bpy.ops.render.render(write_still=True) + im = bpy.data.images.load(tmp) + w, h = im.size + px = np.empty(w * h * 4, np.float32); im.pixels.foreach_get(px) + bpy.data.images.remove(im) + return px.reshape(h, w, 4)[::-1] # Blender pixels start at the bottom row + + +def body_part_mask(parts): + """body triangles (loop_triangles order) whose dominant bone is one of `parts` (names without .L / .R)""" + me = body.data + sub = {"upper_arm_twist": "upper_arm", "forearm_twist": "forearm", "toe": "foot"} # v13 extra bones + names = [g.name.split(".")[0] for g in body.vertex_groups] + names = ["hand" if n.startswith("finger") else sub.get(n, n) for n in names] + W = np.zeros((len(me.vertices), len(names))) + for v in me.vertices: + for g in v.groups: + W[v.index, g.group] = g.weight + me.calc_loop_triangles() + tri = np.array([t.vertices[:] for t in me.loop_triangles]) + dom = W[tri].sum(1).argmax(1) + return np.array([names[k] in parts for k in dom]) + + +def worn_parts(share=0.04): + """body parts (names without .L / .R) the visible items are skinned to: an item wraps them, so they never hide it. + A part counts when it carries at least `share` of an item's total skin weight. Rigid items (one bone: weapons, shields, + quivers) wrap nothing, except on the head (hair, hats), which they sit on.""" + sub = {"upper_arm_twist": "upper_arm", "forearm_twist": "forearm", "toe": "foot"} + out = set() + for o in clothes: + if o.hide_render or not o.vertex_groups: + continue + names = [g.name.split(".")[0] for g in o.vertex_groups] + names = ["hand" if n.startswith("finger") else sub.get(n, n) for n in names] + tot = {} + for v in o.data.vertices: + for g in v.groups: + tot[names[g.group]] = tot.get(names[g.group], 0.0) + g.weight + if len(o.vertex_groups) == 1: + out |= {p for p in tot if p == "head"} + continue + s = sum(tot.values()) + out |= {p for p, w in tot.items() if s > 0 and w / s >= share} + return out + + +WORN = worn_parts() if (LAYER == "clothing" and OWN_PARTS_NEVER_HIDE) else set() +OCCLUDER_TRIS = body_part_mask(set(OCCLUDERS)) # parts BODY_GAP keeps the items away from +HIDER_TRIS = body_part_mask(set(OCCLUDERS) - WORN) # parts that may hide an item in the holdout +CLOAK_WORN = any(g.name.startswith("cloak_") for o in clothes if not o.hide_render for g in o.vertex_groups) +TORSO_TRIS = body_part_mask({"pelvis", "spine", "chest", "neck", "clavicle"}) if (TORSO_HIDE_MARGIN > 0 and CLOAK_WORN and LAYER == "clothing") else None +print("render_uo_layer: items wrap %s; body parts that may hide them: %s" % (sorted(WORN), sorted(set(OCCLUDERS) - WORN))) + + +def raster(objs, tri_mask=None): + """pixel coverage and camera depth (m) of the deformed meshes through UO_Camera, pixel-centre rule (like the + EXACT render). Returns (bool H x W, float H x W with inf where nothing is). tri_mask: triangles to use.""" + rig.update_tag(); body.update_tag(); bpy.context.view_layer.update() + dg = bpy.context.evaluated_depsgraph_get() + cam = sc.camera.evaluated_get(dg) + Pm = np.array(cam.calc_matrix_camera(dg, x=W, y=H)); Vm = np.array(cam.matrix_world.inverted()) + img = np.zeros((H, W), bool); depth = np.full((H, W), np.inf) + for ob in objs: + ev = ob.evaluated_get(dg); me = ev.to_mesh() + co = np.empty(len(me.vertices) * 3, np.float32); me.vertices.foreach_get("co", co); co = co.reshape(-1, 3) + me.calc_loop_triangles() + tri = np.empty(len(me.loop_triangles) * 3, np.int32); me.loop_triangles.foreach_get("vertices", tri); tri = tri.reshape(-1, 3) + if tri_mask is not None and len(tri_mask) == len(tri): + tri = tri[tri_mask] + Mw = np.array(ev.matrix_world) + ev.to_mesh_clear() + hv = np.c_[co, np.ones(len(co))] @ (Vm @ Mw).T # camera space + h = hv @ Pm.T + ndc = h[:, :2] / h[:, 3:4] + P = np.stack([(ndc[:, 0] + 1) * 0.5 * W, (1 - ndc[:, 1]) * 0.5 * H], 1)[tri] + Z = -hv[:, 2][tri] + mn = np.floor(P.min(1)).astype(int); mx = np.ceil(P.max(1)).astype(int) + A, B, C = P[:, 0], P[:, 1], P[:, 2] + den = (B[:, 1] - C[:, 1]) * (A[:, 0] - C[:, 0]) + (C[:, 0] - B[:, 0]) * (A[:, 1] - C[:, 1]) + ok = np.abs(den) > 1e-12; size = np.clip(mx - mn, 0, 16) + for dy in range(int(size[:, 1].max(initial=0)) + 1): + for dx in range(int(size[:, 0].max(initial=0)) + 1): + t = np.nonzero(ok & (dx <= size[:, 0]) & (dy <= size[:, 1]))[0] + px_ = mn[t, 0] + dx; py_ = mn[t, 1] + dy; cx, cy = px_ + 0.5, py_ + 0.5 + l0 = ((B[t, 1] - C[t, 1]) * (cx - C[t, 0]) + (C[t, 0] - B[t, 0]) * (cy - C[t, 1])) / den[t] + l1 = ((C[t, 1] - A[t, 1]) * (cx - C[t, 0]) + (A[t, 0] - C[t, 0]) * (cy - C[t, 1])) / den[t] + k = (l0 >= -1e-4) & (l1 >= -1e-4) & (1 - l0 - l1 >= -1e-4) & (px_ >= 0) & (py_ >= 0) & (px_ < W) & (py_ < H) + img[py_[k], px_[k]] = True + z = l0[k] * Z[t[k], 0] + l1[k] * Z[t[k], 1] + (1 - l0[k] - l1[k]) * Z[t[k], 2] + np.minimum.at(depth, (py_[k], px_[k]), z) + return img, depth + + +def body_coverage(): + """pixels covered by the (deformed) body mesh through UO_Camera, pixel-centre rule (like the EXACT render)""" + return raster([body])[0] + + +def body_occlusion(free, margin): + """the clothing render without the body, with the body in front of the item removed. The body hides a pixel only + where it is more than `margin` in front of the visible item surface. Returns (hold, body coverage).""" + cov, _ = raster([body]) + occ, zb = raster([body], HIDER_TRIS) # only the parts that may hide items (not the torso) + _, zi = raster([o for o in clothes if not o.hide_render]) + seen = free[..., 3] >= 0.5 + for _ in range(2): # item pixels Cycles drew but the raster missed: neighbour depth + miss = seen & np.isinf(zi) + if not miss.any(): + break + pad = np.pad(zi, 1, constant_values=np.inf) + nb = np.min([pad[y:y + H, x:x + W] for y in range(3) for x in range(3)], axis=0) + zi = np.where(miss, nb, zi) + hold = free.copy() + hold[occ & (zb < zi - margin)] = 0.0 + if TORSO_TRIS is not None: # items behind the torso (cloak): clearly behind = hidden + occt, zt = raster([body], TORSO_TRIS) + hold[occt & (zt < zi - TORSO_HIDE_MARGIN)] = 0.0 + return hold, cov + + +def render_frame(a, i, d, body_mode): + """body_mode: 'visible' | 'holdout' | 'hidden'. Includes the horse holdout of mounted actions.""" + body.hide_render = body_mode == "hidden" + body.is_holdout = body_mode == "holdout" + set_horse(a, i) + px = render_px() + hm = HORSE_MASKS.get((a, i, d)) if HORSE_HOLDOUT else None + if hm is not None and horses.get("Horse_a%d_f%d" % (a, i)) is not None: + set_horse(-1, 0) # outside the horse sprite nothing is hidden + px = np.where(hm[..., None], px, render_px()) + return px + + +def binary_dilation(m, iterations=1): + """4-neighbour dilation (same result as scipy.ndimage.binary_dilation), numpy only.""" + for _ in range(iterations): + d = m.copy() + d[1:] |= m[:-1] + d[:-1] |= m[1:] + d[:, 1:] |= m[:, :-1] + d[:, :-1] |= m[:, 1:] + m = d + return m + + +def fill_small_holes(px, free, max_px): + """transparent patches up to max_px fully surrounded by the item are filled: with the item from the render without + the body (skin poking through) or, where the item mesh itself leaves a gap, with the colour of the item around it""" + a = px[..., 3] >= 0.5 + H, W = a.shape + outside = np.zeros_like(a) + outside[0, :] = outside[-1, :] = outside[:, 0] = outside[:, -1] = True + outside &= ~a + while True: # transparent pixels connected to the image border + g = outside.copy() + g[1:] |= outside[:-1]; g[:-1] |= outside[1:]; g[:, 1:] |= outside[:, :-1]; g[:, :-1] |= outside[:, 1:] + g &= ~a + if (g == outside).all(): + break + outside = g + hole = ~a & ~outside + seen = np.zeros_like(hole) + for y, x in zip(*np.nonzero(hole)): + if seen[y, x]: + continue + comp, stack = [], [(y, x)] + seen[y, x] = True + while stack: + cy, cx = stack.pop() + comp.append((cy, cx)) + for ny, nx in ((cy - 1, cx), (cy + 1, cx), (cy, cx - 1), (cy, cx + 1)): + if 0 <= ny < H and 0 <= nx < W and hole[ny, nx] and not seen[ny, nx]: + seen[ny, nx] = True + stack.append((ny, nx)) + if len(comp) > max_px: + continue # a real opening (e.g. an arm in front of the chest) + todo = [] + for cy, cx in comp: + if free[cy, cx, 3] >= 0.5: + px[cy, cx] = free[cy, cx] + else: + todo.append((cy, cx)) + for _ in range(max_px): # mesh gap: colour of the neighbouring item pixels + left = [] + for cy, cx in todo: + nb = [px[ny, nx] for ny, nx in ((cy - 1, cx), (cy + 1, cx), (cy, cx - 1), (cy, cx + 1)) + if 0 <= ny < H and 0 <= nx < W and px[ny, nx, 3] >= 0.5] + if nb: + px[cy, cx] = np.mean(nb, axis=0); px[cy, cx, 3] = 1.0 + else: + left.append((cy, cx)) + todo = left + if not todo: + break + return px + + +def despeckle(img, thr, passes=2): + """uint8 RGBA: dark single pixels inside the item (not its outline) -> colour of their non-dark neighbours""" + out = img.copy(); m = out[..., 3] > 0; H, W = m.shape + offs = [(y, x) for y in range(3) for x in range(3) if (y, x) != (1, 1)] + for _ in range(passes): + rgb = out[..., :3].astype(float) + lum = rgb.mean(-1) + pad = np.pad(rgb, ((1, 1), (1, 1), (0, 0)), mode="edge"); pm = np.pad(m, 1) + stack = np.stack([pad[y:y + H, x:x + W] for y, x in offs], 0) + valid = np.stack([pm[y:y + H, x:x + W] for y, x in offs], 0) + sl = stack.mean(-1) + srt = np.sort(np.where(valid, sl, np.inf), axis=0) + n = valid.sum(0) + lo = np.take_along_axis(srt, np.clip((n - 1) // 2, 0, 7)[None], 0)[0] + hi = np.take_along_axis(srt, np.clip(n // 2, 0, 7)[None], 0)[0] + med = np.where(np.isfinite(hi), (lo + hi) / 2, lo) + dark = m & (n >= 7) & (lum < med - thr) + if not dark.any(): + break + ok = valid & (sl >= (med - thr / 2)[None]) + w = ok.sum(0) + fill = (stack * ok[..., None]).sum(0) / np.maximum(w, 1)[..., None] + sel = dark & (w > 0) + out[sel, :3] = np.clip(fill[sel] + 0.5, 0, 255).astype(np.uint8) + return out + + +def drop_small_pieces(img, min_px): + """uint8 RGBA: detached pieces of the item (8-connected) smaller than min_px -> transparent, except the biggest""" + m = img[..., 3] > 0; H, W = m.shape + seen = np.zeros_like(m); pieces = [] + for y0, x0 in zip(*np.nonzero(m)): + if seen[y0, x0]: + continue + comp = [(y0, x0)]; seen[y0, x0] = True; k = 0 + while k < len(comp): + cy, cx = comp[k]; k += 1 + for ny in (cy - 1, cy, cy + 1): + for nx in (cx - 1, cx, cx + 1): + if 0 <= ny < H and 0 <= nx < W and m[ny, nx] and not seen[ny, nx]: + seen[ny, nx] = True + comp.append((ny, nx)) + pieces.append(comp) + out = img.copy() + big = max(pieces, key=len) if pieces else None + for comp in pieces: + if len(comp) < min_px and comp is not big: + ys, xs = zip(*comp) + out[list(ys), list(xs)] = 0 + return out + + +def exact_clothing(hold, free, orig_body, cov): + """Hide the item exactly where the ORIGINAL body is in front of it; the 3D model decides front/behind.""" + a_h, a_f = hold[..., 3] >= 0.5, free[..., 3] >= 0.5 + hidden = a_f & ~a_h # the model body hides the item here + out = free.copy() # outside the original body nothing hides the item + use_hold = orig_body & cov + out[use_hold] = hold[use_hold] + rim = orig_body & ~cov & binary_dilation(hidden, iterations=2) # thin rim the model body does not reach + out[rim] = 0.0 + return out + + +root = bpy.path.abspath(OUT_DIR + LAYER + "/") +tmp = os.path.join(root, "_tmp.png") +os.makedirs(root, exist_ok=True) +if os.path.exists(os.path.join(root, "STOP")): + os.remove(os.path.join(root, "STOP")) # a leftover STOP from a cancelled run +blocks, meta_blocks = {}, [] +acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) +todo = [a for a in acts if not ONLY or a.name in ONLY] +total_frames = sum(int(a["uo_frames"]) * 5 for a in todo) +view_prefs = bpy.context.preferences.view +render_display = view_prefs.render_display_type + + +def frame_job(): + """one UO frame per step; uo_job.py hands control back to Blender between two of them (the window stays alive, ESC cancels)""" + view_prefs.render_display_type = "NONE" # no Render Result window popping up for every frame + done_frames = 0 + try: + for act in acts: + if ONLY and act.name not in ONLY: + continue + a = int(act["uo_action"]) + rig.animation_data.action = act + for d in range(5): + rig["uo_direction"] = d + rig.update_tag() + fdir = os.path.join(root, "frames", act.name, "dir%d" % d) + os.makedirs(fdir, exist_ok=True) + frames, meta_frames = [], [] + for i in range(int(act["uo_frames"])): + if os.path.exists(os.path.join(root, "STOP")): # create an empty file named STOP to cancel + raise KeyboardInterrupt("STOP file found in " + root) + set_tile(a, i, d) + sc.frame_set(1 + i * STEP) + for o in clothes: + if o.name in CLOTH: + cloth_show(o, a, i) + if BODY_GAP > 0 and LAYER != "body": + body_fix(a, i) + orig = original(a, i, d) if EXACT_ANY else None + orig_m = orig[..., 3] > 0 if orig is not None else None + if LAYER == "body" and EXACT_BODY and orig is not None: + rgba = orig # the original UO body frame, pixel for pixel + elif LAYER == "clothing" and HOLDOUT_MARGIN > 0: + free = render_frame(a, i, d, "hidden") + hold, cov = body_occlusion(free, HOLDOUT_MARGIN) + px = exact_clothing(hold, free, orig_m, cov) if (EXACT_BODY and orig is not None) else hold + if FILL_HOLES > 0: + px = fill_small_holes(px, free, FILL_HOLES) + rgba = uo_post(px) + if DESPECKLE > 0: + rgba = despeckle(rgba, DESPECKLE) + if MIN_PIECE > 0: + rgba = drop_small_pieces(rgba, MIN_PIECE) + elif LAYER == "clothing": + px = render_frame(a, i, d, "holdout") + if EXACT_BODY and orig is not None: + px = exact_clothing(px, render_frame(a, i, d, "hidden"), orig_m, body_coverage()) + rgba = uo_post(px) + if MIN_PIECE > 0: + rgba = drop_small_pieces(rgba, MIN_PIECE) + else: + px = render_frame(a, i, d, "visible") + rgba = uo_post(px, keep=orig_m if (EXACT_COLORS and orig_m is not None) else None) + h, w = rgba.shape[:2] + frames.append(rgba) + png = bpy.data.images.new("uo_tmp_out", w, h, alpha=True) + png.pixels.foreach_set((rgba[::-1].astype(np.float32) / 255.0).ravel()) + png.filepath_raw = os.path.join(fdir, "%02d.png" % i); png.file_format = "PNG"; png.save() + bpy.data.images.remove(png) + meta_frames.append(dict(file="%02d.png" % i)) + done_frames += 1 + yield "%d / %d frames (%s, direction %d)" % (done_frames, total_frames, act.name, d) + blocks[(a, d)] = frames + meta_blocks.append(dict(action=a, dir=d, name=act.name, frames=meta_frames)) + finally: + fix_clear() # items back to bound, also after STOP / an error / ESC + + +def restore_all(): + view_prefs.render_display_type = render_display + set_horse(-1, 0) + for o in clothes: + if o.name in CLOTH: + cloth_show(o, -1, 0) # back to the bound item + body.is_holdout, body.hide_render = state["holdout"], state["body_hide"] + for o in clothes: + o.hide_render = state["cloth"][o.name] + rig.animation_data.action, rig["uo_direction"] = state["action"], state["direction"] + rig.data.pose_position = state["pose"] + cd = sc.camera.data + cd.sensor_fit, cd.ortho_scale, cd.shift_x, cd.shift_y = cam_state # camera and atlas mapping of the 136x120 file + atlas_map(OW, OH, 0, 0) + sc.render.resolution_x, sc.render.resolution_y = OW, OH + + +def finish(): + global meta_blocks + if os.path.exists(tmp): + os.remove(tmp) + # actions rendered in EARLIER runs into the same folder are kept: each run can use a different item setup (e.g. another + # grip for some actions) and the final .vd contains every action whose frames are on disk + names = {int(a["uo_action"]): a.name for a in acts} + for act in acts: + a = int(act["uo_action"]) + for d in range(5): + if (a, d) in blocks: + continue + fdir = os.path.join(root, "frames", act.name, "dir%d" % d) + files = ["%02d.png" % i for i in range(int(act["uo_frames"]))] + if not all(os.path.exists(os.path.join(fdir, f)) for f in files): + continue + frames = [] + for f in files: + im = bpy.data.images.load(os.path.join(fdir, f)); w, h = im.size + px = np.empty(w * h * 4, np.float32); im.pixels.foreach_get(px); bpy.data.images.remove(im) + frames.append(np.clip(px.reshape(h, w, 4)[::-1] * 255 + 0.5, 0, 255).astype(np.uint8)) + blocks[(a, d)] = frames + meta_blocks.append(dict(action=a, dir=d, name=act.name, frames=[dict(file=f) for f in files])) + print("actions in this .vd:", sorted({a for a, _ in blocks})) + # vdtool-compatible meta.json (canvas mode) so the PNGs can also be packed with: python vdtool.py pack out.vd + done_blocks = {(b["action"], b["dir"]): b for b in meta_blocks} + meta_blocks = [done_blocks.get((a, d), dict(action=a, dir=d, name=names.get(a, "action"), frames=[])) + for a in range(35) for d in range(5)] + with open(os.path.join(root, "meta.json"), "w") as fh: + json.dump(dict(tool="render_uo_layer", anim_type=2, actions=35, mode="canvas", canvas=[W, H], + anchor=list(ANCHOR), blocks=meta_blocks), fh, indent=1) + if WRITE_VD: + vd_path = bpy.path.abspath(VD_FILE % LAYER) + writer.write_vd(vd_path, blocks, anim_type=2, anchor=ANCHOR) + print("wrote", vd_path) + + restore_all() + print("done ->", root) + + +def abort(why): + restore_all() + print("render_uo_layer: %s - nothing written to the .vd (the frames already rendered stay in %s)" % (why, root)) + + +# Blender's window: a long loop inside "Run Script" freezes it ("Not Responding"), so in the interface the frames are rendered +# step by step from a modal operator (uo_job.py: progress in the status bar, ESC cancels). Without the text: a plain loop. +if "uo_job.py" in bpy.data.texts: + bpy.data.texts["uo_job.py"].as_module().run(frame_job(), "render_uo_layer", finish, abort) +else: + try: + for _ in frame_job(): + pass + except BaseException: + abort("error") + raise + finish() diff --git a/third_party/UO_Model3D_v13/pipeline/rig.py b/third_party/UO_Model3D_v13/pipeline/rig.py new file mode 100644 index 0000000..23b3291 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/rig.py @@ -0,0 +1,87 @@ +"""Blender armature matching the fitted skeleton + conversion of fitted poses to pose-bone rotations.""" +import numpy as np +import bpy +from mathutils import Matrix, Vector, Quaternion +from body import JI, JOINTS, ARM_REST_ANGLE + +# joint -> (bone name, tail joint or callable, parent bone, align-roll Z vector) +FWD = (0.0, -1.0, 0.0) +UP = (0.0, 0.0, 1.0) + + +def bone_defs(S, P): + S = {k: np.asarray(v, np.float64) for k, v in S.items()} + sa, ca = np.sin(ARM_REST_ANGLE), np.cos(ARM_REST_ANGLE) + J = lambda n: P[JI[n]] + head_top = J("head") + np.array([0, 0, S["head_c"][2] + S["head_r"][2]]) + defs = [ + # name, joint, head, tail, parent, roll_z + ("pelvis", "pelvis", J("pelvis"), J("spine"), None, FWD), + ("spine", "spine", J("spine"), J("chest"), "pelvis", FWD), + ("chest", "chest", J("chest"), J("neck"), "spine", FWD), + ("neck", "neck", J("neck"), J("head"), "chest", FWD), + ("head", "head", J("head"), head_top, "neck", FWD), + ] + for side, sx in (("L", 1), ("R", -1)): + d = np.array([sx * sa, 0, -ca]) + defs += [ + ("upper_arm." + side, "shoulder." + side, J("shoulder." + side), J("elbow." + side), "chest", FWD), + ("forearm." + side, "elbow." + side, J("elbow." + side), J("wrist." + side), "upper_arm." + side, FWD), + ("hand." + side, "wrist." + side, J("wrist." + side), J("wrist." + side) + d * S["hand"], "forearm." + side, FWD), + ("thigh." + side, "hip." + side, J("hip." + side), J("knee." + side), "pelvis", FWD), + ("shin." + side, "knee." + side, J("knee." + side), J("ankle." + side), "thigh." + side, FWD), + ("foot." + side, "ankle." + side, J("ankle." + side), + J("ankle." + side) + np.array([0, -S["foot_len"] + S["heel_y"], -S["ankle_h"] + S["foot_r"][1]]), + "shin." + side, UP), + ] + return defs + + +def build_armature(S, P, name="UO_Rig"): + arm = bpy.data.armatures.new(name) + ob = bpy.data.objects.new(name, arm) + bpy.context.scene.collection.objects.link(ob) + bpy.context.view_layer.objects.active = ob + ob.select_set(True) + bpy.ops.object.mode_set(mode="EDIT") + defs = bone_defs(S, P) + for bname, joint, h, t, parent, rz in defs: + eb = arm.edit_bones.new(bname) + eb.head = Vector(h) + eb.tail = Vector(t) + eb.align_roll(Vector(rz)) + if parent: + eb.parent = arm.edit_bones[parent] + eb.use_connect = bool(np.allclose(arm.edit_bones[parent].tail, eb.head, atol=1e-5)) + bpy.ops.object.mode_set(mode="OBJECT") + arm.display_type = "OCTAHEDRAL" + ob.show_in_front = True + return ob, {b[0]: b[1] for b in defs} + + +def rodrigues_np(r): + th = np.linalg.norm(r) + if th < 1e-9: + return np.eye(3) + k = r / th + K = np.array([[0, -k[2], k[1]], [k[2], 0, -k[0]], [-k[1], k[0], 0]]) + return np.eye(3) + np.sin(th) * K + (1 - np.cos(th)) * K @ K + + +def apply_pose(arm_ob, bone_joint, pose_rot, trans): + """pose_rot: (NJ,3) axis-angle local rotations in world-aligned rest frames; trans: root translation.""" + for pb in arm_ob.pose.bones: + if pb.name not in bone_joint: # helper bones (clavicles): rest unless set by the caller + pb.rotation_mode = "QUATERNION" + pb.rotation_quaternion = (1, 0, 0, 0) + pb.location = (0, 0, 0) + continue + j = JI[bone_joint[pb.name]] + B = np.array(pb.bone.matrix_local.to_3x3()) + L = B.T @ rodrigues_np(np.asarray(pose_rot[j])) @ B + pb.rotation_mode = "QUATERNION" + pb.rotation_quaternion = Matrix(L.tolist()).to_quaternion() + if pb.parent is None: + pb.location = Vector((B.T @ np.asarray(trans)).tolist()) + else: + pb.location = (0, 0, 0) diff --git a/third_party/UO_Model3D_v13/pipeline/run_anims.py b/third_party/UO_Model3D_v13/pipeline/run_anims.py new file mode 100644 index 0000000..3cdb93f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/run_anims.py @@ -0,0 +1,115 @@ +"""Fit per-frame skeleton poses for every action (shape fixed from shape_fit.pkl).""" +import sys, time, pickle, os +import numpy as np +import jax, jax.numpy as jnp, optax +from PIL import Image +from body import * +from fit import * +from targets import targets +from vd import ACTIONS_PEOPLE +from viz import overlay_row + +sf = pickle.load(open("shape_fit.pkl", "rb")) +fixed = {k: jnp.asarray(v) for k, v in sf["fixed"].items()} +S = params_to_shape({k: jnp.asarray(v) for k, v in sf["params"]["shape"].items()}, fixed) +stand_pose = jax.tree.map(lambda x: jnp.asarray(x[0]), sf["params"]["poses"]) + +CYCLIC = {0, 1, 2, 3, 23, 24} +MOUNTED = set(range(23, 30)) +INIT_FROM = {1: 0, 3: 2, 24: 23, 8: 7} +ORDER = [4, 5, 6, 0, 1, 2, 3, 7, 8, 15, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 30, 31, 32, 33, 34, + 23, 24, 25, 26, 27, 28, 29] +out_path = "anim_fit.pkl" +results = pickle.load(open(out_path, "rb")) if os.path.exists(out_path) else {} +only = [int(a) for a in sys.argv[1:]] or ORDER + + +def mounted_init(): + p = jax.tree.map(lambda x: x, stand_pose) + bi = {j: i for i, j in enumerate(BALL_IDX)} + hi = {j: i for i, j in enumerate(HINGE_IDX)} + ball = np.asarray(p["ball"]).copy(); hinge = np.asarray(p["hinge"]).copy() + ball[bi[JI["hip.L"]]] = [-1.3, -0.5, 0.0] # thighs forward (about X) and spread outward (about Y) + ball[bi[JI["hip.R"]]] = [-1.3, 0.5, 0.0] + hinge[hi[JI["knee.L"]]] = 1.3 + hinge[hi[JI["knee.R"]]] = 1.3 + return dict(ball=jnp.asarray(ball), hinge=jnp.asarray(hinge), trans=jnp.asarray([0.0, 0.0, 0.45])) + + +for a in only: + if a in results: + continue + t0 = time.time() + T = targets(a) + F = len(T) + Anp = T[..., 3].astype(np.float32) / 255.0 + y0, y1, x0, x1 = crop_box(Anp) + A = jnp.asarray(Anp[..., y0:y1, x0:x1]) + pix = PIX[y0:y1, x0:x1] + gw = 0.0 if a in MOUNTED else 1.0 + + single = jax.jit(jax.value_and_grad(lambda pp, al: frame_loss(S, pp, al, gw, pix=pix)[0])) + opt = optax.adam(0.02) + + if a in INIT_FROM and INIT_FROM[a] in results: + src = results[INIT_FROM[a]]["poses"] + inits = [jax.tree.map(lambda x: jnp.asarray(x[min(i, x.shape[0] - 1)]), src) for i in range(F)] + else: + inits = [mounted_init() if a in MOUNTED else stand_pose] + [None] * (F - 1) + + # --- sequential pass: each frame starts from the previous frame's solution + poses = [] + prev = None + for i in range(F): + pp = inits[i] if inits[i] is not None else prev + st = opt.init(pp) + for it in range(350): + l, g = single(pp, A[i]) + up, st = opt.update(g, st, pp) + pp = optax.apply_updates(pp, up) + poses.append(pp) + prev = pp + + # --- joint refinement with temporal smoothness + batch = jax.tree.map(lambda *xs: jnp.stack(xs), *poses) + cyc = a in CYCLIC + + def joint_loss(bp): + f = jax.vmap(lambda pp, al: frame_loss(S, pp, al, gw, pix=pix)) + l, d = f(bp, A) + sm = 0.0 + if F > 1: + for k in ("ball", "hinge", "trans"): + x = bp[k] + diff = x[1:] - x[:-1] + sm += jnp.sum(diff ** 2) + if cyc: + sm += jnp.sum((x[0] - x[-1]) ** 2) * 0.5 + return jnp.sum(l) + 0.05 * sm, jnp.sum(d) + jvg = jax.jit(jax.value_and_grad(joint_loss, has_aux=True)) + opt2 = optax.adam(optax.exponential_decay(0.01, 300, 0.3)) + st = opt2.init(batch) + for it in range(300): + (l, d), g = jvg(batch) + up, st = opt2.update(g, st, batch) + batch = optax.apply_updates(batch, up) + (l, d), _ = jvg(batch) + per_frame = [] + for i in range(F): + pp = jax.tree.map(lambda x: x[i], batch) + per_frame.append(float(frame_loss(S, pp, A[i], gw, pix=pix)[1])) + results[a] = dict(poses=jax.tree.map(np.asarray, batch), data_loss=per_frame, crop=(y0, y1, x0, x1)) + pickle.dump(results, open(out_path, "wb")) + # QA overlay + rows = [] + for i in range(F): + pose = pose_from_params(jax.tree.map(lambda x: x[i], batch)) + P, R = fk(S, pose) + rows.append(overlay_row(T[i][:, y0:y1, x0:x1], [render_sil(S, P, R, dd, pix=pix) for dd in range(5)], zoom=3)) + im = Image.new("RGB", (rows[0].width, sum(r.height for r in rows))) + yy = 0 + for r in rows: + im.paste(r, (0, yy)); yy += r.height + os.makedirs("qa", exist_ok=True) + im.save(f"qa/a{a:02d}_{ACTIONS_PEOPLE[a]}.png") + print(f"action {a:2d} {ACTIONS_PEOPLE[a]:24s} frames={F} data={np.mean(per_frame):.3f} max={np.max(per_frame):.3f} {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/run_anims2.py b/third_party/UO_Model3D_v13/pipeline/run_anims2.py new file mode 100644 index 0000000..991a7af --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/run_anims2.py @@ -0,0 +1,233 @@ +"""Per-frame pose fitting with chamfer (distance-transform) terms and coarse-to-fine blur. +Limb identity is never swapped: every frame starts from the previous frame (frame 0 from the stand pose).""" +import sys, time, pickle, os +import numpy as np +import jax, jax.numpy as jnp, optax +from scipy.ndimage import distance_transform_edt +from PIL import Image +from body import * +from fit import * +from targets import targets +from vd import ACTIONS_PEOPLE +from viz import overlay_row + +sf = pickle.load(open("shape_fit.pkl", "rb")) +fixed = {k: jnp.asarray(v) for k, v in sf["fixed"].items()} +S = params_to_shape({k: jnp.asarray(v) for k, v in sf["params"]["shape"].items()}, fixed) +prev_res = pickle.load(open("anim_fit_run1.pkl", "rb")) +stand_pose = {k: jnp.asarray(v[0]) for k, v in prev_res[4]["poses"].items()} + +CYCLIC = {0, 1, 2, 3, 23, 24} +MOUNTED = set(range(23, 30)) +out_path = sys.argv[sys.argv.index("--out") + 1] if "--out" in sys.argv else "anim_fit2.pkl" +acts = [int(a) for a in sys.argv[1:] if a.isdigit()] +results = pickle.load(open(out_path, "rb")) if os.path.exists(out_path) else {} +FIRST_FROM = {9: 7, 10: 7, 11: 7, 18: 7, 19: 8, 12: 8, 13: 8, 14: 8} # frame 0 starts from the combat stance +PER_FRAME_FROM = {2: 0, 3: 0, 15: 0} # cycle starts from the fitted walk + + +def lookup(a): + for f in ("anim_fit2a.pkl", "anim_fit2b.pkl", out_path, "anim_fit_run1.pkl"): + if os.path.exists(f): + r = pickle.load(open(f, "rb")) + if a in r: + if f == "anim_fit_run1.pkl" and a not in (0, 1, 4, 5, 6, 16, 30, 31, 32, 34): + continue # only trust the good first-pass results + return r[a]["poses"] + return None + +BI = {j: i for i, j in enumerate(BALL_IDX)} +HI = {j: i for i, j in enumerate(HINGE_IDX)} +MIR = jnp.array([1.0, -1.0, -1.0]) + + +def swap(pp, balls, hinges): + b, h = pp["ball"], pp["hinge"] + for l in balls: + il, ir = BI[JI[l + ".L"]], BI[JI[l + ".R"]] + bl, br = b[il], b[ir] + b = b.at[il].set(br * MIR).at[ir].set(bl * MIR) + for l in hinges: + il, ir = HI[JI[l + ".L"]], HI[JI[l + ".R"]] + hl, hr = h[il], h[ir] + h = h.at[il].set(hr).at[ir].set(hl) + return dict(ball=b, hinge=h, trans=pp["trans"]) + + +# Left/right hypotheses for the FIRST frame only. In the front (dir 0) and back (dir 4) views left and right limbs +# are on fixed screen sides and a forward foot is drawn lower, so these two views decide which limb is which. +LR_VARIANTS = { + "legs": lambda p: swap(p, ["hip", "ankle"], ["knee"]), + "arms": lambda p: swap(p, ["shoulder", "wrist"], ["elbow"]), + "both": lambda p: swap(p, ["hip", "ankle", "shoulder", "wrist"], ["knee", "elbow"]), +} + + +RIDE_LEGS = { # riding template: thighs forward and spread around the horse, knees bent + "hip.L": [-1.2, -0.55, 0.0], "hip.R": [-1.2, 0.55, 0.0], "ankle.L": [0.3, 0.0, 0.0], "ankle.R": [0.3, 0.0, 0.0]} +RIDE_KNEE = 1.4 +RIDE_IDX = np.array([BI[JI[j]] for j in RIDE_LEGS]) +RIDE_VAL = jnp.asarray(np.array(list(RIDE_LEGS.values())), jnp.float32) +KNEE_IDX = np.array([HI[JI["knee.L"]], HI[JI["knee.R"]]]) + + +def ride_prior(pp): + # UO rider sprites have the parts behind the horse removed, so the legs are held near a riding pose + return 8.0 * (jnp.sum((pp["ball"][RIDE_IDX] - RIDE_VAL) ** 2) + jnp.sum((pp["hinge"][KNEE_IDX] - RIDE_KNEE) ** 2)) + + +def mounted_init(): + ball = np.asarray(stand_pose["ball"]).copy(); hinge = np.asarray(stand_pose["hinge"]).copy() + for j, v in RIDE_LEGS.items(): + ball[BI[JI[j]]] = v + hinge[HI[JI["knee.L"]]] = RIDE_KNEE + hinge[HI[JI["knee.R"]]] = RIDE_KNEE + return dict(ball=jnp.asarray(ball), hinge=jnp.asarray(hinge), trans=jnp.asarray([0.0, 0.0, 0.45])) + + +LIMITS = { # joint: ((xlo,xhi),(ylo,yhi),(zlo,zhi)) on the axis-angle vector in the rest frame + "hip.L": ((-2.3, 0.6), (-0.9, 0.5), (-0.7, 0.7)), "hip.R": ((-2.3, 0.6), (-0.5, 0.9), (-0.7, 0.7)), + "ankle.L": ((-0.8, 0.8), (-0.5, 0.5), (-0.5, 0.5)), "ankle.R": ((-0.8, 0.8), (-0.5, 0.5), (-0.5, 0.5)), + "spine": ((-0.8, 0.8), (-0.6, 0.6), (-0.7, 0.7)), "chest": ((-0.8, 0.8), (-0.6, 0.6), (-0.7, 0.7)), + "neck": ((-0.8, 0.8), (-0.6, 0.6), (-0.9, 0.9)), "head": ((-0.8, 0.8), (-0.6, 0.6), (-0.9, 0.9)), + "wrist.L": ((-1.2, 1.2), (-1.2, 1.2), (-1.2, 1.2)), "wrist.R": ((-1.2, 1.2), (-1.2, 1.2), (-1.2, 1.2)), +} +LIM_IDX = np.array([BI[JI[j]] for j in LIMITS]) +LIM_LO = jnp.asarray(np.array([[r[0] for r in v] for v in LIMITS.values()]), jnp.float32) +LIM_HI = jnp.asarray(np.array([[r[1] for r in v] for v in LIMITS.values()]), jnp.float32) + + +def limit_penalty(pp): + b = pp["ball"][LIM_IDX] + return jnp.sum(jax.nn.relu(LIM_LO - b) ** 2 + jax.nn.relu(b - LIM_HI) ** 2) * 20.0 + + +def full_loss(pp, alpha, dt, gw, pix, tau, wch): + pose = pose_from_params(pp) + P, R = fk(S, pose) + occs, dmins = [], [] + for d in range(5): + o, dist = render_sil(S, P, R, d, tau=tau, return_parts=True, pix=pix) + occs.append(o); dmins.append(jnp.min(dist, 0)) + occ = jnp.stack(occs); dmin = jnp.stack(dmins) + data = jnp.mean((occ - alpha) ** 2) * 100.0 + cham = jnp.mean(occ * dt) + jnp.mean(alpha * jax.nn.relu(dmin)) + reg = 1e-3 * jnp.sum(pp["ball"] ** 2) + hinge_limit_penalty(pp["hinge"]) + limit_penalty(pp) + reg = reg + jnp.where(gw == 0.0, ride_prior(pp), 0.0) + mz = foot_min_z(S, P, R) + ground = gw * (mz ** 2) * 100.0 + 10.0 * jax.nn.relu(-mz - 0.01) ** 2 * 100 + return data + wch * cham + reg + ground, data + + +for a in acts: + t0 = time.time() + T = targets(a) + F = len(T) + Anp = T[..., 3].astype(np.float32) / 255.0 + y0, y1, x0, x1 = crop_box(Anp, margin=10) + A = Anp[..., y0:y1, x0:x1] + DT = np.stack([[distance_transform_edt(A[i, d] < 0.5) for d in range(5)] for i in range(F)]).astype(np.float32) + A = jnp.asarray(A); DT = jnp.asarray(DT) + pix = PIX[y0:y1, x0:x1] + gw = 0.0 if a in MOUNTED else 1.0 + coarse = jax.jit(jax.value_and_grad(lambda pp, al, dt: full_loss(pp, al, dt, gw, pix, 1.2, 2.0)[0])) + fine = jax.jit(jax.value_and_grad(lambda pp, al, dt: full_loss(pp, al, dt, gw, pix, 0.45, 0.0)[0])) + fine_eval = jax.jit(lambda pp, al, dt: full_loss(pp, al, dt, gw, pix, 0.45, 0.0)) + + @jax.jit + def front_back(pp, al): + P, R = fk(S, pose_from_params(pp)) + return sum(jnp.mean((render_sil(S, P, R, d, pix=pix) - al[d]) ** 2) * 100 for d in (0, 4)) + + def run(fn, pp, al, dt, n, lr): + opt = optax.adam(lr); st = opt.init(pp) + for _ in range(n): + l, g = fn(pp, al, dt) + up, st = opt.update(g, st, pp) + pp = optax.apply_updates(pp, up) + return pp + + base = mounted_init() if a in MOUNTED else stand_pose + if a in FIRST_FROM and lookup(FIRST_FROM[a]) is not None: + base = {k: jnp.asarray(v[0]) for k, v in lookup(FIRST_FROM[a]).items()} + extra = lookup(PER_FRAME_FROM[a]) if a in PER_FRAME_FROM else None + cyc = a in CYCLIC + + def fit_frame(i, init): + # starts: previous frame (and, for run/advance cycles, the walk frame with the same index); + # each start: plain silhouette fit, and long-range pull + fit; keep the best. Limb identity is never swapped. + starts = [init] + if extra is not None and i < extra["trans"].shape[0]: + starts.append({k: jnp.asarray(v[i]) for k, v in extra.items()}) + best, bl = None, np.inf + for st0 in starts: + c1 = run(fine, st0, A[i], DT[i], 300, 0.02) + c2 = run(fine, run(coarse, st0, A[i], DT[i], 120, 0.03), A[i], DT[i], 300, 0.02) + for c in (c1, c2): + l = float(fine_eval(c, A[i], DT[i])[0]) + if l < bl: + best, bl = c, l + return best, bl + + poses, losses = [], [] + prev = base + for i in range(F): + p, l = fit_frame(i, prev) + if i == 0: + fb = float(front_back(p, A[0])) + chosen = "as fitted" + for vn, fn_ in LR_VARIANTS.items(): + q = run(fine, fn_(p), A[0], DT[0], 300, 0.015) + ql = float(fine_eval(q, A[0], DT[0])[0]); qfb = float(front_back(q, A[0])) + if qfb < 0.95 * fb and ql < 1.05 * l: + p, l, fb, chosen = q, ql, qfb, vn + " L/R matched to original" + print(f" action {a} frame 0 left/right: {chosen}", flush=True) + poses.append(p); losses.append(l) + prev = p + if cyc and F > 1: + # second pass around the loop: frame 0 continues from the last frame, and so on + prev = poses[-1] + for i in range(F): + p, l = fit_frame(i, prev) + if l < losses[i]: + poses[i], losses[i] = p, l + prev = poses[i] + + batch = jax.tree.map(lambda *xs: jnp.stack(xs), *poses) + + def joint_loss(bp): + l, d = jax.vmap(lambda pp, al, dt: full_loss(pp, al, dt, gw, pix, 0.45, 0.0))(bp, A, DT) + sm = 0.0 + if F > 1: + for k in ("ball", "hinge", "trans"): + x = bp[k] + sm += jnp.sum((x[1:] - x[:-1]) ** 2) + if cyc: + sm += 0.5 * jnp.sum((x[0] - x[-1]) ** 2) + return jnp.sum(l) + 0.05 * sm, jnp.sum(d) + jvg = jax.jit(jax.value_and_grad(joint_loss, has_aux=True)) + opt2 = optax.adam(optax.exponential_decay(0.01, 250, 0.3)); st = opt2.init(batch) + for _ in range(250): + (l, d), g = jvg(batch) + up, st = opt2.update(g, st, batch) + batch = optax.apply_updates(batch, up) + worst = [] + rows = [] + for i in range(F): + pp = jax.tree.map(lambda x: x[i], batch) + P, R = fk(S, pose_from_params(pp)) + occ = [render_sil(S, P, R, dd, pix=pix) for dd in range(5)] + o = np.stack([np.asarray(x) for x in occ]) > 0.5 + s = np.asarray(A[i]) > 0.5 + worst.append(min((o[d] & s[d]).sum() / max((o[d] | s[d]).sum(), 1) for d in range(5))) + rows.append(overlay_row(T[i][:, y0:y1, x0:x1], occ, zoom=3)) + results = pickle.load(open(out_path, "rb")) if os.path.exists(out_path) else {} + results[a] = dict(poses=jax.tree.map(np.asarray, batch), worst_iou=worst, crop=(y0, y1, x0, x1)) + pickle.dump(results, open(out_path, "wb")) + im = Image.new("RGB", (rows[0].width, sum(r.height for r in rows))) + yy = 0 + for r in rows: + im.paste(r, (0, yy)); yy += r.height + os.makedirs("qa2", exist_ok=True) + im.save(f"qa2/a{a:02d}_{ACTIONS_PEOPLE[a]}.png") + print(f"action {a:2d} {ACTIONS_PEOPLE[a]:24s} frames={F} worstIoU mean={np.mean(worst):.3f} min={np.min(worst):.3f} {time.time()-t0:.0f}s", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/run_render_headless.py b/third_party/UO_Model3D_v13/pipeline/run_render_headless.py new file mode 100644 index 0000000..31521ff --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/run_render_headless.py @@ -0,0 +1,40 @@ +"""Run render_uo_layer.py headless (bpy module) on a .blend with some settings overridden. + + python run_render_headless.py [--script render_uo_layer.py] [NAME= ...] + python run_render_headless.py ../model/UO_Body_0x190.blend /tmp/out LAYER='"body"' ONLY='["04_stand"]' CANVAS='(136,120)' ANCHOR='(68,86)' + --pre file.py runs a script (with bpy) after the .blend is opened and before the render, e.g. to add a test object. + +The script text comes from the given file (default: render_uo_layer.py next to this one), not from the text embedded in the +.blend, so a change in pipeline/ can be tested without touching the .blend. Output goes to // and /.vd. +The .blend is only read, never saved. Needs: pip install numpy "bpy==4.2.*" (or "bpy==5.0.1"; Blender 5.2 also works: blender -b --python run_render_headless.py -- ). +""" +import os, re, sys +if "--" in sys.argv: # run inside Blender: blender -b --python this.py -- + sys.argv = sys.argv[:1] + sys.argv[sys.argv.index("--") + 1:] + +import bpy + +args = sys.argv[1:] +blend, out_dir = os.path.abspath(args.pop(0)), os.path.abspath(args.pop(0)) +script = os.path.join(os.path.dirname(os.path.abspath(__file__)), "render_uo_layer.py") +pre = None +while args and args[0] in ("--script", "--pre"): + flag = args.pop(0) + if flag == "--script": + script = os.path.abspath(args.pop(0)) + else: + pre = os.path.abspath(args.pop(0)) +over = dict(a.split("=", 1) for a in args) +over.setdefault("OUT_DIR", repr(out_dir + "/")) +over.setdefault("VD_FILE", repr(out_dir + "/%s.vd")) + +text = open(script).read() +for k, v in over.items(): + text, n = re.subn(r"^%s\s*=.*$" % re.escape(k), "%s = %s" % (k, v), text, count=1, flags=re.M) + if n != 1: + sys.exit("setting %s not found in %s" % (k, script)) + +bpy.ops.wm.open_mainfile(filepath=blend) +if pre: + exec(compile(open(pre).read(), pre, "exec"), {"__name__": "__pre__", "bpy": bpy}) +exec(compile(text, script, "exec"), {"__name__": "__main__", "__file__": script}) diff --git a/third_party/UO_Model3D_v13/pipeline/run_script_in_blend.py b/third_party/UO_Model3D_v13/pipeline/run_script_in_blend.py new file mode 100644 index 0000000..e8074f3 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/run_script_in_blend.py @@ -0,0 +1,10 @@ +"""python run_script_in_blend.py : open the .blend (bpy module) and run the script with bpy in its globals (the .blend is not saved).""" +import sys, os +if "--" in sys.argv: # run inside Blender: blender -b --python this.py -- + sys.argv = sys.argv[:1] + sys.argv[sys.argv.index("--") + 1:] +import bpy +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(sys.argv[1])) +sc = os.path.abspath(sys.argv[2]) +exec(compile(open(sc).read(), sc, "exec"), {"__name__": "__main__", "bpy": bpy}) +sys.stdout.flush(); sys.stderr.flush() +os._exit(0) # the bpy module can segfault while it shuts down, after the work is done diff --git a/third_party/UO_Model3D_v13/pipeline/run_shape.py b/third_party/UO_Model3D_v13/pipeline/run_shape.py new file mode 100644 index 0000000..e248dd6 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/run_shape.py @@ -0,0 +1,54 @@ +import numpy as np, jax, jax.numpy as jnp, optax, pickle, time +from body import * +from fit import * +from targets import targets +from viz import overlay_row +from PIL import Image + +# frames used for the shape fit: stand, walk, run, fidget, spell_area, bow +sel = [(4,0)] + [(0,i) for i in range(0,10,2)] + [(2,i) for i in range(0,10,2)] + [(17,3),(16,3),(32,2),(6,2)] +T = np.stack([targets(a,i)[0] for a,i in sel]) # (F,5,H,W,4) +Anp = T[...,3].astype(np.float32)/255.0 +y0,y1,x0,x1 = crop_box(Anp) +print('crop', y1-y0, x1-x0) +A = jnp.asarray(Anp[...,y0:y1,x0:x1]) +pix = PIX[y0:y1,x0:x1] +F = len(sel) +ground_w = jnp.asarray([0.0 if a==21 else 1.0 for a,_ in sel]) + +S0 = init_shape() +fixed = {k:S0[k] for k in FIXED_KEYS} +params = dict(shape=shape_to_params(S0), + poses=jax.tree.map(lambda x: jnp.stack([x]*F), init_pose_params())) + +def total(params): + S = params_to_shape(params['shape'], fixed) + f = jax.vmap(lambda pp, a, g: frame_loss(S, pp, a, g, pix=pix, torso_w=0.3)) + l, d = f(params['poses'], A, ground_w) + return jnp.sum(l) + shape_prior(S, S0), jnp.sum(d) + +vg = jax.jit(jax.value_and_grad(total, has_aux=True)) +sched = optax.exponential_decay(0.02, 1000, 0.3) +opt = optax.adam(sched); st = opt.init(params) +@jax.jit +def step(params, st): + (l, d), g = vg(params) + up, st = opt.update(g, st, params) + return optax.apply_updates(params, up), st, l, d +t=time.time() +for it in range(1601): + params, st, l, d = step(params, st) + if it%250==0: print(it, float(l), float(d), f"{time.time()-t:.0f}s", flush=True) +pickle.dump(jax.tree.map(np.asarray, dict(params=params, fixed=fixed, sel=sel)), open('shape_fit.pkl','wb')) +S = params_to_shape(params['shape'], fixed) +print('theta deg', float(jnp.degrees(S['theta']))) +for k,v in S.items(): print(k, np.round(np.asarray(v),3)) +rows=[] +for i in range(F): + pose = pose_from_params(jax.tree.map(lambda x:x[i], params['poses'])) + P,R = fk(S,pose) + rows.append(overlay_row(T[i], [render_sil(S,P,R,d) for d in range(5)], zoom=3)) +W=rows[0].width; im=Image.new('RGB',(W,sum(r.height for r in rows))) +y=0 +for r in rows: im.paste(r,(0,y)); y+=r.height +im.save('shape_fit.png') diff --git a/third_party/UO_Model3D_v13/pipeline/sdfmesh.py b/third_party/UO_Model3D_v13/pipeline/sdfmesh.py new file mode 100644 index 0000000..3a883bd --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/sdfmesh.py @@ -0,0 +1,150 @@ +"""Build a smooth rest-pose body surface from the fitted primitives: SDF smooth-union + marching cubes.""" +import numpy as np +from skimage import measure +import jax.numpy as jnp +from body import fk, zero_pose, JI, ARM_REST_ANGLE + +PART_BONE = {} # primitive name -> bone name (for skin weights) + + +def sd_ellipsoid(p, c, R, r): + q = (p - c) @ R # into local frame + k0 = np.linalg.norm(q / r, axis=-1) + k1 = np.linalg.norm(q / (r * r), axis=-1) + return k0 * (k0 - 1.0) / np.maximum(k1, 1e-9) + + +def sd_round_cone(p, a, b, r1, r2): + ba = b - a + l2 = ba @ ba + rr = r1 - r2 + a2 = l2 - rr * rr + il2 = 1.0 / l2 + pa = p - a + y = pa @ ba + z = y - l2 + x2 = np.sum((pa * l2 - np.outer(y, ba)) ** 2, -1) + y2 = y * y * l2 + z2 = z * z * l2 + k = np.sign(rr) * rr * rr * x2 + d3 = (np.sqrt(np.maximum(x2 * a2 * il2, 0)) + y * rr) * il2 - r1 + d = np.where(np.sign(z) * a2 * z2 > k, np.sqrt(x2 + z2) * il2 - r2, + np.where(np.sign(y) * a2 * y2 < k, np.sqrt(x2 + y2) * il2 - r1, d3)) + return d + + +def smin(a, b, k): + h = np.clip(0.5 + 0.5 * (b - a) / k, 0.0, 1.0) + return b * (1 - h) + a * h - k * h * (1 - h) + + +def rot_x(a): + c, s = np.cos(a), np.sin(a) + return np.array([[1, 0, 0], [0, c, -s], [0, s, c]]) + + +def rot_y(a): + c, s = np.cos(a), np.sin(a) + return np.array([[c, 0, s], [0, 1, 0], [-s, 0, c]]) + + +def body_parts(S): + """List of (name, bone, sdf_fn) for the rest pose (A-pose).""" + S = {k: np.asarray(v, np.float64) for k, v in S.items()} + P, _ = fk({k: jnp.asarray(v, jnp.float32) for k, v in S.items()}, zero_pose()) + P = np.asarray(P, np.float64) + I = np.eye(3) + sa, ca = np.sin(ARM_REST_ANGLE), np.cos(ARM_REST_ANGLE) + parts = [] + + def ell(name, bone, c, r, R=I): + parts.append((name, bone, lambda p, c=c, r=r, R=R: sd_ellipsoid(p, c, R, r))) + + def cone(name, bone, a, b, r1, r2): + parts.append((name, bone, lambda p, a=a, b=b, r1=r1, r2=r2: sd_round_cone(p, a, b, r1, r2))) + + pel, sp, ch, nk, hd = (P[JI[n]] for n in ("pelvis", "spine", "chest", "neck", "head")) + ell("pelvis", "pelvis", pel + S["pelvis_c"], S["pelvis_r"]) + ell("abdomen", "spine", sp + S["abd_c"], S["abd_r"]) + ell("chest", "chest", ch + S["chest_c"], S["chest_r"]) + cone("neck", "neck", nk, hd, S["neck_r"], S["neck_r"] * 0.9) + hc, hr = hd + S["head_c"], S["head_r"] + ell("head", "head", hc, hr) + # --- anatomical detail (fixed relative to fitted sizes; small, mostly inside the fitted silhouette) + ell("jaw", "head", hc + np.array([0, -0.35 * hr[1], -0.45 * hr[2]]), hr * np.array([0.75, 0.62, 0.5])) + cone("nose", "head", hc + np.array([0, -0.80 * hr[1], 0.05 * hr[2]]), + hc + np.array([0, -1.02 * hr[1], -0.22 * hr[2]]), 0.10 * hr[0], 0.16 * hr[0]) + ell("brow", "head", hc + np.array([0, -0.62 * hr[1], 0.20 * hr[2]]), hr * np.array([0.62, 0.30, 0.16])) + for sx in (1, -1): + ell("ear" + str(sx), "head", hc + np.array([sx * 0.93 * hr[0], 0.05 * hr[1], 0.02 * hr[2]]), + hr * np.array([0.14, 0.24, 0.32])) + cr, cc = S["chest_r"], ch + S["chest_c"] + for sx, side in ((1, "L"), (-1, "R")): + ell("pec." + side, "chest", cc + np.array([sx * 0.42 * cr[0], -0.55 * cr[1], 0.05 * cr[2]]), + np.array([0.46 * cr[0], 0.48 * cr[1], 0.38 * cr[2]])) + sh = P[JI["shoulder." + side]] + ell("delt." + side, "upper_arm." + side, sh + np.array([sx * 0.25, 0, -0.35]) * S["uarm_r"][0], + np.array([1.15, 1.2, 1.35]) * S["uarm_r"][0], rot_y(sx * ARM_REST_ANGLE * 0.5)) + ell("trap." + side, "chest", (sh + nk) / 2 + np.array([0, 0.25 * cr[1], -0.02]), + np.array([0.55 * np.linalg.norm(sh - nk), 0.45 * cr[1], 0.28 * cr[2]])) + ell("glute." + side, "pelvis", pel + S["pelvis_c"] + np.array([sx * 0.45 * S["pelvis_r"][0], 0.45 * S["pelvis_r"][1], -0.25 * S["pelvis_r"][2]]), + S["pelvis_r"] * np.array([0.52, 0.62, 0.62])) + ua = (P[JI["shoulder." + side]], P[JI["elbow." + side]]) + cone("uarm." + side, "upper_arm." + side, ua[0], ua[1], *S["uarm_r"]) + fa = (P[JI["elbow." + side]], P[JI["wrist." + side]]) + cone("farm." + side, "forearm." + side, fa[0], fa[1], *S["farm_r"]) + d = np.array([sx * sa, 0, -ca]) + Rh = rot_y(sx * ARM_REST_ANGLE).T + Rh = np.array([[ca, 0, -sx * sa], [0, 1, 0], [sx * sa, 0, ca]]) + w = P[JI["wrist." + side]] + # palm: flattened in the arm plane (thin along Y), thumb pointing forward + ell("hand." + side, "hand." + side, w + d * S["hand"] * 0.45, S["hand_r"], Rh) + tb = w + d * S["hand"] * 0.25 + np.array([0, -S["hand_r"][1] * 1.2, 0]) + cone("thumb." + side, "hand." + side, w + d * 0.02 + np.array([0, -S["hand_r"][1] * 0.5, 0]), + tb + d * S["hand"] * 0.25, S["hand_r"][1] * 0.75, S["hand_r"][1] * 0.6) + th = (P[JI["hip." + side]], P[JI["knee." + side]]) + cone("thigh." + side, "thigh." + side, th[0], th[1], *S["thigh_r"]) + sh_ = (P[JI["knee." + side]], P[JI["ankle." + side]]) + cone("shin." + side, "shin." + side, sh_[0], sh_[1], *S["shin_r"]) + ell("calf." + side, "shin." + side, sh_[0] * 0.72 + sh_[1] * 0.28 + np.array([0, 0.35 * S["shin_r"][0], 0]), + np.array([0.85, 0.9, 2.6]) * S["shin_r"][0]) + a = P[JI["ankle." + side]] + heel = a + np.array([0.0, S["heel_y"], -S["ankle_h"] + S["foot_r"][0]]) + toe = a + np.array([0.0, -S["foot_len"] + S["heel_y"] + S["foot_r"][1], -S["ankle_h"] + S["foot_r"][1]]) + cone("foot." + side, "foot." + side, heel, toe, *S["foot_r"]) + return parts, P + + +BLEND_K = {"default": 0.03, "abdomen": 0.08, "chest": 0.08, "neck": 0.05, "head": 0.03, + "nose": 0.008, "ear1": 0.006, "ear-1": 0.006, "thumb.L": 0.01, "thumb.R": 0.01, "brow": 0.015, + "jaw": 0.02, "pec.L": 0.04, "pec.R": 0.04, "trap.L": 0.05, "trap.R": 0.05, + "glute.L": 0.04, "glute.R": 0.04, "uarm.L": 0.04, "uarm.R": 0.04, "thigh.L": 0.035, "thigh.R": 0.035} + + +def body_sdf(parts, pts): + d = None + per = [] + for name, bone, f in parts: + di = f(pts) + per.append(di) + k = BLEND_K.get(name, BLEND_K["default"]) + d = di if d is None else smin(d, di, k) + return d, np.stack(per) + + +def build_mesh(S, res=0.006): + parts, P = body_parts(S) + lo = np.array([-1.0, -0.4, -0.05]) + hi = np.array([1.0, 0.4, 2.2]) + # tighten box using joints + lo = np.minimum(lo, P.min(0) - 0.3) + hi = np.maximum(hi, P.max(0) + 0.3) + n = np.ceil((hi - lo) / res).astype(int) + 1 + g = np.stack(np.meshgrid(*[lo[i] + np.arange(n[i]) * res for i in range(3)], indexing="ij"), -1).reshape(-1, 3) + d = np.empty(len(g)) + for i in range(0, len(g), 400000): + d[i:i + 400000], _ = body_sdf(parts, g[i:i + 400000]) + vol = d.reshape(n) + v, f, nrm, _ = measure.marching_cubes(vol, 0.0, spacing=(res, res, res)) + v = v + lo + return v, f[:, ::-1], parts, P diff --git a/third_party/UO_Model3D_v13/pipeline/shift_test.py b/third_party/UO_Model3D_v13/pipeline/shift_test.py new file mode 100644 index 0000000..5bc1167 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/shift_test.py @@ -0,0 +1,27 @@ +"""How much would a per-(frame, direction) 2D image shift of the model improve the IoU? (integer shifts, +-3 px)""" +import sys, pickle, numpy as np, jax.numpy as jnp +from posefit_mesh import * +from posefit_mesh import _posed_j +from vd import ACTIONS_PEOPLE +P = pickle.load(open(sys.argv[1], "rb")) +R = 3 +allsh = [] +for a in range(35): + T = targets(a); m = T[..., 3] > 127; F = len(T) + hid = (horse_masks(a, F) & ~m) if a in HORSE_OF else np.zeros_like(m) + i0 = []; ib = []; sh = [] + for i in range(F): + X = _posed_j({k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()}) + for d in range(5): + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H) + s = m[i, d]; best = (-1, 0, 0) + for dy in range(-R, R + 1): + for dx in range(-R, R + 1): + k = np.roll(np.roll(mk, dy, 0), dx, 1) & ~hid[i, d] + iou = (k & s).sum() / max((k | s).sum(), 1) + if dx == 0 and dy == 0: z = iou + if iou > best[0]: best = (iou, dx, dy) + i0.append(z); ib.append(best[0]); sh.append(best[1:]) + sh = np.array(sh); allsh.append(sh) + nz = (np.abs(sh).max(1) > 0).mean() + print(f"{a:2d} {ACTIONS_PEOPLE[a]:24s} IoU {np.mean(i0):.3f} -> {np.mean(ib):.3f} shifted views {nz:.2f} mean|shift| {np.abs(sh).mean(0)}", flush=True) diff --git a/third_party/UO_Model3D_v13/pipeline/strip_originals.py b/third_party/UO_Model3D_v13/pipeline/strip_originals.py new file mode 100644 index 0000000..6813330 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/strip_originals.py @@ -0,0 +1,17 @@ +"""Copy of the .blend WITHOUT the packed original UO frames (for the repository). Exact modes stay off until +pack_originals.py puts the frames back from the user's own client files.""" +import bpy, sys, os +src, out = sys.argv[sys.argv.index("--src") + 1], sys.argv[sys.argv.index("--out") + 1] +os.makedirs(out, exist_ok=True) +bpy.context.preferences.filepaths.save_version = 0 +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(src)) +sc = bpy.context.scene +for name in ("UO_Original_Atlas",): + if name in bpy.data.images: + bpy.data.images.remove(bpy.data.images[name]) +if "uo_original_frames.json" in bpy.data.texts: + bpy.data.texts.remove(bpy.data.texts["uo_original_frames.json"]) +sc["uo_exact"] = 0.0 +bpy.data.texts["render_uo_layer.py"].from_string(open("render_uo_layer.py").read()) +bpy.ops.wm.save_as_mainfile(filepath=os.path.abspath(os.path.join(out, "UO_Body_0x190.blend"))) +print("stripped") diff --git a/third_party/UO_Model3D_v13/pipeline/sync_blend_scripts.py b/third_party/UO_Model3D_v13/pipeline/sync_blend_scripts.py new file mode 100644 index 0000000..9e011e9 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/sync_blend_scripts.py @@ -0,0 +1,32 @@ +"""Compare / copy the scripts of pipeline/ with the texts embedded in a .blend (the .blend runs ITS OWN copy of a script). + + python sync_blend_scripts.py --check # which embedded texts differ from the files of pipeline/ + python sync_blend_scripts.py render_uo_layer.py # copy the given scripts into the .blend and save it +Only the named texts are replaced. Everything else in the .blend stays as it is. Needs: pip install "bpy==4.2.*" (a file saved by Blender 5.x does not open in 4.2: sync with 4.2 to keep both working), or run it inside Blender 5.x with --background --python. +""" +import os, sys +if "--" in sys.argv: # run inside Blender: blender -b --python this.py -- + sys.argv = sys.argv[:1] + sys.argv[sys.argv.index("--") + 1:] + +import bpy + +HERE = os.path.dirname(os.path.abspath(__file__)) +args = sys.argv[1:] +blend = os.path.abspath(args.pop(0)) +check = args == ["--check"] +bpy.ops.wm.open_mainfile(filepath=blend) +names = [t.name for t in bpy.data.texts if os.path.exists(os.path.join(HERE, t.name))] if check else args +changed = 0 +for name in names: + src = os.path.join(HERE, name) + new = open(src, encoding="utf-8").read() + t = bpy.data.texts.get(name) + old = t.as_string() if t else None + state = "missing in the .blend" if t is None else ("identical" if old == new else "DIFFERENT (%d -> %d chars)" % (len(old), len(new))) + print("%-28s %s" % (name, state)) + if not check and old != new: + t = t or bpy.data.texts.new(name) + t.clear(); t.write(new); changed += 1 +if not check and changed: + bpy.ops.wm.save_as_mainfile(filepath=blend) + print("saved", blend) diff --git a/third_party/UO_Model3D_v13/pipeline/targets.py b/third_party/UO_Model3D_v13/pipeline/targets.py new file mode 100644 index 0000000..91b8953 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/targets.py @@ -0,0 +1,33 @@ +import numpy as np +from vd import read_vd, ACTIONS_PEOPLE +from body import CANVAS_W, CANVAS_H, ANCHOR_X, ANCHOR_Y + +_cache = {} + + +def load(path="body400.vd"): + if path not in _cache: + _cache[path] = read_vd(path) + return _cache[path] + + +def frame_canvas(f): + """Place a decoded frame on the fixed canvas with its anchor at (ANCHOR_X, ANCHOR_Y).""" + rgba = np.zeros((CANVAS_H, CANVAS_W, 4), np.uint8) + x0 = ANCHOR_X - f["cx"] + y0 = ANCHOR_Y - (f["cy"] + f["h"]) + img = f["img"] + h, w = img.shape[:2] + sx0, sy0 = max(0, -x0), max(0, -y0) + ex, ey = min(w, CANVAS_W - x0), min(h, CANVAS_H - y0) + assert sx0 == 0 and sy0 == 0 and ex == w and ey == h, "frame exceeds canvas" + rgba[y0 + sy0:y0 + ey, x0 + sx0:x0 + ex] = img[sy0:ey, sx0:ex] + return rgba + + +def targets(action, frame=None, path="body400.vd"): + """Returns array (F,5,H,W,4) uint8 for all frames (or one) of an action.""" + _, _, anims = load(path) + n = len(anims[(action, 0)]) + idx = range(n) if frame is None else [frame] + return np.stack([[frame_canvas(anims[(action, d)][i]) for d in range(5)] for i in idx]) diff --git a/third_party/UO_Model3D_v13/pipeline/test_canvas.py b/third_party/UO_Model3D_v13/pipeline/test_canvas.py new file mode 100644 index 0000000..126e81c --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_canvas.py @@ -0,0 +1,94 @@ +"""Regression test of the CANVAS / ANCHOR parameters of render_uo_layer.py. + +For every test case the frames are rendered with (a) the reference script (default: the version of commit ea55c0b, 136x120 with +anchor (68, 86) hard-wired), (b) the current script with CANVAS=(136,120) - must be pixel-identical to (a), and (c) the current +script on other canvases - inside the area of the original 136x120 frame (anchors aligned) they must have the same silhouette +and colours within 1 level of (a) (float rounding), and everywhere else the frame must be transparent (the test items fit into +the old canvas). (a) is the old script plus `dither_intensity = 0`: Blender's 8-bit dither is position dependent noise. + + python test_canvas.py [--blend ../model/UO_Body_0x190.blend] [--ref ref_render_uo_layer.py] [--tmp DIR] [--quick] +""" +import argparse, os, subprocess, sys, tempfile + +import numpy as np +from PIL import Image + +HERE = os.path.dirname(os.path.abspath(__file__)) +CASES = { # name: (settings, actions) + "clothing": ('LAYER="clothing"', ["04_stand", "25_mounted_stand", "09_attack_1h_slash"]), + "body_model": ('LAYER="body"; EXACT_BODY=False', ["04_stand", "25_mounted_stand"]), # atlas colours through UOX_* nodes + "body_exact": ('LAYER="body"; EXACT_BODY=True', ["04_stand", "00_walk_unarmed"]), + "all": ('LAYER="all"', ["04_stand", "25_mounted_stand"]), +} +CANVASES = [((136, 120), (68, 86)), ((256, 256), (128, 192)), ((200, 180), (90, 130)), ((100, 100), (40, 70))] + + +def render(blend, script, out, case, actions, canvas=None): + sets = dict(s.split("=", 1) for s in CASES[case][0].split("; ")) + sets["ONLY"] = repr(actions) + if "OWN_PARTS_NEVER_HIDE" in open(script).read(): # the reference (commit ea55c0b) has no such rule: switch it off, this test only checks the canvas + sets["OWN_PARTS_NEVER_HIDE"] = "False" + if canvas: + sets["CANVAS"], sets["ANCHOR"] = repr(canvas[0]), repr(canvas[1]) + cmd = [sys.executable, os.path.join(HERE, "run_render_headless.py"), blend, out, "--script", script] + ["%s=%s" % kv for kv in sets.items()] + r = subprocess.run(cmd, capture_output=True, text=True) + if r.returncode: + sys.exit("render failed (%s):\n%s\n%s" % (" ".join(cmd[-6:]), r.stdout[-1500:], r.stderr[-1500:])) + return os.path.join(out, sets["LAYER"].strip('"'), "frames") + + +def frames(root): + for dp, _, fs in sorted(os.walk(root)): + for f in sorted(fs): + if f.endswith(".png"): + yield os.path.relpath(os.path.join(dp, f), root), np.array(Image.open(os.path.join(dp, f)).convert("RGBA")) + + +def compare(ref_root, new_root, canvas): + (W, H), (ax, ay) = canvas + dx, dy = ax - 68, ay - 86 + ref = dict(frames(ref_root)); new = dict(frames(new_root)) + assert ref.keys() == new.keys(), "different frame lists" + bad_in = bad_out = 0 + for k, a in ref.items(): + b = new[k] + assert b.shape == (H, W, 4), (k, b.shape) + full = np.zeros_like(b) + y0, y1, x0, x1 = max(dy, 0), min(dy + 120, H), max(dx, 0), min(dx + 136, W) + full[y0:y1, x0:x1] = a[y0 - dy:y1 - dy, x0 - dx:x1 - dx] + inside = np.zeros((H, W), bool); inside[y0:y1, x0:x1] = True + diff = np.abs(b.astype(int) - full.astype(int)) + d = diff.max(-1) > (0 if (dx, dy) == (0, 0) and (W, H) == (136, 120) else 1) # identity canvas: exact; others: 1 level of float rounding + d |= diff[..., 3] > 0 # the silhouette must always be identical + bad_in += int((d & inside).sum()); bad_out += int((diff.max(-1) > 0)[~inside].sum()) + return len(ref), bad_in, bad_out + + +if __name__ == "__main__": + ap = argparse.ArgumentParser() + ap.add_argument("--blend", default=os.path.join(HERE, "..", "model", "UO_Body_0x190.blend")) + ap.add_argument("--ref", help="reference script (default: render_uo_layer.py of commit ea55c0b from git)") + ap.add_argument("--tmp", default=None) + ap.add_argument("--quick", action="store_true", help="only 04_stand") + a = ap.parse_args() + tmp = os.path.abspath(a.tmp) if a.tmp else tempfile.mkdtemp(prefix="test_canvas_") + os.makedirs(tmp, exist_ok=True) + blend = os.path.abspath(a.blend) + ref = a.ref or os.path.join(tmp, "ref_render_uo_layer.py") + if not a.ref: # the old script plus the one line that turns the position-dependent 8-bit dither off + old = subprocess.check_output(["git", "show", "ea55c0b:pipeline/render_uo_layer.py"], cwd=HERE).decode() + assert "sc.render.resolution_percentage = 100\n" in old + open(ref, "w").write(old.replace("sc.render.resolution_percentage = 100\n", "sc.render.resolution_percentage = 100\nsc.render.dither_intensity = 0.0\n", 1)) + fail = 0 + for case, (_, actions) in CASES.items(): + actions = actions[:1] if a.quick else actions + ref_root = render(blend, ref, os.path.join(tmp, "ref_" + case), case, actions) + for canvas in CANVASES: + root = render(blend, os.path.join(HERE, "render_uo_layer.py"), os.path.join(tmp, "%s_%dx%d" % ((case,) + canvas[0])), case, actions, canvas) + n, bi, bo = compare(ref_root, root, canvas) + ok = bi == 0 and bo == 0 + fail += not ok + print("%-11s canvas %-9s anchor %-10s %3d frames | px off inside the old area: %5d | outside: %5d | %s" % ( + case, "%dx%d" % canvas[0], canvas[1], n, bi, bo, "OK" if ok else "FAIL")) + print("output in", tmp) + sys.exit(1 if fail else 0) diff --git a/third_party/UO_Model3D_v13/pipeline/test_exact.py b/third_party/UO_Model3D_v13/pipeline/test_exact.py new file mode 100644 index 0000000..40b2eac --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_exact.py @@ -0,0 +1,23 @@ +"""Render one action with the exact modes and compare with the original frames.""" +import bpy, sys, os, numpy as np +from PIL import Image +arg = lambda k, d=None: sys.argv[sys.argv.index(k) + 1] if k in sys.argv else d +blend, out, action = arg("--blend"), os.path.abspath(arg("--out")), arg("--action") +layer, exb, exc = arg("--layer", "body"), arg("--exact-body", "0") == "1", arg("--exact-colors", "1") == "1" +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(blend)) +sc = bpy.context.scene; sc.render.engine = "CYCLES"; sc.cycles.device = "CPU"; sc.cycles.samples = 4 +src = bpy.data.texts["render_uo_layer.py"].as_string() +src = src.replace('LAYER = "clothing"', 'LAYER = %r' % layer).replace("ONLY = []", "ONLY = [%r]" % action) +src = src.replace("WRITE_VD = True", "WRITE_VD = False").replace('OUT_DIR = "//uo_render/"', "OUT_DIR = %r" % (out + "/")) +src = src.replace("EXACT_BODY = True", "EXACT_BODY = %r" % exb).replace("EXACT_COLORS = True", "EXACT_COLORS = %r" % exc) +exec(compile(src, "render_uo_layer.py", "exec")) +a = int(action[:2]) +for d in range(5): + fdir = os.path.join(out, layer, "frames", action, "dir%d" % d) + for fn in sorted(os.listdir(fdir)): + i = int(fn[:2]); r = np.array(Image.open(os.path.join(fdir, fn)).convert("RGBA")); o = original(a, i, d) + mr, mo = r[..., 3] > 0, o[..., 3] > 0 + both = mr & mo + same = (np.abs(r[..., :3].astype(int) - o[..., :3].astype(int)).max(-1) <= 8) & both + print(f"dir{d} f{i}: IoU {(both).sum()/max((mr|mo).sum(),1):.3f} missing {(mo&~mr).sum()} outside {(mr&~mo).sum()} " + f"colour equal on overlap {same.sum()/max(both.sum(),1):.3f}") diff --git a/third_party/UO_Model3D_v13/pipeline/test_import_item.py b/third_party/UO_Model3D_v13/pipeline/test_import_item.py new file mode 100644 index 0000000..eddfdc0 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_import_item.py @@ -0,0 +1,76 @@ +"""Test of uo_import_item.py with a stand-in for a foreign model: a body-hugging replica of a UO item (test_items.py) is made "foreign" (other size, +other place, Y-up glTF with the skeleton and weights of the UO rig still inside), saved as .glb, imported into a fresh UO_Body_0x190.blend by +uo_import_item.py, then fitted, bound and rendered; the result is compared with the sprite of the original item (test_real_item.py). + + python test_import_item.py [--item shirt] [--scale 1.15] [--offset 0.12,0.05,-0.20] [--turn 0] [--tmp DIR] +""" +import argparse, json, os, subprocess, sys, tempfile + +HERE = os.path.dirname(os.path.abspath(__file__)) +STAGE_A = r''' +import bpy, os, json, numpy as np +exec(open(os.path.join(os.environ["UO_TEST_SCRIPTS"], "test_items_pre.py")).read(), {"__name__": "__pre__", "bpy": bpy}) +item = bpy.context.view_layer.objects.active +rig = bpy.data.objects["UO_Rig"]; rig.data.pose_position = "REST" +s, off = float(os.environ["FOREIGN_SCALE"]), [float(x) for x in os.environ["FOREIGN_OFFSET"].split(",")] +bpy.context.view_layer.update() +for o in list(bpy.data.objects): # only the item and the rig go into the file + if o not in (item, rig): + bpy.data.objects.remove(o, do_unlink=True) +ref = np.array([item.matrix_world @ v.co for v in item.data.vertices]) +np.save(os.environ["FOREIGN_REF"], ref) +item.scale = (s, s, s); item.location = (np.array(item.location) * s + off) +bpy.context.view_layer.update() +bpy.ops.object.select_all(action="SELECT") +bpy.ops.export_scene.gltf(filepath=os.environ["FOREIGN_GLB"], use_selection=True, export_apply=False, export_skins=True) +print("stage A: foreign glb written") +''' +STAGE_B = r''' +import bpy, os, sys, re, numpy as np +bpy.context.view_layer.objects.active = None +rig = bpy.data.objects["UO_Rig"]; rig.data.pose_position = "REST" +for o in [o for o in bpy.data.collections["Clothing"].all_objects]: + bpy.data.objects.remove(o, do_unlink=True) +def run(script, **over): + text = open(os.path.join(os.environ["UO_TEST_SCRIPTS"], script)).read() + for k, v in over.items(): + text, n = re.subn(r"^%s\s*=.*$" % k, "%s = %r" % (k, v), text, count=1, flags=re.M) + assert n == 1, (script, k) + exec(compile(text, script, "exec"), {"__name__": "__main__"}) +run("uo_import_item.py", FILE=os.environ["FOREIGN_GLB"], KIND=os.environ["FOREIGN_KIND"], TURN=int(os.environ["FOREIGN_TURN"])) +item = bpy.context.view_layer.objects.active +got = np.array([item.matrix_world @ v.co for v in item.data.vertices]); ref = np.load(os.environ["FOREIGN_REF"]) +print("RESULT bbox ref min", ref.min(0).round(3), "max", ref.max(0).round(3)) +print("RESULT bbox got min", got.min(0).round(3), "max", got.max(0).round(3)) +run("uo_materials.py") +run("uo_fit_item.py") +run("uo_bind_item.py", PART=os.environ["FOREIGN_PART"]) +bpy.ops.wm.save_as_mainfile(filepath=os.environ["FOREIGN_OUT"]) +''' +if __name__ == "__main__": + ap = argparse.ArgumentParser() + ap.add_argument("--item", default="shirt"); ap.add_argument("--scale", default="1.15"); ap.add_argument("--offset", default="0.12,0.05,-0.20") + ap.add_argument("--turn", default="0"); ap.add_argument("--skip", default="icosphere"); ap.add_argument("--tmp"); ap.add_argument("--render", action="store_true") + a = ap.parse_args() + tmp = os.path.abspath(a.tmp) if a.tmp else tempfile.mkdtemp(prefix="test_import_") + os.makedirs(tmp, exist_ok=True) + sys.path.insert(0, HERE) + import test_items as ti + spec = os.path.join(tmp, "spec.json"); json.dump(ti.ITEMS, open(spec, "w")) + blend = os.path.abspath(os.path.join(HERE, "..", "model", "UO_Body_0x190.blend")) + sa, sb = os.path.join(tmp, "stage_a.py"), os.path.join(tmp, "stage_b.py") + open(sa, "w").write(STAGE_A); open(sb, "w").write(STAGE_B) + kind = a.item + env = dict(os.environ, UO_TEST_SPEC=spec, UO_TEST_ITEM=a.item, UO_TEST_FIT="0", UO_TEST_SCRIPTS=HERE, FOREIGN_SCALE=a.scale, FOREIGN_OFFSET=a.offset, + FOREIGN_REF=os.path.join(tmp, "ref.npy"), FOREIGN_GLB=os.path.join(tmp, "foreign.glb"), FOREIGN_KIND=kind, FOREIGN_TURN=a.turn, + FOREIGN_PART=ti.ITEMS[a.item]["part"], UO_IMPORT_SKIP=a.skip, FOREIGN_OUT=os.path.join(tmp, "imported.blend")) + for stage in (sa, sb): + r = subprocess.run([sys.executable, os.path.join(HERE, "run_script_in_blend.py"), blend, stage], capture_output=True, text=True, env=env) + print("\n".join(l for l in r.stdout.splitlines() if l.startswith(("RESULT", "uo_import_item", "uo_materials", "uo_fit", "uo_bind", "stage", " ")))) + if r.returncode: + sys.exit("%s failed:\n%s\n%s" % (stage, r.stdout[-2500:], r.stderr[-2500:])) + if a.render: + r = subprocess.run([sys.executable, os.path.join(HERE, "test_real_item.py"), "--blend", env["FOREIGN_OUT"], "--anim", str(ti.ITEMS[a.item]["anim"]), + "--tmp", os.path.join(tmp, "render"), "--img", os.path.join(tmp, "overlay.png")], capture_output=True, text=True) + print(r.stdout[-800:], r.stderr[-800:] if r.returncode else "") + print("output in", tmp) diff --git a/third_party/UO_Model3D_v13/pipeline/test_items.py b/third_party/UO_Model3D_v13/pipeline/test_items.py new file mode 100644 index 0000000..5c7093b --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_items.py @@ -0,0 +1,134 @@ +"""Item-level QA: replicas of real UO items rendered with the whole pipeline (uo_bind_item + render_uo_layer) and compared +with the original sprites from the client. + + python test_items.py [--items shirt,pants,plate,gloves,boots,helm] [--actions 04_stand,09_attack_1h_slash,...|--all] + [--fit] [--tmp DIR] [--out qa.json] [--img overlay.png] [--canvas 256,256 --anchor 128,192] + +The replica of an item is the skin of the body it covers, moved out by the item's thickness (body-hugging shell), so the numbers +measure the model + the render pipeline (occlusion by the body, EXACT_BODY cut, holes, specks, palette), not the 3D modelling of an +item. Sprites: pipeline/body13/mul/anim_NNNN.vd (the Nelderim client, same bytes as anim.mul). Per item and frame: + iou overlap of the rendered item with the sprite + outside rendered pixels the sprite does not have missing sprite pixels the render does not have + strip part of `missing` that touches the render (<= 1 px: the 1-px skin strips along the edges of tight items) + pieces detached pieces of the render (specks) clipped frames where the render touches the canvas border + colors most colours (RGB555) in one action/direction block; > 256 means the palette is reduced +""" +import argparse, json, os, subprocess, sys, tempfile, time + +import numpy as np +from PIL import Image +from scipy import ndimage + +HERE = os.path.dirname(os.path.abspath(__file__)) +sys.path.insert(0, os.path.join(HERE, "body13")) +from itemframes import canvas as sprite_canvas, load as load_sprites # noqa: E402 + +ITEMS = { # name: sprite id, bones covered, thickness m, cut (bone, keep from t0 along it), zrange (rest-pose height m), uo_bind_item PART + # zrange comes from the sprites: lowest/highest row of the item in 04_stand (mean of 5 directions) -> z = -row / (36 cos 28.4557) + 0.07 + "shirt": dict(anim=434, parts=["pelvis", "spine", "chest", "clavicle", "upper_arm", "neck"], thickness=0.012, cut=None, cut_far=["upper_arm", 0.4], zrange=[1.03, 9], part="chest"), + "plate": dict(anim=527, parts=["pelvis", "spine", "chest", "clavicle", "neck", "thigh"], thickness=0.03, cut=None, zrange=[0.68, 9], part="chest"), + "arms": dict(anim=528, parts=["upper_arm", "forearm", "clavicle"], thickness=0.025, cut=None, part="arms"), + "pants": dict(anim=431, parts=["pelvis", "thigh", "shin"], thickness=0.012, cut=None, zrange=[-9, 1.17], part="legs"), + "legs": dict(anim=529, parts=["pelvis", "thigh", "shin"], thickness=0.03, cut=None, zrange=[-9, 1.14], part="legs"), + "boots": dict(anim=477, parts=["shin", "foot"], thickness=0.015, cut=None, zrange=[-9, 0.56], part="boots"), + "gloves": dict(anim=530, parts=["hand", "forearm"], thickness=0.03, cut=["forearm", 0.4], part="gloves"), + # loose items: the template of the body file (chains of the cloth, fitted to the original frames) stands for the item; no cloth bake + "skirt": dict(anim=449, template="UO_Template_Skirt", part="skirt"), + "cloak": dict(anim=468, template="UO_Template_Cloak", part="cloak"), + "helm": dict(anim=563, parts=["head"], thickness=0.02, cut=None, part="helm"), +} +DEFAULT_ITEMS = "shirt,plate,pants,boots,gloves,helm" +DEFAULT_ACTIONS = "04_stand,00_walk_unarmed,09_attack_1h_slash,16_spell_directed,21_die_forward,25_mounted_stand" + + +def render(blend, out, item, actions, canvas, anchor, fit, spec_path, extra=()): + env = dict(os.environ, UO_TEST_SPEC=spec_path, UO_TEST_ITEM=item, UO_TEST_FIT="1" if fit else "0", UO_TEST_SCRIPTS=HERE) + cmd = [sys.executable, os.path.join(HERE, "run_render_headless.py"), blend, out, "--pre", os.path.join(HERE, "test_items_pre.py"), + 'LAYER="clothing"', "ONLY=%r" % (actions,), "CANVAS=%r" % (canvas,), "ANCHOR=%r" % (anchor,)] + list(extra) + r = subprocess.run(cmd, capture_output=True, text=True, env=env) + if r.returncode: + sys.exit("render of %s failed:\n%s\n%s" % (item, r.stdout[-2000:], r.stderr[-2000:])) + return os.path.join(out, "clothing", "frames") + + +def measure(frames_root, item, canvas, anchor, img_frames): + spr = load_sprites(ITEMS[item]["anim"]) + rows, blocks, imgs = [], {}, [] + st = ndimage.generate_binary_structure(2, 2) + for act in sorted(os.listdir(frames_root)): + a = int(act[:2]) + for d in range(5): + fdir = os.path.join(frames_root, act, "dir%d" % d) + colors = set() + for fn in sorted(os.listdir(fdir)): + i = int(fn[:2]) + R = np.array(Image.open(os.path.join(fdir, fn)).convert("RGBA")) + G = sprite_canvas(spr.get((a, d)), i, anchor, canvas) + r, g = R[..., 3] > 0, G[..., 3] > 0 + m = R[..., 3] > 0 + c15 = ((R[..., 0].astype(int) * 31 + 127) // 255 << 10) | ((R[..., 1].astype(int) * 31 + 127) // 255 << 5) | ((R[..., 2].astype(int) * 31 + 127) // 255) + colors |= set(np.unique(c15[m]).tolist()) + if not g.any(): + continue + miss = g & ~r + near = ndimage.binary_dilation(r, st, iterations=1) + lab, n = ndimage.label(r, structure=st) + rows.append(dict(a=a, i=i, d=d, iou=(r & g).sum() / max((r | g).sum(), 1), outside=int((r & ~g).sum()), missing=int(miss.sum()), + strip=int((miss & near).sum()), pieces=int(n), clipped=bool(r[0].any() or r[-1].any() or r[:, 0].any() or r[:, -1].any()), + sprite_px=int(g.sum()))) + if (act, i, d) in img_frames: + im = np.zeros(r.shape + (3,), np.uint8) + 25 + im[r & g] = (190, 190, 190); im[r & ~g] = (230, 60, 60); im[g & ~r] = (60, 120, 255) + imgs.append(im) + blocks[(a, d)] = len(colors) + return rows, blocks, imgs + + +def summarize(rows, blocks): + f = lambda k: float(np.mean([r[k] for r in rows])) if rows else 0.0 + return dict(frames=len(rows), iou=f("iou"), outside=f("outside"), missing=f("missing"), strip=f("strip"), + pieces=f("pieces"), clipped=int(sum(r["clipped"] for r in rows)), + colors_max=max(blocks.values()) if blocks else 0, blocks_over_256=int(sum(v > 256 for v in blocks.values())), + by_action={str(a): float(np.mean([r["iou"] for r in rows if r["a"] == a])) for a in sorted({r["a"] for r in rows})}) + + +if __name__ == "__main__": + ap = argparse.ArgumentParser() + ap.add_argument("--blend", default=os.path.join(HERE, "..", "model", "UO_Body_0x190.blend")) + ap.add_argument("--items", default=DEFAULT_ITEMS) + ap.add_argument("--actions", default=DEFAULT_ACTIONS) + ap.add_argument("--all", action="store_true", help="all 35 actions (about 10x slower)") + ap.add_argument("--fit", action="store_true", help="also run uo_fit_item.py before uo_bind_item.py") + ap.add_argument("--canvas", default="256,256"); ap.add_argument("--anchor", default="128,192") + ap.add_argument("--tmp"); ap.add_argument("--out"); ap.add_argument("--img") + ap.add_argument("--set", action="append", default=[], metavar="NAME=VALUE", help="extra render_uo_layer.py setting, e.g. --set HOLDOUT_MARGIN=0.05 (repeatable)") + a = ap.parse_args() + tmp = os.path.abspath(a.tmp) if a.tmp else tempfile.mkdtemp(prefix="test_items_") + os.makedirs(tmp, exist_ok=True) + canvas, anchor = tuple(int(x) for x in a.canvas.split(",")), tuple(int(x) for x in a.anchor.split(",")) + spec_path = os.path.join(tmp, "spec.json"); json.dump(ITEMS, open(spec_path, "w")) + actions = [] if a.all else a.actions.split(",") + show = {("04_stand", 0, 0), ("09_attack_1h_slash", 3, 1), ("16_spell_directed", 3, 0), ("21_die_forward", 3, 2), ("00_walk_unarmed", 3, 1)} + res, panels = {}, [] + print("%-7s %6s %6s %8s %8s %6s %6s %7s %7s | %s" % ("item", "frames", "IoU", "outside", "missing", "strip", "pieces", "clipped", "colors", "IoU per action")) + for item in a.items.split(","): + t0 = time.time() + root = render(os.path.abspath(a.blend), os.path.join(tmp, item), item, actions, canvas, anchor, a.fit, spec_path, a.set) + rows, blocks, imgs = measure(root, item, canvas, anchor, show) + res[item] = s = summarize(rows, blocks) + print("%-7s %6d %6.3f %8.1f %8.1f %6.1f %6.2f %7d %7d | %s (%.0fs)" % ( + item, s["frames"], s["iou"], s["outside"], s["missing"], s["strip"], s["pieces"], s["clipped"], s["colors_max"], + " ".join("%s:%.2f" % (k, v) for k, v in s["by_action"].items()), time.time() - t0), flush=True) + if imgs: + panels.append(np.concatenate([np.pad(im[max(anchor[1] - 90, 0):anchor[1] + 36, max(anchor[0] - 45, 0):anchor[0] + 45], + ((1, 1), (1, 1), (0, 0)), constant_values=90) for im in imgs], 1)) + mean_iou = float(np.mean([v["iou"] for v in res.values()])) if res else 0.0 + print("mean IoU over items: %.3f" % mean_iou) + if a.out: + os.makedirs(os.path.dirname(os.path.abspath(a.out)), exist_ok=True) + json.dump(dict(canvas=canvas, anchor=anchor, actions=actions or "all", fit=a.fit, items=res, mean_iou=mean_iou), open(a.out, "w"), indent=1) + if a.img and panels: + w = max(p.shape[1] for p in panels) + big = np.concatenate([np.pad(p, ((0, 0), (0, w - p.shape[1]), (0, 0))) for p in panels], 0) + Image.fromarray(big).resize((big.shape[1] * 2, big.shape[0] * 2), Image.NEAREST).save(a.img) + print("output in", tmp) diff --git a/third_party/UO_Model3D_v13/pipeline/test_items_pre.py b/third_party/UO_Model3D_v13/pipeline/test_items_pre.py new file mode 100644 index 0000000..0b83dc3 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_items_pre.py @@ -0,0 +1,99 @@ +"""Runs inside bpy (run_render_headless.py --pre): builds a body-hugging replica of one UO item and binds it with uo_bind_item.py. + +The replica is the part of the UO_Body skin that the real item covers (vertices whose dominant bone is in `parts`, optionally +cut along a limb bone), moved out along the vertex normals by `thickness` metres. It replaces everything in the Clothing +collection. Settings come from the environment: UO_TEST_SPEC (json file with the item table of test_items.py), UO_TEST_ITEM, +UO_TEST_FIT (1 = also run uo_fit_item.py), UO_TEST_SCRIPTS (folder with uo_bind_item.py / uo_fit_item.py). +""" +import json, os, re + +import bmesh +import numpy as np + +spec = json.load(open(os.environ["UO_TEST_SPEC"]))[os.environ["UO_TEST_ITEM"]] +if "UO_TEST_THICK" in os.environ: # experiment: another thickness of the replica + spec = dict(spec, thickness=float(os.environ["UO_TEST_THICK"])) +scripts = os.environ["UO_TEST_SCRIPTS"] +body, rig = bpy.data.objects["UO_Body"], bpy.data.objects["UO_Rig"] +me = body.data +assert np.allclose(body.scale, 1.0), "UO_Body is scaled" + +SUB = {"upper_arm_twist": "upper_arm", "forearm_twist": "forearm", "toe": "foot"} + + +def base_of(n): + s = n[-2:] if n.endswith((".L", ".R")) else "" + b = n[:-2] if s else n + return ("hand" if b.startswith("finger") else SUB.get(b, b)), s + + +groups = [base_of(g.name) for g in body.vertex_groups] +dom = [groups[max(v.groups, key=lambda g: g.weight).group] if v.groups else ("", "") for v in me.vertices] +keep = np.array([d[0] in spec.get("parts", []) for d in dom]) +co = np.empty(len(me.vertices) * 3); me.vertices.foreach_get("co", co); co = co.reshape(-1, 3) +nrm = np.empty_like(co); me.vertices.foreach_get("normal", nrm.ravel()) +if spec.get("cut"): # drop the near end of a limb bone: boots start up the shin, gloves on the forearm + bname, t0 = spec["cut"] + child = {"shin": "foot", "forearm": "hand"}[bname] + M = np.array(rig.matrix_world.inverted() @ body.matrix_world) + ca = co @ M[:3, :3].T + M[:3, 3] + for s in (".L", ".R"): + h = np.array(rig.data.bones[bname + s].head_local); ax = np.array(rig.data.bones[child + s].head_local) - h + L = np.linalg.norm(ax); t = ((ca - h) @ (ax / L)) / L + keep &= ~(np.array([d == (bname, s) for d in dom]) & (t < t0)) + +if spec.get("zrange"): # height cut in the rest pose (world z), measured from the sprite extent + z = (co @ np.array(body.matrix_world)[:3, :3].T + np.array(body.matrix_world)[:3, 3])[:, 2] + keep &= (z >= spec["zrange"][0]) & (z <= spec["zrange"][1]) + +if spec.get("cut_far"): # drop the far end of a limb bone (short sleeves): keep t <= t1 + bname, t1 = spec["cut_far"] + child = {"upper_arm": "forearm", "thigh": "shin"}[bname] + M = np.array(rig.matrix_world.inverted() @ body.matrix_world) + ca = co @ M[:3, :3].T + M[:3, 3] + for s_ in (".L", ".R"): + h = np.array(rig.data.bones[bname + s_].head_local); ax = np.array(rig.data.bones[child + s_].head_local) - h + L = np.linalg.norm(ax); t = ((ca - h) @ (ax / L)) / L + keep &= ~(np.array([d == (bname, s_) for d in dom]) & (t > t1)) + +bm = bmesh.new(); bm.from_mesh(me); bm.verts.ensure_lookup_table() +if spec.get("template"): # loose items: the cloth template of the body file stands for the item (skirt, cloak) + tpl = bpy.data.objects[spec["template"]] + bm.free(); bm = bmesh.new(); bm.from_mesh(tpl.data); bm.verts.ensure_lookup_table() + keep = np.ones(len(bm.verts), bool) + nrm = np.zeros((len(bm.verts), 3)) + spec = dict(spec, thickness=spec.get("thickness", 0.0)) +for v in bm.verts: + v.co += type(v.co)(nrm[v.index] * spec["thickness"]) +for lay in list(bm.verts.layers.deform): # the replica must not inherit the body's group indices: uo_bind_item makes its own groups + bm.verts.layers.deform.remove(lay) +bmesh.ops.delete(bm, geom=[v for v in bm.verts if not keep[v.index]], context="VERTS") +item_me = bpy.data.meshes.new("test_" + os.environ["UO_TEST_ITEM"]); bm.to_mesh(item_me); bm.free() +item = bpy.data.objects.new(item_me.name, item_me); item.matrix_world = (bpy.data.objects[spec["template"]].matrix_world if spec.get("template") else body.matrix_world).copy() + +clo = bpy.data.collections["Clothing"] +shirt = bpy.data.objects.get("Example_Shirt") +if shirt is not None: + item_me.materials.append(shirt.active_material) # the UO look; colours do not matter for the silhouette tests +for o in list(clo.all_objects): + for c in [c for c in bpy.data.collections if o.name in c.objects]: + c.objects.unlink(o) +clo.objects.link(item) +bpy.context.view_layer.update() +for o in bpy.context.view_layer.objects: + o.select_set(False) +item.select_set(True); bpy.context.view_layer.objects.active = item + + +def run(script, **over): + text = open(os.path.join(scripts, script)).read() + for k, v in over.items(): + text, n = re.subn(r"^%s\s*=.*$" % k, "%s = %r" % (k, v), text, count=1, flags=re.M) + assert n == 1, (script, k) + exec(compile(text, script, "exec"), {"__name__": "__main__"}) + + +if os.environ.get("UO_TEST_FIT") == "1": + run("uo_fit_item.py", KIND=os.environ["UO_TEST_ITEM"], **({"MIN_GAP": float(os.environ["UO_TEST_MIN_GAP"])} if "UO_TEST_MIN_GAP" in os.environ else {})) +run("uo_bind_item.py", PART=spec["part"]) +print("test_items_pre: %s -> %d vertices, %d faces, PART=%s" % (item.name, len(item_me.vertices), len(item_me.polygons), spec["part"])) diff --git a/third_party/UO_Model3D_v13/pipeline/test_materials.py b/third_party/UO_Model3D_v13/pipeline/test_materials.py new file mode 100644 index 0000000..750d7aa --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_materials.py @@ -0,0 +1,101 @@ +"""Test of uo_materials.py: a sphere in front of the chest with a foreign PBR material (metallic, rough, image texture) is converted to the UO look and +rendered (Cycles, 04_stand); it must come out exactly as the same sphere with the plain UO_Look material of the same albedo (flat colour case), keep the +texture (checker case), and cut out transparent texels (alpha case). + + python test_materials.py [--tmp DIR] +""" +import argparse, os, subprocess, sys, tempfile + +import numpy as np + +HERE = os.path.dirname(os.path.abspath(__file__)) +PRE = r''' +import bpy, os, numpy as np +V = os.environ["MAT_VARIANT"] +col = (0.55, 0.30, 0.12, 1.0) +bpy.ops.mesh.primitive_uv_sphere_add(radius=0.18, location=(0, -0.05, 1.35), segments=32, ring_count=16) +ob = bpy.context.active_object; ob.name = "T_" + V +for p in ob.data.polygons: p.use_smooth = True +clo = bpy.data.collections["Clothing"] +for o in list(clo.all_objects): bpy.data.objects.remove(o, do_unlink=True) +for c in list(ob.users_collection): c.objects.unlink(ob) +clo.objects.link(ob) +ng = bpy.data.node_groups["UO_Look"] +mat = bpy.data.materials.new("M_" + V); mat.use_nodes = True +nt = mat.node_tree +if V == "ref": + nt.nodes.clear() + o = nt.nodes.new("ShaderNodeOutputMaterial"); g = nt.nodes.new("ShaderNodeGroup"); g.node_tree = ng + g.inputs["Albedo"].default_value = col; nt.links.new(g.outputs["Shader"], o.inputs["Surface"]) +else: + b = next(n for n in nt.nodes if n.type == "BSDF_PRINCIPLED") + b.inputs["Metallic"].default_value = 1.0 if V in ("raw", "metal") else 0.0; b.inputs["Roughness"].default_value = 0.15 + if V in ("flat", "raw", "metal"): + img = bpy.data.images.new("t", 8, 8, alpha=True); img.colorspace_settings.name = "Non-Color"; px = np.tile(np.array(col, np.float32), 64); img.pixels.foreach_set(px) + elif V == "checker": + img = bpy.data.images.new("t", 64, 64, alpha=True); img.colorspace_settings.name = "Non-Color"; a = np.zeros((64, 64, 4), np.float32); a[..., 3] = 1 + a[...] = (0.8, 0.2, 0.2, 1); a[(np.arange(64)[:, None] // 8 + np.arange(64)[None] // 8) % 2 == 0] = (0.2, 0.3, 0.8, 1); img.pixels.foreach_set(a.ravel()) + elif V == "alpha": + img = bpy.data.images.new("t", 64, 64, alpha=True); img.colorspace_settings.name = "Non-Color"; a = np.zeros((64, 64, 4), np.float32); a[...] = col; a[:, :, 3] = (np.arange(64)[None] // 16 % 2) + img.pixels.foreach_set(a.ravel()) + tx = nt.nodes.new("ShaderNodeTexImage"); tx.image = img; tx.interpolation = "Closest" + nt.links.new(tx.outputs["Color"], b.inputs["Base Color"]) + if V == "alpha": nt.links.new(tx.outputs["Alpha"], b.inputs["Alpha"]) +ob.data.materials.append(mat) +bpy.ops.object.select_all(action="DESELECT"); ob.select_set(True); bpy.context.view_layer.objects.active = ob +if V not in ("ref", "raw"): # raw = the foreign material as it came (the "before" measurement) + text = open(os.path.join(os.environ["MAT_SCRIPTS"], "uo_materials.py")).read() + exec(compile(text, "uo_materials.py", "exec"), {"__name__": "__main__"}) +''' + + +def render(variant, tmp): + pre = os.path.join(tmp, "pre.py"); open(pre, "w").write(PRE) + out = os.path.join(tmp, variant) + env = dict(os.environ, MAT_VARIANT=variant, MAT_SCRIPTS=HERE) + r = subprocess.run([sys.executable, os.path.join(HERE, "run_render_headless.py"), os.path.join(HERE, "..", "model", "UO_Body_0x190.blend"), out, "--pre", pre, + 'LAYER="clothing"', 'ONLY=["04_stand"]'], capture_output=True, text=True, env=env) + for l in r.stdout.splitlines(): + if l.startswith(("uo_materials", " ")): + print(l) + if r.returncode: + sys.exit("render failed:\n%s\n%s" % (r.stdout[-1500:], r.stderr[-1500:])) + from PIL import Image + d = os.path.join(out, "clothing", "frames") + fs = sorted(os.path.join(dp, f) for dp, _, fn in os.walk(d) for f in fn if f.endswith(".png")) + return [np.array(Image.open(f).convert("RGBA")) for f in fs] + + +if __name__ == "__main__": + ap = argparse.ArgumentParser(); ap.add_argument("--tmp"); a = ap.parse_args() + tmp = os.path.abspath(a.tmp) if a.tmp else tempfile.mkdtemp(prefix="test_mat_") + os.makedirs(tmp, exist_ok=True) + res = {v: render(v, tmp) for v in ("ref", "raw", "flat", "metal", "checker", "alpha")} + ok = True + for v, fr in res.items(): + print("%-8s frames %d, opaque px %d, colours %d" % (v, len(fr), sum(int((f[..., 3] > 0).sum()) for f in fr), len({tuple(p) for f in fr for p in f[f[..., 3] > 0][:, :3]}))) + ref = res["ref"] + d = max(int(np.abs(f.astype(int) - g.astype(int)).max()) for f, g in zip(ref, res["flat"])) if len(ref) == len(res["flat"]) else 999 + dr = np.mean([np.abs(f.astype(int) - g.astype(int))[f[..., 3] > 0].mean() for f, g in zip(ref, res["raw"])]) + print("before (raw foreign PBR material vs UO look): mean channel difference %.1f of 255" % dr) + print("flat vs ref: max channel difference %d (0 = identical)" % d); ok &= d <= 1 + # metal: the highlight SPEC_STRENGTH * c^SPEC_POWER (linear) on top of the matte render, c = N.L recovered from the matte render of the same sphere + from scipy import ndimage + dec = lambda v: np.where(v <= 0.04045, v / 12.92, ((v + 0.055) / 1.055) ** 2.4) + enc = lambda l: np.where(l <= 0.0031308, l * 12.92, 1.055 * np.power(np.maximum(l, 0), 1 / 2.4) - 0.055) + err, gain = 0, 0 + for f, m in zip(res["flat"], res["metal"]): + sel = ndimage.binary_erosion(f[..., 3] > 0, iterations=2) + if not sel.any(): + continue + lin = dec(f[..., 0].astype(float) / 255)[sel] + c = np.clip((lin / 0.55 - 0.0798) / 0.9202, 0, 1) + pred = 255 * enc(lin + 1.0 * 0.55 * c ** 16) + err = max(err, float(np.abs(pred - m[..., 0][sel]).max())); gain = max(gain, float((m[..., 0][sel].astype(float) - f[..., 0][sel]).max())) + print("metal: highlight adds up to %.0f/255; prediction (1.0 * albedo * c^16) off by at most %.1f" % (gain, err)); ok &= gain > 40 and err <= 12 # c comes from an 8-bit render and is raised to the 16th power: a few levels of quantisation noise + nref = len({tuple(p) for f in ref for p in f[f[..., 3] > 0][:, :3]}); nchk = len({tuple(p) for f in res["checker"] for p in f[f[..., 3] > 0][:, :3]}) + print("checker: %d colours vs %d for the flat sphere" % (nchk, nref)); ok &= nchk > nref + areas = {v: sum(int((f[..., 3] > 0).sum()) for f in res[v]) for v in res} + print("alpha sphere area %.2f of the flat one" % (areas["alpha"] / areas["flat"])); ok &= 0.2 < areas["alpha"] / areas["flat"] < 0.95 # the inside of the far half shows through the cut-out + print("RESULT", "OK" if ok else "FAIL") + print("output in", tmp) diff --git a/third_party/UO_Model3D_v13/pipeline/test_real_item.py b/third_party/UO_Model3D_v13/pipeline/test_real_item.py new file mode 100644 index 0000000..18798f1 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_real_item.py @@ -0,0 +1,42 @@ +"""QA of a REAL item already bound in the .blend (collection Clothing, e.g. Example_Shirt) against the original sprite of the item it imitates. + + python test_real_item.py --anim 434 [--actions 04_stand,...] [--tmp DIR] [--out qa.json] [--img overlay.png] [--set NAME=VALUE] +Same metrics as test_items.py (IoU, outside, missing, strips, specks, colours), but no replica is built: the render of the Clothing collection is used +as it is. Sprites come from pipeline/body13/mul/anim_NNNN.vd (same bytes as the client). +""" +import argparse, json, os, subprocess, sys, tempfile + +import numpy as np +from PIL import Image + +import test_items as ti + +if __name__ == "__main__": + ap = argparse.ArgumentParser() + ap.add_argument("--blend", default=os.path.join(ti.HERE, "..", "model", "UO_Body_0x190.blend")) + ap.add_argument("--anim", type=int, required=True) + ap.add_argument("--actions", default=ti.DEFAULT_ACTIONS) + ap.add_argument("--canvas", default="256,256"); ap.add_argument("--anchor", default="128,192") + ap.add_argument("--tmp"); ap.add_argument("--out"); ap.add_argument("--img") + ap.add_argument("--set", action="append", default=[]) + a = ap.parse_args() + tmp = os.path.abspath(a.tmp) if a.tmp else tempfile.mkdtemp(prefix="test_real_") + canvas, anchor = tuple(int(x) for x in a.canvas.split(",")), tuple(int(x) for x in a.anchor.split(",")) + actions = a.actions.split(",") + cmd = [sys.executable, os.path.join(ti.HERE, "run_render_headless.py"), os.path.abspath(a.blend), tmp, 'LAYER="clothing"', "ONLY=%r" % (actions,), + "CANVAS=%r" % (canvas,), "ANCHOR=%r" % (anchor,)] + a.set + r = subprocess.run(cmd, capture_output=True, text=True) + if r.returncode: + sys.exit("render failed:\n%s\n%s" % (r.stdout[-2000:], r.stderr[-2000:])) + ti.ITEMS["real"] = dict(anim=a.anim) + show = {("04_stand", 0, 0), ("09_attack_1h_slash", 3, 1), ("16_spell_directed", 3, 0), ("21_die_forward", 3, 2), ("00_walk_unarmed", 3, 1)} + rows, blocks, imgs = ti.measure(os.path.join(tmp, "clothing", "frames"), "real", canvas, anchor, show) + s = ti.summarize(rows, blocks) + print("anim %d: frames %d IoU %.3f outside %.1f missing %.1f strip %.1f pieces %.2f clipped %d colors %d | %s" % ( + a.anim, s["frames"], s["iou"], s["outside"], s["missing"], s["strip"], s["pieces"], s["clipped"], s["colors_max"], + " ".join("%s:%.2f" % (k, v) for k, v in s["by_action"].items()))) + if a.out: + json.dump(dict(anim=a.anim, canvas=canvas, anchor=anchor, actions=actions, result=s), open(a.out, "w"), indent=1) + if a.img and imgs: + im = np.concatenate([np.pad(i[max(anchor[1] - 90, 0):anchor[1] + 36, max(anchor[0] - 45, 0):anchor[0] + 45], ((1, 1), (1, 1), (0, 0)), constant_values=90) for i in imgs], 1) + Image.fromarray(im).resize((im.shape[1] * 2, im.shape[0] * 2), Image.NEAREST).save(a.img) diff --git a/third_party/UO_Model3D_v13/pipeline/test_tall_item.py b/third_party/UO_Model3D_v13/pipeline/test_tall_item.py new file mode 100644 index 0000000..c8a00fe --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_tall_item.py @@ -0,0 +1,50 @@ +"""A 3.5 m tall pole next to the body: cut by the old 136x120 canvas, whole on 256x256 / (128, 192). + + python test_tall_item.py [--blend ../model/UO_Body_0x190.blend] [--tmp DIR] +Adds the pole (not bound to the rig) to the Clothing collection through run_render_headless.py --pre, renders 04_stand +and checks the top of the pole in the frames and in the .vd written for the canvas. +""" +import argparse, os, subprocess, sys, tempfile +import numpy as np +from PIL import Image + +HERE = os.path.dirname(os.path.abspath(__file__)) +PRE = ''' +import bmesh +me = bpy.data.meshes.new("test_pole"); bm = bmesh.new() +bmesh.ops.create_cone(bm, cap_ends=True, segments=12, radius1=0.03, radius2=0.03, depth=3.5, matrix=__import__("mathutils").Matrix.Translation((0.5, -0.3, 1.75))) +bm.to_mesh(me); bm.free() +ob = bpy.data.objects.new("test_pole", me) +for o in bpy.data.collections["Clothing"].all_objects: + o.hide_render = True +bpy.data.collections["Clothing"].objects.link(ob) +''' + + +def run(blend, out, canvas, anchor, pre): + cmd = [sys.executable, os.path.join(HERE, "run_render_headless.py"), blend, out, "--pre", pre, 'LAYER="clothing"', 'ONLY=["04_stand"]', + "CANVAS=%r" % (canvas,), "ANCHOR=%r" % (anchor,), "BODY_GAP=0", "EXACT_BODY=False"] + r = subprocess.run(cmd, capture_output=True, text=True) + if r.returncode: + sys.exit("render failed:\n" + r.stdout[-1500:] + r.stderr[-1500:]) + return np.array(Image.open(os.path.join(out, "clothing", "frames", "04_stand", "dir0", "00.png")).convert("RGBA")) + + +if __name__ == "__main__": + ap = argparse.ArgumentParser() + ap.add_argument("--blend", default=os.path.join(HERE, "..", "model", "UO_Body_0x190.blend")) + ap.add_argument("--tmp") + a = ap.parse_args() + tmp = os.path.abspath(a.tmp) if a.tmp else tempfile.mkdtemp(prefix="test_tall_") + os.makedirs(tmp, exist_ok=True) + pre = os.path.join(tmp, "pre.py"); open(pre, "w").write(PRE) + old = run(os.path.abspath(a.blend), os.path.join(tmp, "old"), (136, 120), (68, 86), pre) + new = run(os.path.abspath(a.blend), os.path.join(tmp, "new"), (256, 256), (128, 192), pre) + rows = lambda im: np.nonzero(im[..., 3] > 0)[0] + o_top, n_top = rows(old).min(), rows(new).min() + n_up = 192 - n_top # rows above the anchor row + th = np.radians(28.4557) # camera elevation; the pole stands 0.3 m towards the camera, radius 3 cm + exp_px = ((3.5 - 0.07) * np.cos(th) + (-0.3 + 0.03) * np.sin(th)) * 36 + print("old canvas: topmost pole row %d (0 = cut by the canvas) | 256x256: top at row %d = %d px above the anchor, expected ~%.0f" % (o_top, n_top, n_up, exp_px)) + ok = o_top == 0 and n_top > 0 and abs(n_up - exp_px) < 3 + print("OK" if ok else "FAIL"); sys.exit(0 if ok else 1) diff --git a/third_party/UO_Model3D_v13/pipeline/test_weapon_roll.py b/third_party/UO_Model3D_v13/pipeline/test_weapon_roll.py new file mode 100644 index 0000000..427cdb4 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_weapon_roll.py @@ -0,0 +1,95 @@ +"""Roll QA: a flat plate shaped like the head of an original weapon (learned from its sprites by weapon_roll_fit.py), bound to the class weapon bone and +rendered through the whole pipeline (uo_bind_item + render_uo_layer) against the original weapon sprite, with the roll of the class per pose (mode class) +or one fixed roll (mode const) or no roll at all (mode none). + + python test_weapon_roll.py --anim 613 --roll ROLLDIR --vd VDDIR/anim [--mode class|const|none] [--actions 04_stand,...] [--tmp DIR] [--out qa.json] + +ROLLDIR holds roll_.json and cells_.npy (weapon_roll_fit.py). Per frame: IoU, symmetric chamfer (px, capped at 15) and the tolerant mismatch +(px further than 1 px from the other mask) of the rendered plate and the sprite. +""" +import argparse, json, os, subprocess, sys, tempfile +import numpy as np +from PIL import Image +from scipy import ndimage + +HERE = os.path.dirname(os.path.abspath(__file__)) +sys.path.insert(0, os.path.join(HERE, "..", "vdtool")) +import vdtool # noqa: E402 + +BONE_PART = {"polearm.L": "polearm", "axe2h.L": "axe2h", "bow.L": "bow", "weapon1h.R": "weapon1h"} +DEFAULT_ACTIONS = "04_stand,03_run_armed,08_combat_idle_2h,09_attack_1h_slash,12_attack_2h_bash,13_attack_2h_slash,14_attack_2h_pierce,21_die_forward,30_block" + + +def sprite_mask(blk, ai, d, i): + G = np.zeros((256, 256), bool); b = blk.get((ai, d)) + if b is not None and i < len(b["frames"]): + f = b["frames"][i]; rgba = vdtool.frame_rgba(f, b["palette"]); h, w = rgba.shape[:2]; x0, y0 = 128 - f["cx"], 192 - f["cy"] - f["h"] + ys, xs = slice(max(y0, 0), min(y0 + h, 256)), slice(max(x0, 0), min(x0 + w, 256)) + if ys.stop > ys.start and xs.stop > xs.start: + G[ys, xs] = rgba[ys.start - y0:ys.stop - y0, xs.start - x0:xs.stop - x0, 3] > 0 + return G + + +def measure(out, blk, only): + rows = [] + box = np.ones((3, 3), bool) + for act in only: + ai = int(act[:2]) + for d in range(5): + fdir = os.path.join(out, "clothing", "frames", act, "dir%d" % d) + if not os.path.isdir(fdir): + continue + for fn in sorted(os.listdir(fdir)): + i = int(fn[:2]); R = np.array(Image.open(os.path.join(fdir, fn)).convert("RGBA"))[..., 3] > 0 + G = sprite_mask(blk, ai, d, i) + if G.sum() < 4: + continue + if R.sum() < 1: + ch, mm = 15.0, float(G.sum()) + else: + dg = ndimage.distance_transform_edt(~G); dr = ndimage.distance_transform_edt(~R) + ch = 0.5 * (min(dg[R].mean(), 15) + min(dr[G].mean(), 15)) + mm = float((R & ~ndimage.binary_dilation(G, box)).sum() + (G & ~ndimage.binary_dilation(R, box)).sum()) + rows.append(dict(a=ai, d=d, i=i, iou=float((R & G).sum() / max((R | G).sum(), 1)), chamfer=float(ch), mismatch=mm)) + return rows + + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument("--anim", type=int, required=True); ap.add_argument("--roll", required=True); ap.add_argument("--vd", required=True) + ap.add_argument("--mode", default="class"); ap.add_argument("--actions", default=DEFAULT_ACTIONS); ap.add_argument("--thick", type=float, default=0.012) + ap.add_argument("--blend", default=os.path.join(HERE, "..", "model", "UO_Body_0x190.blend")); ap.add_argument("--tmp"); ap.add_argument("--out") + ap.add_argument("--reuse", action="store_true") + a = ap.parse_args() + tmp = os.path.abspath(a.tmp or tempfile.mkdtemp(prefix="test_weapon_roll_")) + cls = None + for fn in os.listdir(a.roll): + if fn.startswith("roll_") and fn.endswith(".json"): + R = json.load(open(os.path.join(a.roll, fn))) + if str(a.anim) in R["weapons"]: + cls, RJ = R["cls"], R + W = RJ["weapons"][str(a.anim)] + cells = np.load(os.path.join(a.roll, "cells_%d.npy" % a.anim)) + WM = json.load(open(os.path.join(HERE, "weapon_motion.json")))[cls] + spec = dict(cls=cls, parent=WM["parent"], part=BONE_PART[cls], cells=cells.tolist(), step=0.015, thick=a.thick, delta=float(np.deg2rad(W["delta_deg"])), mode=a.mode, + phi=RJ["phi"] if a.mode == "class" else None, const=(W["const_abs_deg"] - W["delta_deg"]) if a.mode == "const" else 0.0) + env = dict(os.environ, UO_TR_SPEC=json.dumps(spec), UO_TR_SCRIPTS=HERE) + out = os.path.join(tmp, "%d_%s" % (a.anim, a.mode)); only = a.actions.split(",") + cmd = [sys.executable, os.path.join(HERE, "run_render_headless.py"), os.path.abspath(a.blend), out, "--pre", os.path.join(HERE, "test_weapon_roll_pre.py"), + "LAYER='clothing'", "ONLY=%r" % only, "EXACT_BODY=False", "EXACT_COLORS=False", "CANVAS=(256,256)", "ANCHOR=(128,192)"] + if not a.reuse: + subprocess.run(cmd, env=env, check=True) + meta = json.load(open(os.path.join(a.roll, "..", "..", "weapons_meta.json"))) if os.path.exists(os.path.join(a.roll, "..", "..", "weapons_meta.json")) else None + _, blocks = vdtool.read_vd(a.vd); blk = {(b["action"], b["dir"]): b for b in blocks} + rows = measure(out, blk, only) + f = lambda k: float(np.mean([r[k] for r in rows])) + res = dict(anim=a.anim, mode=a.mode, cls=cls, frames=len(rows), iou=f("iou"), chamfer=f("chamfer"), mismatch=f("mismatch"), + by_action={str(x): float(np.mean([r["mismatch"] for r in rows if r["a"] == x])) for x in sorted({r["a"] for r in rows})}) + print("anim %d %-5s frames %d IoU %.3f chamfer %.2f px tolerant mismatch %.1f px | per action: %s" % ( + a.anim, a.mode, res["frames"], res["iou"], res["chamfer"], res["mismatch"], " ".join("%s:%.0f" % kv for kv in res["by_action"].items()))) + if a.out: + json.dump(res, open(a.out, "w"), indent=1) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/test_weapon_roll_pre.py b/third_party/UO_Model3D_v13/pipeline/test_weapon_roll_pre.py new file mode 100644 index 0000000..a7bddef --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_weapon_roll_pre.py @@ -0,0 +1,62 @@ +"""Pre-script of test_weapon_roll.py (run inside Blender by run_render_headless.py --pre): a flat plate (the head learned by weapon_roll_fit.py, cells +(s, u) in m along the class line and across it) in Rest Position on the class line of the weapon bone, turned about the shaft by the offset of this weapon, +bound with uo_bind_item.py; the class bone is re-keyed with the roll per pose (roll composed into the pose turn: R' = R * Rot_u(phi)). +Spec in the env var UO_TR_SPEC = json {cls, parent, part, cells, step, thick, delta, phi: {"a,i": deg} or null, const: deg}.""" +import bpy, json, os, re, math +import numpy as np +from mathutils import Vector, Matrix + +spec = json.loads(os.environ["UO_TR_SPEC"]); scripts = os.environ["UO_TR_SCRIPTS"] +cls = spec["cls"] +WM = json.loads(bpy.data.texts["weapon_motion.json"].as_string()) +C = WM[cls]; u = np.array(C["dir"], float); u /= np.linalg.norm(u); piv = np.array(C["pivot"], float) + + +def rot(axis, ang): + return Matrix.Rotation(ang, 3, Vector(axis)) + + +x = np.array([1.0, 0, 0]); e1 = x - (x @ u) * u +if np.linalg.norm(e1) < 0.3: + x = np.array([0, 1.0, 0]); e1 = x - (x @ u) * u +e1 /= np.linalg.norm(e1) + +# 1. the roll per pose through the "roll" field of the class (what uo_weapon_bones.py keys), re-keyed with the uo_weapon_bones.py of this repo +phi = spec.get("phi"); const = math.radians(spec.get("const", 0.0)); mode = spec["mode"] +C.pop("roll", None) +if mode == "class": + C["roll"] = dict(phi={k: math.radians(v) for k, v in phi.items()}) +elif mode == "const": + C["roll"] = dict(phi={k: const for k in C["poses"]}) +t = bpy.data.texts["weapon_motion.json"]; t.clear(); t.write(json.dumps(WM)) +src = open(os.path.join(scripts, "uo_weapon_bones.py")).read() +exec(compile(src, "uo_weapon_bones.py", "exec"), {"__name__": "__main__"}) + +# 2. the plate +rig = bpy.data.objects["UO_Rig"] +H = rig.matrix_world @ rig.data.bones[spec["parent"]].matrix_local +ru = np.array(rot(u, spec["delta"]) @ Vector(e1)); rv = np.cross(u, ru) +step, th = spec["step"], spec["thick"] +verts, faces = [], [] +for s, uu in spec["cells"]: + c = piv + u * s + ru * uu; b = len(verts) + for sx in (-1, 1): + for sy in (-1, 1): + for sz in (-1, 1): + q = c + u * sx * step / 2 + ru * sy * step / 2 + rv * sz * th / 2 + verts.append((H @ Vector(q))[:]) + faces += [(b + 0, b + 1, b + 3, b + 2), (b + 4, b + 6, b + 7, b + 5), (b + 0, b + 4, b + 5, b + 1), (b + 2, b + 3, b + 7, b + 6), + (b + 0, b + 2, b + 6, b + 4), (b + 1, b + 5, b + 7, b + 3)] +me = bpy.data.meshes.new("TestPlate"); me.from_pydata(verts, [], faces); me.update() +ob = bpy.data.objects.new("TestPlate", me) +if "Clothing" not in bpy.data.collections: + bpy.context.scene.collection.children.link(bpy.data.collections.new("Clothing")) +for o in list(bpy.data.collections["Clothing"].objects): + bpy.data.objects.remove(o) +bpy.data.collections["Clothing"].objects.link(ob) +mat = bpy.data.materials.get("UO_Look") or bpy.data.materials.get("UO_Skin") +if mat: me.materials.append(mat) +bpy.ops.object.select_all(action="DESELECT"); ob.select_set(True); bpy.context.view_layer.objects.active = ob +text = open(os.path.join(scripts, "uo_bind_item.py")).read() +text, k = re.subn(r"^PART\s*=.*$", "PART = %r" % spec["part"], text, count=1, flags=re.M); assert k == 1 +exec(compile(text, "uo_bind_item.py", "exec"), {"__name__": "__main__"}) diff --git a/third_party/UO_Model3D_v13/pipeline/test_weapons.py b/third_party/UO_Model3D_v13/pipeline/test_weapons.py new file mode 100644 index 0000000..7d4b465 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_weapons.py @@ -0,0 +1,79 @@ +"""Weapon QA: a thin shaft (replica of a weapon) rendered through the whole pipeline (uo_bind_item + render_uo_layer) against the original weapon sprite. + + python test_weapons.py --anim 648 --mode polearm|rigid --vd VDDIR [--rigid RIGID.json] [--actions 04_stand,12_attack_2h_bash,...] [--tmp DIR] [--out qa.json] + +mode polearm (or axe2h, bow, weapon1h; the last one is in the right hand): the shaft lies on the class line of weapon_motion.json (extent of that weapon) and is bound to the weapon bone (calibrated motion). +mode rigid: the shaft lies on the rigid line fitted for this weapon (weapon_fit.py rigid --out) and is bound to the hand it was fitted in (what was possible before). +Per frame: IoU and the symmetric chamfer distance (px) of the rendered shaft pixels and the sprite pixels (capped at 15 px). +""" +import argparse, json, os, subprocess, sys, tempfile +import numpy as np +from PIL import Image +from scipy import ndimage + +HERE = os.path.dirname(os.path.abspath(__file__)) +sys.path.insert(0, os.path.join(HERE, "..", "vdtool")) +import vdtool # noqa: E402 + +CLASS_BONE = {"polearm": "polearm.L", "axe2h": "axe2h.L", "bow": "bow.L", "weapon1h": "weapon1h.R"} +DEFAULT_ACTIONS = "04_stand,03_run_armed,08_combat_idle_2h,12_attack_2h_bash,13_attack_2h_slash,14_attack_2h_pierce,21_die_forward,30_block" + + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument("--anim", type=int, required=True); ap.add_argument("--mode", required=True); ap.add_argument("--vd", required=True) + ap.add_argument("--rigid"); ap.add_argument("--actions", default=DEFAULT_ACTIONS); ap.add_argument("--radius", type=float, default=0.03) + ap.add_argument("--blend", default=os.path.join(HERE, "..", "model", "UO_Body_0x190.blend")) + ap.add_argument("--motion", default=os.path.join(HERE, "weapon_motion.json")); ap.add_argument("--tmp"); ap.add_argument("--out"); ap.add_argument("--reuse", action="store_true", help="measure frames already rendered in --tmp") + a = ap.parse_args() + tmp = os.path.abspath(a.tmp or tempfile.mkdtemp(prefix="test_weapons_")) + if a.mode == "rigid": + R = json.load(open(a.rigid))["rigid"]; p, u = np.array(R["p0"]), np.array(R["u"]) + spec = dict(p=p.tolist(), u=u.tolist(), s0=0.0, s1=R["length"], part="weapon" if R.get("bone") == "hand.R" else "weapon.L", parent=R.get("bone", "hand.L")) + else: + C = json.load(open(a.motion))[CLASS_BONE[a.mode]]; ex = C["anims"][str(a.anim)] + spec = dict(p=C["pivot"], u=C["dir"], s0=ex[0], s1=ex[1], part=a.mode, parent=C["parent"]) + spec["radius"] = a.radius + env = dict(os.environ, UO_TW_SPEC=json.dumps(spec), UO_TW_SCRIPTS=HERE) + out = os.path.join(tmp, "%d_%s" % (a.anim, a.mode)) + only = [x for x in a.actions.split(",")] + cmd = [sys.executable, os.path.join(HERE, "run_render_headless.py"), os.path.abspath(a.blend), out, "--pre", os.path.join(HERE, "test_weapons_pre.py"), + 'LAYER="clothing"', "ONLY=%r" % only, "EXACT_BODY=False", "EXACT_COLORS=False", "CANVAS=(256,256)", "ANCHOR=(128,192)"] + cmd = [c.replace('LAYER="clothing"', "LAYER='clothing'") for c in cmd] + if not a.reuse: + subprocess.run(cmd, env=env, check=True) + _, blocks = vdtool.read_vd(os.path.join(a.vd, "anim_%04d.vd" % a.anim)); blk = {(b["action"], b["dir"]): b for b in blocks} + rows = [] + for act in only: + ai = int(act[:2]) + for d in range(5): + fdir = os.path.join(out, "clothing", "frames", act, "dir%d" % d) + if not os.path.isdir(fdir): + continue + for fn in sorted(os.listdir(fdir)): + i = int(fn[:2]); Rm = np.array(Image.open(os.path.join(fdir, fn)).convert("RGBA"))[..., 3] > 0 + b = blk.get((ai, d)); G = np.zeros((256, 256), bool) + if b is not None and i < len(b["frames"]): + f = b["frames"][i]; rgba = vdtool.frame_rgba(f, b["palette"]); h, w = rgba.shape[:2]; x0, y0 = 128 - f["cx"], 192 - f["cy"] - f["h"] + ys, xs = slice(max(y0, 0), min(y0 + h, 256)), slice(max(x0, 0), min(x0 + w, 256)) + if ys.stop > ys.start and xs.stop > xs.start: + G[ys, xs] = rgba[ys.start - y0:ys.stop - y0, xs.start - x0:xs.stop - x0, 3] > 0 + if G.sum() < 4: + continue + if Rm.sum() < 1: + ch = 15.0 + else: + dg = ndimage.distance_transform_edt(~G); dr = ndimage.distance_transform_edt(~Rm) + ch = 0.5 * (min(dg[Rm].mean(), 15) + min(dr[G].mean(), 15)) + rows.append(dict(a=ai, d=d, i=i, iou=float((Rm & G).sum() / max((Rm | G).sum(), 1)), chamfer=float(ch))) + f = lambda k: float(np.mean([r[k] for r in rows])) + res = dict(anim=a.anim, mode=a.mode, frames=len(rows), iou=f("iou"), chamfer=f("chamfer"), chamfer_median=float(np.median([r["chamfer"] for r in rows])), + by_action={str(x): float(np.mean([r["chamfer"] for r in rows if r["a"] == x])) for x in sorted({r["a"] for r in rows})}) + print("anim %d %-8s frames %d IoU %.3f chamfer mean %.2f median %.2f px | per action: %s" % ( + a.anim, a.mode, res["frames"], res["iou"], res["chamfer"], res["chamfer_median"], " ".join("%s:%.1f" % kv for kv in res["by_action"].items()))) + if a.out: + json.dump(res, open(a.out, "w"), indent=1) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/test_weapons_pre.py b/third_party/UO_Model3D_v13/pipeline/test_weapons_pre.py new file mode 100644 index 0000000..9f8330f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/test_weapons_pre.py @@ -0,0 +1,31 @@ +"""Pre-script of test_weapons.py (run inside Blender by run_render_headless.py --pre): a thin straight shaft in Rest Position along a line given in the +local frame of the hand bone `parent` (hand.L by default; spec in the env var UO_TW_SPEC = json {p, u, s0, s1, radius, part}), bound with uo_bind_item.py to the bone of `part`.""" +import bpy, json, os, re, math +import numpy as np +from mathutils import Vector, Matrix + +spec = json.loads(os.environ["UO_TW_SPEC"]) +rig = bpy.data.objects["UO_Rig"] +H = rig.matrix_world @ rig.data.bones[spec.get("parent", "hand.L")].matrix_local # hand frame at rest -> world +p, u = np.array(spec["p"]), np.array(spec["u"]) +a, b = H @ Vector(p + u * spec["s0"]), H @ Vector(p + u * spec["s1"]) +n, r = 12, spec["radius"] +axis = (b - a).normalized(); ref = Vector((0, 1, 0)) if abs(axis.y) < 0.9 else Vector((1, 0, 0)) +e1 = axis.cross(ref).normalized(); e2 = axis.cross(e1).normalized() +verts = [a + (e1 * math.cos(2 * math.pi * k / n) + e2 * math.sin(2 * math.pi * k / n)) * r for k in range(n)] + \ + [b + (e1 * math.cos(2 * math.pi * k / n) + e2 * math.sin(2 * math.pi * k / n)) * r for k in range(n)] +faces = [(k, (k + 1) % n, n + (k + 1) % n, n + k) for k in range(n)] + [tuple(range(n))[::-1], tuple(range(n, 2 * n))] +me = bpy.data.meshes.new("TestShaft"); me.from_pydata([v[:] for v in verts], [], faces); me.update() +ob = bpy.data.objects.new("TestShaft", me) +if "Clothing" not in bpy.data.collections: + bpy.context.scene.collection.children.link(bpy.data.collections.new("Clothing")) +for o in list(bpy.data.collections["Clothing"].objects): + bpy.data.objects.remove(o) +bpy.data.collections["Clothing"].objects.link(ob) +mat = bpy.data.materials.get("UO_Look") or bpy.data.materials.get("UO_Skin") +if mat: me.materials.append(mat) +bpy.ops.object.select_all(action="DESELECT"); ob.select_set(True); bpy.context.view_layer.objects.active = ob +scripts = os.path.dirname(os.path.abspath(os.environ["UO_TW_SPEC_FILE"])) if "UO_TW_SPEC_FILE" in os.environ else os.getcwd() +text = open(os.path.join(os.environ["UO_TW_SCRIPTS"], "uo_bind_item.py")).read() +text, k = re.subn(r"^PART\s*=.*$", "PART = %r" % spec["part"], text, count=1, flags=re.M); assert k == 1 +exec(compile(text, "uo_bind_item.py", "exec"), {"__name__": "__main__"}) diff --git a/third_party/UO_Model3D_v13/pipeline/texbake.py b/third_party/UO_Model3D_v13/pipeline/texbake.py new file mode 100644 index 0000000..126a209 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/texbake.py @@ -0,0 +1,154 @@ +"""Project sprite colours onto the model's UV texture (5 views + mirror-partner samples).""" +import numpy as np +from body import ANCHOR_X, ANCHOR_Y + + +def cam_basis(theta, d): + yaw = -d * np.pi / 4 + c, s = np.cos(-yaw), np.sin(-yaw) + Rz = np.array([[c, -s, 0], [s, c, 0], [0, 0, 1.0]]) + right = Rz @ np.array([1.0, 0, 0]) + up = Rz @ np.array([0, np.sin(theta), np.cos(theta)]) + fwd = np.cross(right, up) # toward camera + return right, up, fwd + + +def to_screen(p, theta, scale, d): + r, u, f = cam_basis(theta, d) + return np.stack([ANCHOR_X + scale * (p @ r), ANCHOR_Y - scale * (p @ u), p @ f], -1) + + +def tri_raster(pts2, fn, W, H): + """Rasterise triangles given 2D points (T,3,2); calls fn(tri_index, xs, ys, bary(n,3)) for covered pixel centres.""" + for t in range(len(pts2)): + a, b, c = pts2[t] + x0 = max(int(np.floor(min(a[0], b[0], c[0]))), 0) + x1 = min(int(np.ceil(max(a[0], b[0], c[0]))), W - 1) + y0 = max(int(np.floor(min(a[1], b[1], c[1]))), 0) + y1 = min(int(np.ceil(max(a[1], b[1], c[1]))), H - 1) + if x1 < x0 or y1 < y0: + continue + ys, xs = np.mgrid[y0:y1 + 1, x0:x1 + 1] + px = xs.ravel() + 0.5 + py = ys.ravel() + 0.5 + den = (b[1] - c[1]) * (a[0] - c[0]) + (c[0] - b[0]) * (a[1] - c[1]) + if abs(den) < 1e-12: + continue + l0 = ((b[1] - c[1]) * (px - c[0]) + (c[0] - b[0]) * (py - c[1])) / den + l1 = ((c[1] - a[1]) * (px - c[0]) + (a[0] - c[0]) * (py - c[1])) / den + l2 = 1 - l0 - l1 + m = (l0 >= -1e-4) & (l1 >= -1e-4) & (l2 >= -1e-4) + if m.any(): + fn(t, xs.ravel()[m], ys.ravel()[m], np.stack([l0[m], l1[m], l2[m]], 1)) + + +def zbuffer(vs, tris, W, H, ss): + """vs: (N,3) screen x,y (canvas px), depth-toward-camera. Returns zbuf (H*ss, W*ss).""" + zb = np.full((H * ss, W * ss), -np.inf) + p2 = vs[tris][..., :2] * ss + z = vs[tris][..., 2] + + def fn(t, xs, ys, bc): + zz = bc @ z[t] + np.maximum.at(zb, (ys, xs), zz) + tri_raster(p2, fn, W * ss, H * ss) + return zb + + +def vertex_normals(v, tris): + fn = np.cross(v[tris[:, 1]] - v[tris[:, 0]], v[tris[:, 2]] - v[tris[:, 0]]) + n = np.zeros_like(v) + for k in range(3): + np.add.at(n, tris[:, k], fn) + return n / np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12) + + +def erode(mask, it=1): + m = mask.copy() + for _ in range(it): + n = m.copy() + n[1:] &= m[:-1]; n[:-1] &= m[1:]; n[:, 1:] &= m[:, :-1]; n[:, :-1] &= m[:, 1:] + m = n + return m + + +def bake(tris, tri_uv, posed, mirror, sprites, theta, scale, size=1024, ss=4, mirror_w=0.6, eps=0.02): + """tris (T,3) vertex idx; tri_uv (T,3,2) in [0,1]; posed (N,3); mirror (N,) partner index; + sprites: list of 5 canvas RGBA uint8 (H,W,4) for file dirs 0..4. Returns RGBA float texture and weight map.""" + H, W = sprites[0].shape[:2] + nrm = vertex_normals(posed, tris) + # texel -> (triangle, barycentric) + tex_tri = np.full((size, size), -1, np.int64) + tex_bc = np.zeros((size, size, 3)) + + def fn(t, xs, ys, bc): + tex_tri[ys, xs] = t + tex_bc[ys, xs] = bc + uvpx = tri_uv.copy() + uvpx[..., 0] *= size + uvpx[..., 1] = (1 - uvpx[..., 1]) * size + tri_raster(uvpx, fn, size, size) + ys, xs = np.nonzero(tex_tri >= 0) + t = tex_tri[ys, xs] + bc = tex_bc[ys, xs] + acc = np.zeros((len(t), 3)) + wsum = np.zeros(len(t)) + # equalise overall brightness between directions (UO lights are fixed while the body turns) + means = [] + for img in sprites: + core = erode(img[..., 3] > 127, 1) + means.append(img[core][:, :3].mean()) + gains = np.mean(means) / np.array(means) + for use_mirror, wm in ((False, 1.0), (True, mirror_w)): + idx = tris[t] if not use_mirror else mirror[tris[t]] + P = np.einsum("nk,nkd->nd", bc, posed[idx]) + N = np.einsum("nk,nkd->nd", bc, nrm[idx]) + N /= np.maximum(np.linalg.norm(N, axis=1, keepdims=True), 1e-12) + for d in range(5): + scr_v = to_screen(posed, theta, scale, d) + zb = zbuffer(scr_v, tris, W, H, ss) + sp = to_screen(P, theta, scale, d) + _, _, fwd = cam_basis(theta, d) + facing = N @ fwd + xi = np.floor(sp[:, 0]).astype(int) + yi = np.floor(sp[:, 1]).astype(int) + zx = np.clip(np.floor(sp[:, 0] * ss).astype(int), 0, W * ss - 1) + zy = np.clip(np.floor(sp[:, 1] * ss).astype(int), 0, H * ss - 1) + inside = (xi >= 0) & (xi < W) & (yi >= 0) & (yi < H) + vis = inside & (sp[:, 2] >= zb[zy, zx] - eps) & (facing > 0.15) + img = sprites[d] + core = erode(img[..., 3] > 127, 1) # skip the dark 1-px outline of the sprite + a = np.zeros(len(t)) + a[vis] = img[yi[vis], xi[vis], 3] / 255.0 + vis &= a > 0.5 + incore = np.zeros(len(t), bool) + incore[vis] = core[yi[vis], xi[vis]] + w = np.where(vis, facing ** 2, 0.0) * wm * np.where(incore, 1.0, 0.05) + col = np.zeros((len(t), 3)) + col[vis] = img[yi[vis], xi[vis], :3] * gains[d] + acc += col * w[:, None] + wsum += w + tex = np.zeros((size, size, 3)) + wt = np.zeros((size, size)) + ok = wsum > 1e-6 + tex[ys[ok], xs[ok]] = acc[ok] / wsum[ok, None] + wt[ys[ok], xs[ok]] = 1.0 + return tex, wt, (tex_tri >= 0) + + +def pull_push_fill(tex, wt): + """Fill holes (wt==0) from coarser mip levels.""" + levels = [(tex * wt[..., None], wt.copy())] + while levels[-1][1].shape[0] > 1: + c, w = levels[-1] + h = c.shape[0] // 2 + c2 = c[:2 * h, :2 * h].reshape(h, 2, h, 2, 3).sum((1, 3)) + w2 = w[:2 * h, :2 * h].reshape(h, 2, h, 2).sum((1, 3)) + levels.append((c2, w2)) + col = levels[-1][0] / np.maximum(levels[-1][1], 1e-9)[..., None] + for c, w in reversed(levels[:-1]): + up = np.repeat(np.repeat(col, 2, 0), 2, 1)[: c.shape[0], : c.shape[1]] + own = c / np.maximum(w, 1e-9)[..., None] + a = np.clip(w, 0, 1)[..., None] + col = own * a + up * (1 - a) + return col diff --git a/third_party/UO_Model3D_v13/pipeline/uo_bind_item.py b/third_party/UO_Model3D_v13/pipeline/uo_bind_item.py new file mode 100644 index 0000000..d0ad6b6 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_bind_item.py @@ -0,0 +1,298 @@ +# Bind the SELECTED item meshes to the UO body in one go: parent + Armature modifier + skin weights + shape corrections. +# 1. Model the item on the body in Rest Position, put it in the "Clothing" collection (keep it under ~10k vertices). +# 2. Set PART to the kind of item (e.g. "chest" for a breastplate, "gloves" for gloves), select it and run (Alt+P). +# Every item vertex follows the skin right under it (MAP = "under"); weights and shape corrections are taken from +# that skin point and smoothed over the item (SMOOTH). "chest" moves most of the upper-arm weight to the +# collarbones, so the shoulders of a breastplate stay on the shoulders while the arms move under it. +# Run it again after you change the item's shape (old weights and "uo_" corrections are replaced). Your own shape +# keys (names not starting with "uo_") are kept. The finger, twist and toe bones of the v13 body count as the hand, +# arm and foot in PARTS (e.g. "gloves" follows the fingers too). +import bpy +import numpy as np +from mathutils import Vector +from mathutils.bvhtree import BVHTree +from mathutils.geometry import barycentric_transform + +PART = "all" # kind of item, see PARTS below (e.g. "chest" for a breastplate, "gloves" for gloves) +MAP = "under" # "under": follow the skin right under each vertex (along its normal); "nearest": nearest skin +SMOOTH = 4 # smoothing passes of weights and corrections over the item (0 = off) +MAX_DIST = 0.15 # m, farthest skin an item vertex may follow along its normal +CORR_KEEP = 0.0 # 0..1: share of the skin corrections kept where FOLLOW moved weight to a parent bone +# PART: (bones the item may follow - None = all, FOLLOW = share of a limb bone's weight that stays on it; the rest goes +# to its parent bone: hand->forearm->upper_arm->clavicle, foot->shin->thigh->pelvis, head->neck). A FOLLOW of +# (share, t0, t1) grows along the bone: `share` near its joint (up to t0 of the bone length), 1.0 from t1 on - so in +# "chest" the pauldron on the shoulder rides on the collarbone while the sleeve further down follows the arm. +PARTS = { + "all": (None, {}), # robe, cloak, full suit: like the skin + "chest": (None, {"upper_arm": (0.2, 0.15, 0.45), "hand": 0.0, # breastplate / armour with + "thigh": (0.3, 0.1, 0.4), "foot": 0.0, "head": 0.0}), # pauldrons and sleeves + "torso": (["pelvis", "spine", "chest", "neck"], {}), # torso skin only + "shoulders": (["chest", "upper_arm.L", "upper_arm.R"], {}), # pauldrons + "arms": (["upper_arm.L", "forearm.L", "upper_arm.R", "forearm.R"], {}), # sleeves, arm armour + "gloves": (["forearm.L", "hand.L", "forearm.R", "hand.R"], {}), # gloves, gauntlets, bracers + "legs": (["pelvis", "thigh.L", "shin.L", "thigh.R", "shin.R"], {}), # leggings, trousers + "boots": (["shin.L", "foot.L", "shin.R", "foot.R"], {}), # boots, greaves + "helm": (["head"], {}), # helmet, hat, mask + "neck": (["neck", "chest", "head"], {}), # gorget, collar + # cloth (v13 body): weights from the cloth template (bone chains fitted to the original UO cloak / skirt frames) + "skirt": (["pelvis", "spine", "thigh.L", "thigh.R"], {}), # skirt, kilt: all on the skirt chains + "cloak": (["chest", "spine", "neck", "clavicle.L", "clavicle.R"], {}), # cloak, cape: all on the cloak chains + "robe": (None, {"hand": 0.0, "foot": 0.0, "head": 0.0}), # robe, dress: top like the skin, +} # below the waist the skirt chains, + # sleeves on the arms at any height +# PART -> (cloth template object, height band in m over which the item goes from the body weights to the template +# weights below the template's top; None = template weights only) +CLOTH = {"skirt": ("UO_Template_Skirt", None), "cloak": ("UO_Template_Cloak", None), "robe": ("UO_Template_Skirt", 0.35)} +# rigid items: every vertex 100 % on one bone (they do not bend): hair and beards (UO draws them rigid on the head), +# weapons, shields (left forearm), quivers (back). UO holds 2H weapons, staffs, bows and crossbows in the LEFT hand and 1H weapons in the right, +# and moves them differently from the hand: they ride on the weapon bones polearm.L / axe2h.L / bow.L / weapon1h.R (uo_weapon_bones.py, +# calibrated on the original weapons: model the shaft along the class line, see that script). "weapon" = rigid in hand.R and "weapon.L" = rigid +# in hand.L (no calibration). +RIGID = {"hair": "head", "beard": "head", "hat": "head", "weapon": "hand.R", "weapon.L": "hand.L", "weapon1h": "weapon1h.R", "shield": "shield.L", "quiver": "chest", + "polearm": "polearm.L", "staff": "polearm.L", "weapon2h": "polearm.L", "axe2h": "axe2h.L", "bow": "bow.L", "crossbow": "bow.L"} +PARENT = {"hand": "forearm", "forearm": "upper_arm", "upper_arm": "clavicle", "foot": "shin", "shin": "thigh", + "thigh": "pelvis", "head": "neck"} + +body = bpy.data.objects["UO_Body"] +rig = bpy.data.objects["UO_Rig"] +SUB = {"upper_arm_twist": "upper_arm", "forearm_twist": "forearm", "toe": "foot"} # extra bones -> their UO bone + + +def group_of(name): + """UO bone a body bone belongs to: finger / twist / toe bones count as hand / arm / foot""" + side = name[-2:] if name.endswith((".L", ".R")) else "" + base = name[:-2] if side else name + base = "hand" if base.startswith("finger") else SUB.get(base, base) + return base + side + + +def body_regions(allowed): + """Body skin triangles whose dominant bone is in `allowed`, plus the body vertex weights of those bones.""" + me = body.data + names = [g.name for g in body.vertex_groups] + W = np.zeros((len(me.vertices), len(names))) + for v in me.vertices: + for g in v.groups: + W[v.index, g.group] = g.weight + keep = [i for i, n in enumerate(names) if allowed is None or group_of(n) in allowed] + basis = np.empty(len(me.vertices) * 3, np.float32) + (me.shape_keys.key_blocks[0].data if me.shape_keys else me.vertices).foreach_get("co", basis) + basis = basis.reshape(-1, 3).astype(np.float64) + me.calc_loop_triangles() + tri = np.array([t.vertices[:] for t in me.loop_triangles]) + dom = W[tri].sum(1).argmax(1) # dominant bone of every triangle + tri = tri[np.isin(dom, keep)] + if not len(tri): + raise RuntimeError("no body skin for PART %r" % PART) + bvh = BVHTree.FromPolygons([Vector(p) for p in basis], tri.tolist()) + return bvh, tri, basis, W[:, keep], [names[i] for i in keep] + + +def cloth_blend(co, wv, bones, tpl_name, band): + """blend the body weights with the weights of the nearest point of the cloth template (all in body space); with a + band (robe) the parts on the arms (sleeves) keep the body weights at any height""" + tpl = bpy.data.objects.get(tpl_name) + if tpl is None: + raise RuntimeError("cloth template %s not found (v13 body file)" % tpl_name) + me = tpl.data + M = body.matrix_world.inverted() @ tpl.matrix_world + tco = np.array([M @ v.co for v in me.vertices]) + tn = [g.name for g in tpl.vertex_groups] + TW = np.zeros((len(me.vertices), len(tn))) + for v in me.vertices: + for g in v.groups: + TW[v.index, g.group] = g.weight + me.calc_loop_triangles() + ttri = np.array([t.vertices[:] for t in me.loop_triangles]) + bvh = BVHTree.FromPolygons([Vector(p) for p in tco], ttri.tolist()) + wt = np.zeros((len(co), len(tn))) + for i, p in enumerate(co): + loc, nrm, fi, dist = bvh.find_nearest(Vector(p)) + a, b, c = ttri[fi] + w = barycentric_transform(loc, Vector(tco[a]), Vector(tco[b]), Vector(tco[c]), + Vector((1, 0, 0)), Vector((0, 1, 0)), Vector((0, 0, 1))) + w = np.clip(np.array(w), 0, 1); w /= max(w.sum(), 1e-9) + wt[i] = w[0] * TW[a] + w[1] * TW[b] + w[2] * TW[c] + wt /= np.maximum(wt.sum(1, keepdims=True), 1e-9) + if band is None: + h = np.ones(len(co)) + else: + top = tco[:, 2].max() + arm = wv[:, [j for j, b in enumerate(bones) if group_of(b).split(".")[0] in ("upper_arm", "forearm", "hand")]].sum(1) + h = np.clip((top - co[:, 2]) / band, 0, 1) + h = h * h * (3 - 2 * h) * np.clip(1 - 2 * arm, 0, 1) # smooth; sleeves stay on the arms + names = list(bones) + [b for b in tn if b not in bones] + out = np.zeros((len(co), len(names))) + out[:, :len(bones)] = wv * (1 - h)[:, None] + for j, b in enumerate(tn): + out[:, names.index(b)] += wt[:, j] * h + return out, names + + +def bind(ob, allowed): + bvh, tri, basis, W, bones = body_regions(allowed) + M = body.matrix_world.inverted() @ ob.matrix_world # item space -> body space + n = len(ob.data.vertices) + co = np.empty(n * 3, np.float32) + if ob.data.shape_keys: + ob.data.shape_keys.key_blocks[0].data.foreach_get("co", co) + else: + ob.data.vertices.foreach_get("co", co) + co = np.array([M @ Vector(p) for p in co.reshape(-1, 3)]) # body space + ob.data.calc_loop_triangles() + itri = np.array([t.vertices[:] for t in ob.data.loop_triangles]).reshape(-1, 3) + fn = np.cross(co[itri[:, 1]] - co[itri[:, 0]], co[itri[:, 2]] - co[itri[:, 0]]) + vn = np.zeros_like(co) + for k in range(3): + np.add.at(vn, itri[:, k], fn) + vn /= np.maximum(np.linalg.norm(vn, axis=1, keepdims=True), 1e-12) + idx = np.zeros((n, 3), int); bary = np.zeros((n, 3)) + for i, p in enumerate(co): + p = Vector(p) + loc, nrm, fi, dist = bvh.find_nearest(p) + if MAP == "under" and (p - loc).dot(nrm) > 0: # vertex outside the body: skin under it + best = None + for d in (-Vector(vn[i]), Vector(vn[i])): # normals may point either way + hit = bvh.ray_cast(p, d, MAX_DIST) + if hit[0] is not None and (p - hit[0]).dot(hit[1]) > 0 and (best is None or hit[3] < best[3]): + best = hit + if best is not None and best[3] < max(3 * dist, dist + 0.05): + loc, nrm, fi, dist = best + a, b, c = tri[fi] + w = barycentric_transform(loc, Vector(basis[a]), Vector(basis[b]), Vector(basis[c]), + Vector((1, 0, 0)), Vector((0, 1, 0)), Vector((0, 0, 1))) + idx[i] = a, b, c; bary[i] = np.clip(w, 0, 1); bary[i] /= max(bary[i].sum(), 1e-9) + edges = np.array([e.vertices[:] for e in ob.data.edges]).reshape(-1, 2) + deg = np.bincount(edges.ravel(), minlength=n).astype(float)[:, None] + + def smooth(x): + for _ in range(SMOOTH): + acc = np.zeros_like(x) + np.add.at(acc, edges[:, 0], x[edges[:, 1]]); np.add.at(acc, edges[:, 1], x[edges[:, 0]]) + x = np.where(deg > 0, 0.5 * x + 0.5 * acc / np.maximum(deg, 1), x) + return x + + # --- skin weights: body weights at the nearest skin point, only the PART bones, normalised + wv = smooth((W[idx] * bary[..., None]).sum(1)) + s = wv.sum(1, keepdims=True) + wv = np.where(s > 1e-6, wv / np.maximum(s, 1e-9), 0) + lost = s[:, 0] <= 1e-6 # no weight of the part here: nearest bone of the part + if lost.any(): + wv[lost, W[idx[lost, 0]].argmax(1)] = 1.0 + moved = np.zeros(n) + bones = list(bones) + for base in ("hand", "forearm", "upper_arm", "foot", "shin", "thigh", "head"): # distal first, so chains fold + if base not in FOLLOW: + continue + for side in ((".L", ".R") if base != "head" else ("",)): + b, pb = base + side, PARENT[base] + ("" if PARENT[base] in ("pelvis", "neck") else side) + if b not in rig.data.bones or pb not in rig.data.bones: + continue + f = FOLLOW[base] + if isinstance(f, tuple): # share grows along the bone (t = 0 joint, 1 end) + bone = rig.data.bones[b] + to_body = body.matrix_world.inverted() @ rig.matrix_world + h, t_ = np.array(to_body @ bone.head_local), np.array(to_body @ bone.tail_local) + t = ((co - h) @ (t_ - h)) / max(((t_ - h) ** 2).sum(), 1e-12) + f = f[0] + (1 - f[0]) * np.clip((t - f[1]) / max(f[2] - f[1], 1e-6), 0, 1) + for j in [j for j, nm in enumerate(bones) if group_of(nm) == b]: # the bone + its finger / twist / toe bones + mv = wv[:, j] * (1 - f) + wv[:, j] -= mv; moved += mv + if pb in bones: + wv[:, bones.index(pb)] += mv + else: + wv = np.c_[wv, mv]; bones.append(pb) + moved = np.clip(moved, 0, 1) + if PART in CLOTH: + wv, bones = cloth_blend(co, wv, bones, *CLOTH[PART]) + moved = np.ones(n) + body_bones = {g.name for g in body.vertex_groups} | {b.name for b in rig.data.bones} + for g in [g for g in ob.vertex_groups if g.name in body_bones or g.name.startswith("clavicle")]: + ob.vertex_groups.remove(g) + for j, name in enumerate(bones): + nz = np.nonzero(wv[:, j] > 1e-4)[0] + if len(nz): + g = ob.vertex_groups.new(name=name) + for i in nz: + g.add([int(i)], float(wv[i, j]), "REPLACE") + + # --- parent + Armature modifier + if ob.parent != rig: + mw = ob.matrix_world.copy() + ob.parent = rig; ob.matrix_parent_inverse = rig.matrix_world.inverted(); ob.matrix_world = mw + arm = next((m for m in ob.modifiers if m.type == "ARMATURE"), None) + if arm is None: + arm = ob.modifiers.new("Armature", "ARMATURE") + try: + ob.modifiers.move(len(ob.modifiers) - 1, 0) + except Exception: + pass + arm.object = rig; arm.use_vertex_groups = True; arm.use_bone_envelopes = False + + # --- shape corrections of the same skin points (only a body with corrective shape keys, v12) + if ob.data.shape_keys: + for k in [k for k in ob.data.shape_keys.key_blocks if k.name.startswith("uo_")]: + ob.shape_key_remove(k) + if body.data.shape_keys is None or not any(k.name.startswith("uo_") for k in body.data.shape_keys.key_blocks): + print("uo_bind_item: %s -> PART %s, bones %s" % (ob.name, PART, bones)) + return + kb = body.data.shape_keys.key_blocks + R = np.array((body.matrix_world.inverted() @ ob.matrix_world).to_3x3().inverted()) # body offsets -> item space + if ob.data.shape_keys is None: + ob.shape_key_add(name="Basis", from_mix=False) + for k in [k for k in ob.data.shape_keys.key_blocks if k.name.startswith("uo_")]: + ob.shape_key_remove(k) + obasis = np.empty(n * 3, np.float32); ob.data.shape_keys.key_blocks[0].data.foreach_get("co", obasis) + obasis = obasis.reshape(-1, 3).astype(np.float64) + drivers = {d.data_path: d for d in body.data.shape_keys.animation_data.drivers} + nb = len(body.data.vertices); buf = np.empty(nb * 3, np.float32) + keys = [k for k in kb if k.name.startswith("uo_")] + for k in keys: + k.data.foreach_get("co", buf) + off = buf.reshape(-1, 3) - basis + o = smooth((off[idx] * bary[..., None]).sum(1) * (1 - moved * (1 - CORR_KEEP))[:, None]) @ R.T + sk = ob.shape_key_add(name=k.name, from_mix=False) + sk.data.foreach_set("co", (obasis + o).ravel().astype(np.float32)) + src = drivers['key_blocks["%s"].value' % k.name].driver + d = sk.driver_add("value").driver; d.type = "SCRIPTED" + for sv in src.variables: + v = d.variables.new(); v.name = sv.name; v.type = sv.type + v.targets[0].id_type = sv.targets[0].id_type; v.targets[0].id = sv.targets[0].id + v.targets[0].data_path = sv.targets[0].data_path + d.expression = src.expression + print("uo_bind_item: %s -> PART %s, bones %s, %d corrections" % (ob.name, PART, bones, len(keys))) + + +def bind_rigid(ob, bone): + body_bones = {g.name for g in body.vertex_groups} + for g in [g for g in ob.vertex_groups if g.name in body_bones]: + ob.vertex_groups.remove(g) + g = ob.vertex_groups.new(name=bone); g.add(list(range(len(ob.data.vertices))), 1.0, "REPLACE") + if ob.parent != rig: + mw = ob.matrix_world.copy() + ob.parent = rig; ob.matrix_parent_inverse = rig.matrix_world.inverted(); ob.matrix_world = mw + arm = next((m for m in ob.modifiers if m.type == "ARMATURE"), None) or ob.modifiers.new("Armature", "ARMATURE") + arm.object = rig; arm.use_vertex_groups = True; arm.use_bone_envelopes = False + if ob.data.shape_keys: + for k in [k for k in ob.data.shape_keys.key_blocks if k.name.startswith("uo_")]: + ob.shape_key_remove(k) + print("uo_bind_item: %s -> rigid on %s" % (ob.name, bone)) + + +if PART not in PARTS and PART not in RIGID: + raise ValueError("PART must be one of %s" % (list(PARTS) + list(RIGID))) +FOLLOW = PARTS[PART][1] if PART in PARTS else {} +pose = rig.data.pose_position +rig.data.pose_position = "REST" +bpy.context.view_layer.update() +try: + for ob in [o for o in bpy.context.selected_objects if o.type == "MESH" and o != body]: + if PART in RIGID: + bone = RIGID[PART] + if bone not in rig.data.bones: # older file without the shield / weapon bones + bone = {"shield.L": "forearm.L", "polearm.L": "hand.L", "axe2h.L": "hand.L", "bow.L": "hand.L", "weapon1h.R": "hand.R"}.get(bone, bone) + bind_rigid(ob, bone) + else: + bind(ob, PARTS[PART][0]) +finally: + rig.data.pose_position = pose diff --git a/third_party/UO_Model3D_v13/pipeline/uo_cloth_bake.py b/third_party/UO_Model3D_v13/pipeline/uo_cloth_bake.py new file mode 100644 index 0000000..e7f9a11 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_cloth_bake.py @@ -0,0 +1,612 @@ +# Cloth simulation for loose items (robe, dress, skirt, cloak): the hanging part falls, swings and collides with the +# body instead of following the bones rigidly. Run it AFTER uo_bind_item.py, with the items selected (Alt+P). +# 1. A simplified copy of the item (about SIM_VERTS vertices) is simulated with Blender's Cloth physics. What the +# bind put on the cloth chains (PART "skirt" / "robe" / "cloak") hangs free; the rest (shoulders, chest, sleeves) +# is pinned and follows the skeleton exactly. +# 2. Every UO action is simulated on its own: the item first settles for PREROLL frames in the action's first pose; +# looping actions (walk, run, stand) run LOOP_CYCLES times and the last cycle is kept, so the loop has no jump. +# In the mounted actions the horse (collection Horse_Proxy, one shape per frame) is a collider too. +# 3. The result is saved next to the .blend (OUT_DIR/.npz). render_uo_layer.py uses it automatically; after +# the bake, playing an action in the viewport shows it too (run the script again with BAKE = False to get that +# preview back after reopening the file). To go back to the plain bound item, run it with REMOVE = True. +# Bake again after changing the item, its fit or its binding. All actions take about 30-60 minutes; the progress +# is printed in the system console (Window > Toggle System Console), one line per action for the simulation and +# again for the check against the body (FIX_GAP). Blender's window stays alive meanwhile (uo_job.py): progress in the status +# bar at the bottom, ESC cancels (the item being baked is then not saved). +import bpy +import os +import numpy as np +import bmesh +from mathutils import Vector, Matrix, Quaternion +from mathutils.bvhtree import BVHTree + +MATERIAL = "wool" # silk, cotton, wool, leather (how light / flowing -> heavy / stiff the cloth is) +SIM_VERTS = 4000 # the simulated copy has about this many vertices (more = finer folds, slower) +ACTIONS = [] # e.g. ["00_walk_unarmed", "04_stand"]; empty = all actions on foot +LOOP_ACTIONS = [0, 1, 2, 3, 4, 7, 8, 23, 24, 25] # UO actions the game loops (walk, run, stand, combat idle) +MOUNTED = True # mounted actions too: the horse of every frame (collection Horse_Proxy) pushes the cloth +LOOP_CYCLES = 3 # looping actions: cycles simulated, the last one is kept +PREROLL = 40 # frames the cloth settles in the first pose of an action (at 24 fps) +QUALITY = 8 # cloth steps per frame (more = fewer tunnelling problems in fast attacks, slower) +GOAL = 0.5 # 0..1: how strongly the hanging part is pulled towards the bound shape (the cloth chains are + # fitted to the original UO robe / skirt / cloak frames): 0 = pure cloth, 1 = no cloth at all +SELF_COLLISION = True # layers of the item (a coat over a tunic) collide with each other, so the inner one never + # shows through the outer one (slower) +CHAIN_SWING = 0.5 # 0..1: how much of the cloth chains' swing (fitted to the UO sprites) the cloth is pulled + # towards; lower = calmer cloth in fast actions (war walk, run) +FRICTION = 1.0 # how much the cloth sticks to the body (lower: it slides off a leg instead of being dragged) +TIE = 0.03 # m: separate pieces of the item (layers, a skirt under a belt) closer than this are tied + # together, so no piece falls off +DISTANCE = 0.012 # m, the cloth keeps this far from the body +FIX_GAP = 0.004 # m: afterwards every frame is checked against the real posed body; parts of the item inside it + # or closer than this are pushed out, smoothly (skin never shows through). 0 = off +OUT_DIR = "//uo_cloth/" +BAKE = True # False: only (re)enable the viewport preview of an existing bake +REMOVE = False # True: forget the bake of the selected items (back to the plain bound item) +STEP = 3 # scene frames between two UO frames (as in render_uo_layer.py) + +MATERIALS = { # mass, tension/compression/shear stiffness, bending, damping (Blender's cloth presets) + "silk": (0.15, 5, 0.05, 0), + "cotton": (0.3, 15, 0.5, 5), + "wool": (0.5, 25, 3, 15), + "leather": (0.4, 80, 150, 25), +} +CHAIN = ("skirt_", "cloak_") # cloth chain bones of the v13 rig + +sc = bpy.context.scene +rig = bpy.data.objects["UO_Rig"] +body = bpy.data.objects["UO_Body"] + + +def log(msg): + print(msg, flush=True) + + +def cache_path(ob): + return bpy.path.abspath(OUT_DIR + bpy.path.clean_name(ob.name) + ".npz") + + +def weights(ob, n): + names = [g.name for g in ob.vertex_groups] + W = np.zeros((n, len(names))) + for v in ob.data.vertices: + for g in v.groups: + if g.group < len(names): + W[v.index, g.group] = g.weight + return W, names + + +def signature(ob): + """vertex count + coordinate sum of the item's rest shape: a bake of a changed item is not used""" + base = ob.data.shape_keys.key_blocks[0].data if ob.data.shape_keys else ob.data.vertices + co = np.empty(len(ob.data.vertices) * 3, np.float32); base.foreach_get("co", co) + return np.array([len(ob.data.vertices), float(np.abs(co.astype(np.float64)).sum())]) + + +def local_co(me): + co = np.empty(len(me.vertices) * 3, np.float32); me.vertices.foreach_get("co", co) + return co.reshape(-1, 3).astype(np.float64) + + +def make_proxy(item): + """simplified, welded copy of the item (same parent / transform / vertex groups), in rest shape""" + sim = item.copy(); sim.data = item.data.copy(); sim.name = item.name + "_uo_sim" + if "uo_cloth" in sim: + del sim["uo_cloth"] + for c in list(sim.users_collection): + c.objects.unlink(sim) + sc.collection.objects.link(sim) + sim.hide_render = True + if sim.data.shape_keys: + sim.shape_key_clear() + for m in list(sim.modifiers): + sim.modifiers.remove(m) + bm = bmesh.new(); bm.from_mesh(sim.data) + bmesh.ops.remove_doubles(bm, verts=bm.verts[:], dist=1e-5) # UV-seam splits would tear the cloth apart + bm.to_mesh(sim.data); bm.free() + n = len(sim.data.vertices) + if n > SIM_VERTS * 1.2: + dec = sim.modifiers.new("dec", "DECIMATE"); dec.ratio = SIM_VERTS / n + dg = bpy.context.evaluated_depsgraph_get() + me = bpy.data.meshes.new_from_object(sim.evaluated_get(dg), preserve_all_data_layers=True, depsgraph=dg) + sim.modifiers.remove(dec) + old = sim.data; sim.data = me; bpy.data.meshes.remove(old) + tie_pieces(sim.data) + return sim + + +def tie_pieces(me): + """loose edges (cloth springs) between vertices of different pieces closer than TIE""" + n = len(me.vertices) + E = np.array([e.vertices[:] for e in me.edges]).reshape(-1, 2) + lab = np.arange(n) + while True: # connected pieces + a = np.minimum(lab[E[:, 0]], lab[E[:, 1]]); nl = lab.copy() + np.minimum.at(nl, E[:, 0], a); np.minimum.at(nl, E[:, 1], a); nl = nl[nl] + if (nl == lab).all(): + break + lab = nl + if len(np.unique(lab)) < 2: + return + from mathutils.kdtree import KDTree + co = local_co(me); kd = KDTree(n) + for i, p in enumerate(co): + kd.insert(p, i) + kd.balance() + new = set() + for i, p in enumerate(co): + best = None + for q, j, d in kd.find_range(p, TIE): + if lab[j] != lab[i] and (best is None or d < best[1]): + best = (j, d) + if best: + new.add((min(i, best[0]), max(i, best[0]))) + if new: + k = len(me.edges); me.edges.add(len(new)) + for e, (i, j) in zip(list(me.edges)[k:], sorted(new)): + e.vertices = (i, j) + me.update() + + +def pin_weights(sim): + """1 = follows the skeleton, 0 = free cloth: free where the bind used the cloth chains; without chains (PART + "all") everything below the hips hangs free, sleeves stay pinned""" + n = len(sim.data.vertices) + W, names = weights(sim, n) + chain = [j for j, nm in enumerate(names) if nm.startswith(CHAIN)] + if chain: + free = W[:, chain].sum(1) + else: + Mw = np.array(sim.matrix_world); z = local_co(sim.data) @ Mw[2, :3] + Mw[2, 3] + hip = (rig.matrix_world @ rig.data.bones["pelvis"].head_local).z + t = np.clip((hip - 0.05 - z) / 0.25, 0, 1); free = t * t * (3 - 2 * t) + arm = [j for j, nm in enumerate(names) if nm.split(".")[0] in ("upper_arm", "forearm", "hand", + "upper_arm_twist", "forearm_twist") or nm.startswith("finger")] + free *= np.clip(1 - 2 * W[:, arm].sum(1), 0, 1) + pin = GOAL + (1 - GOAL) * np.clip(1 - 1.3 * free, 0, 1) + g = sim.vertex_groups.get("uo_pin") or sim.vertex_groups.new(name="uo_pin") + for i in range(n): + g.add([i], float(pin[i]), "REPLACE") + return pin + + +def add_cloth(sim, frames): + for m in [m for m in sim.modifiers if m.type == "CLOTH"]: + sim.modifiers.remove(m) + cm = sim.modifiers.new("UO_Cloth", "CLOTH"); s = cm.settings + mass, stiff, bend, damp = MATERIALS[MATERIAL] + s.quality = QUALITY; s.mass = mass + s.tension_stiffness = s.compression_stiffness = s.shear_stiffness = stiff + s.bending_stiffness = bend + s.tension_damping = s.compression_damping = s.shear_damping = damp + s.air_damping = 1.0 + s.vertex_group_mass = "uo_pin"; s.pin_stiffness = 1.0 + c = cm.collision_settings + c.use_collision = True; c.distance_min = DISTANCE; c.collision_quality = 4 + c.use_self_collision = SELF_COLLISION; c.self_distance_min = 0.006; c.self_friction = 5.0 + cm.point_cache.frame_start = 1; cm.point_cache.frame_end = frames + return cm + + +def colliders(): + """a simplified copy of the body (and a floor for the falls) pushes the cloth; returns the objects to delete""" + made = [] + col = body.copy(); col.data = body.data.copy(); col.name = "UO_Body_uo_collider" + for c in list(col.users_collection): + c.objects.unlink(col) + sc.collection.objects.link(col); col.hide_render = True + if col.data.shape_keys: + col.shape_key_clear() + for m in list(col.modifiers): + col.modifiers.remove(m) + dec = col.modifiers.new("dec", "DECIMATE"); dec.ratio = min(1.0, 5000 / len(col.data.vertices)) + dg = bpy.context.evaluated_depsgraph_get() + me = bpy.data.meshes.new_from_object(col.evaluated_get(dg), preserve_all_data_layers=True, depsgraph=dg) + col.modifiers.remove(dec); old = col.data; col.data = me; bpy.data.meshes.remove(old) + arm = col.modifiers.new("Armature", "ARMATURE"); arm.object = rig + col.modifiers.new("UO_Collision", "COLLISION") + col.collision.thickness_outer = DISTANCE; col.collision.cloth_friction = FRICTION + made.append(("obj", col, None)) + me = bpy.data.meshes.new("UO_Floor") + me.from_pydata([(-3, -3, 0), (3, -3, 0), (3, 3, 0), (-3, 3, 0)], [], [(0, 1, 2, 3)]) + fl = bpy.data.objects.new("UO_Floor", me); sc.collection.objects.link(fl); fl.hide_render = True + fl.modifiers.new("UO_Collision", "COLLISION"); fl.collision.thickness_outer = DISTANCE + made.append(("obj", fl, None)) + return made + + +def horse_shapes(a, nf): + """the horse proxy of every UO frame of a mounted action, as ONE mesh topology (frame 0's) moved onto each frame's + surface, so it can be a moving collider; None if the file has no horse for this action""" + hs = [bpy.data.objects.get("Horse_a%d_f%d" % (a, i)) for i in range(nf)] + if not hs or any(h is None for h in hs): + return None + def world(h): + co = local_co(h.data); M = np.array(h.matrix_world) + return co @ M[:3, :3].T + M[:3, 3] + base = world(hs[0]); out = [base] + for h in hs[1:]: + h.data.calc_loop_triangles() + bvh = BVHTree.FromPolygons([Vector(p) for p in world(h)], [t.vertices[:] for t in h.data.loop_triangles]) + out.append(np.array([bvh.find_nearest(Vector(p))[0][:] for p in base])) + return hs[0], out + + +def horse_collider(a, nf): + hs = horse_shapes(a, nf) + if hs is None: + return None, None + src, shapes = hs + me = src.data.copy(); me.name = "UO_Horse_uo_collider" + col = bpy.data.objects.new("UO_Horse_uo_collider", me); sc.collection.objects.link(col); col.hide_render = True + me.vertices.foreach_set("co", shapes[0].astype(np.float32).ravel()); me.update() + col.modifiers.new("UO_Collision", "COLLISION"); col.collision.thickness_outer = DISTANCE + col.collision.cloth_friction = FRICTION + return col, shapes + + +def poses(act, times): + """pose (matrix_basis of every bone) of the action at the given scene frames""" + rig.animation_data.action = act + out = {} + for t in sorted(set(times)): + sc.frame_set(t) + out[t] = [pb.matrix_basis.copy() for pb in rig.pose.bones] + return out + + +def simulate(sim, act): + """generator (one step per cloth frame, see uo_job.py); its return value is {UO frame: proxy vertex positions (object space)}""" + a = int(act["uo_action"]); nf = int(act["uo_frames"]) + f0, f1 = int(act.frame_range[0]), int(act.frame_range[1]) + L = f1 - f0 # cycle length (the last key = the first) + if a in LOOP_ACTIONS and L > 0: + t_of = lambda k: f0 + (k % L) + run = LOOP_CYCLES * L; keep0 = PREROLL + (LOOP_CYCLES - 1) * L + else: + t_of = lambda k: min(f0 + k, f1) + run = (nf - 1) * STEP + 1 if L > 0 else 1; keep0 = PREROLL + total = PREROLL + run + times = [f0] * PREROLL + [t_of(k) for k in range(run)] + P = poses(act, times) + rig.animation_data.action = None + horse, shapes = horse_collider(a, nf) if 23 <= a <= 29 else (None, None) + try: + add_cloth(sim, total) + want = {keep0 + 1 + i * STEP: i for i in range(nf)} + out = {} + chain = [pb.name.startswith(CHAIN) for pb in rig.pose.bones] + for s in range(1, total + 1): + for pb, m, ch in zip(rig.pose.bones, P[times[s - 1]], chain): + if ch and CHAIN_SWING < 1: # calmer chains: part of the way to rest + loc, q, sca = m.decompose() + m = Matrix.LocRotScale(loc, q.slerp(Quaternion(), 1 - CHAIN_SWING), sca) + pb.matrix_basis = m + if horse is not None: # the horse of this moment (blend of 2 frames) + u = (times[s - 1] - f0) / STEP; j0 = int(np.floor(u)); w = u - j0 + j1 = (j0 + 1) % nf if a in LOOP_ACTIONS else min(j0 + 1, nf - 1); j0 = min(j0, nf - 1) + horse.data.vertices.foreach_set("co", ((1 - w) * shapes[j0] + w * shapes[j1]).astype(np.float32).ravel()) + horse.data.update() + sc.frame_set(s) + if s in want: + dg = bpy.context.evaluated_depsgraph_get() + ev = sim.evaluated_get(dg); me = ev.to_mesh() + out[want[s]] = local_co(me).astype(np.float32); ev.to_mesh_clear() + yield "%s %s: cloth step %d / %d" % (sim.name.replace("_uo_sim", ""), act.name, s, total) + finally: + if horse is not None: + me = horse.data; bpy.data.objects.remove(horse); bpy.data.meshes.remove(me) + return out + + +def pieces(co, tris): + """connected piece of every vertex (vertices at the same place count as connected)""" + _, node = welded(co) + E = node[np.r_[tris[:, [0, 1]], tris[:, [1, 2]], tris[:, [2, 0]]]]; lab = np.arange(node.max() + 1) + while True: + a = np.minimum(lab[E[:, 0]], lab[E[:, 1]]); nl = lab.copy() + np.minimum.at(nl, E[:, 0], a); np.minimum.at(nl, E[:, 1], a); nl = nl[nl] + if (nl == lab).all(): + return lab[node] + lab = nl + + +def bind_to_proxy(item_co, item_tris, sim_co, tris): + """every item vertex rides on the nearest proxy triangle OF ITS OWN PIECE (a tunic under a coat follows the + tunic): barycentric point + offset along the normal and in the triangle plane""" + ip = pieces(item_co, item_tris); sp = pieces(sim_co, tris)[tris[:, 0]] + whole = BVHTree.FromPolygons([Vector(p) for p in sim_co], tris.tolist()) + votes = {} # item piece -> proxy piece (majority) + for i in range(0, len(item_co), 7): + f = whole.find_nearest(Vector(item_co[i]))[2] + votes.setdefault(ip[i], []).append(sp[f]) + own = {k: np.bincount(v).argmax() for k, v in votes.items()} + trees = {} + for q in np.unique(sp): + sel = np.nonzero(sp == q)[0] + trees[q] = (BVHTree.FromPolygons([Vector(p) for p in sim_co], tris[sel].tolist()), sel) + fi = np.zeros(len(item_co), np.int32); bc = np.zeros((len(item_co), 3)); off = np.zeros((len(item_co), 3)) + fr = frames_of(sim_co, tris) + for i, p in enumerate(item_co): + tree, sel = trees[own.get(ip[i], sp[0])] + loc, nrm, f, d = tree.find_nearest(Vector(p)); f = sel[f] + a, b, c = sim_co[tris[f]] + v0, v1, v2 = b - a, c - a, np.array(loc) - a + d00, d01, d11, d20, d21 = v0 @ v0, v0 @ v1, v1 @ v1, v2 @ v0, v2 @ v1 + den = max(d00 * d11 - d01 * d01, 1e-18) + v = (d11 * d20 - d01 * d21) / den; w = (d00 * d21 - d01 * d20) / den + fi[i] = f; bc[i] = (1 - v - w, v, w) + off[i] = fr[f] @ (p - np.array(loc)) + return fi, bc.astype(np.float32), off.astype(np.float32) + + +def frames_of(co, tris, vn=None): + """per triangle orthonormal frame (rows: edge dir, in-plane perpendicular, normal)""" + a, b, c = co[tris[:, 0]], co[tris[:, 1]], co[tris[:, 2]] + e1 = b - a; e1 /= np.maximum(np.linalg.norm(e1, axis=1, keepdims=True), 1e-12) + n = np.cross(b - a, c - a); n /= np.maximum(np.linalg.norm(n, axis=1, keepdims=True), 1e-12) + e2 = np.cross(n, e1) + return np.stack([e1, e2, n], 1) + + +def apply_binding(sim_co, tris, fi, bc, off): + fr = frames_of(sim_co, tris)[fi] + base = (sim_co[tris[fi]] * bc[..., None]).sum(1) + return base + np.einsum("nk,nkj->nj", off, fr) + + +def welded(co): + """vertices at the same place (UV-seam splits) -> one node, so fixes never tear the item open""" + key = np.round(co / 1e-5).astype(np.int64) + _, first, node = np.unique(key, axis=0, return_index=True, return_inverse=True) + return first, node.ravel() + + +def push_out(X, bvh, E, deg): + """displacement that keeps the points X (body space) FIX_GAP outside the body; spread over the item (smooth)""" + D = np.zeros_like(X); look = np.arange(len(X)); reach = 0.1 + for it in range(12): + P = X + D; need = np.zeros(len(X)); N = np.zeros_like(X); near = [] + for i in look: + p = Vector(P[i]); loc, nrm, fi, dist = bvh.find_nearest(p, reach) + if loc is not None: + near.append(i); s = (p - loc).dot(nrm) + if s < FIX_GAP: + need[i] = FIX_GAP - s; N[i] = nrm + if it == 0: + look = np.array(near, int); reach = FIX_GAP + 0.05 + if not (need > 1e-4).any(): + break + D += need[:, None] * N + if it < 11: + for _ in range(2): + acc = np.zeros_like(D) + np.add.at(acc, E[:, 0], D[E[:, 1]]); np.add.at(acc, E[:, 1], D[E[:, 0]]) + D = np.where(deg[:, None] > 0, 0.5 * D + 0.5 * acc / np.maximum(deg, 1)[:, None], D) + look = np.union1d(look, np.nonzero(np.abs(D).max(1) > 1e-5)[0]) + return D + + +def fix_pass(item, data, done): + """generator (one step per frame, see uo_job.py): push every baked frame of the item out of the real posed body (see FIX_GAP); stored as sparse node offsets""" + base = item.data.shape_keys.key_blocks[0].data if item.data.shape_keys else item.data.vertices + ico = np.empty(len(item.data.vertices) * 3, np.float32); base.foreach_get("co", ico) + first, node = welded(ico.reshape(-1, 3).astype(np.float64)) + E = np.array([e.vertices[:] for e in item.data.edges]).reshape(-1, 2) + E = np.unique(np.sort(node[E], 1), axis=0); E = E[E[:, 0] != E[:, 1]] + deg = np.bincount(E.ravel(), minlength=len(first)).astype(float) + data["fix_node"] = node.astype(np.int32) + moved = 0 + for act in [a for a in bpy.data.actions if "uo_action" in a and int(a["uo_action"]) in done]: + a = int(act["uo_action"]); rig.animation_data.action = act + for i in range(int(data["frames_%d" % a])): + sc.frame_set(1 + i * STEP) + dg = bpy.context.evaluated_depsgraph_get() + ev = body.evaluated_get(dg); me = ev.to_mesh(); bco = local_co(me) + me.calc_loop_triangles(); btri = [t.vertices[:] for t in me.loop_triangles]; ev.to_mesh_clear() + hz = bpy.data.objects.get("Horse_a%d_f%d" % (a, i)) if 23 <= a <= 29 else None + if hz is not None: # mounted: the horse of this frame too + Hm = np.array(body.matrix_world.inverted() @ hz.matrix_world); hco = local_co(hz.data) + hz.data.calc_loop_triangles() + btri = btri + [tuple(k + len(bco) for k in t.vertices) for t in hz.data.loop_triangles] + bco = np.r_[bco, hco @ Hm[:3, :3].T + Hm[:3, 3]] + bvh = BVHTree.FromPolygons([Vector(p) for p in bco], btri) + M = np.array(body.matrix_world.inverted() @ item.matrix_world) + co = apply_binding(data["a%d_f%d" % (a, i)].astype(np.float64), data["tris"], data["fi"], data["bc"], + data["off"])[first] + D = push_out(co @ M[:3, :3].T + M[:3, 3], bvh, E, deg) @ np.linalg.inv(M[:3, :3]).T + idx = np.nonzero(np.abs(D).max(1) > 2e-4)[0] + data["d%d_f%d_i" % (a, i)] = idx.astype(np.int32) + data["d%d_f%d_v" % (a, i)] = D[idx].astype(np.float16) + moved = max(moved, len(idx)) + yield "%s %s: checking frame %d against the body" % (item.name, act.name, i + 1) + log("uo_cloth_bake: %s %s: checked against the body" % (item.name, act.name)) + log("uo_cloth_bake: %s pushed out of the body (up to %d points per frame)" % (item.name, moved)) + + +def fix_offsets(c, a, i, n): + """per-vertex fix of frame i of action a (zeros if none)""" + k = "d%d_f%d_i" % (a, i) + if "fix_node" not in c or k not in c: + return 0.0 + Dn = np.zeros((int(c["fix_node"].max()) + 1, 3)); Dn[c[k]] = c["d%d_f%d_v" % (a, i)] + return Dn[c["fix_node"]] + + +# ---------------------------------------------------------------- preview / render support (shared with the renderer) +_cache = {} + + +def load(ob): + p = ob.get("uo_cloth") + if not p: + return None + p = bpy.path.abspath(p) + if p not in _cache: + if not os.path.exists(p): + return None + d = np.load(p); _cache[p] = {k: d[k] for k in d.files} + return _cache[p] + + +def show(ob, a, t): + """put the item in the baked shape of UO action a at UO frame t (float: blends two frames); False = no bake""" + c = load(ob) + if c is not None and not np.allclose(c["item_sig"], signature(ob), rtol=1e-5): + c = None # the item changed since the bake + arm = [m for m in ob.modifiers if m.type == "ARMATURE"] + key = ob.data.shape_keys.key_blocks.get("uo_cloth") if ob.data.shape_keys else None + n = int(c["frames_%d" % a]) if c is not None and ("frames_%d" % a) in c else 0 + if n == 0: + for m in arm: + m.show_viewport = m.show_render = True + if key: + key.value = 0.0 + return False + i0 = int(np.floor(t)) % n; i1 = (i0 + 1) % n; w = t - np.floor(t) + if a not in LOOP_ACTIONS and i0 == n - 1: + i1, w = i0, 0.0 + sim_co = (1 - w) * c["a%d_f%d" % (a, i0)].astype(np.float64) + w * c["a%d_f%d" % (a, i1)].astype(np.float64) + co = apply_binding(sim_co, c["tris"], c["fi"], c["bc"], c["off"]) + co = co + (1 - w) * fix_offsets(c, a, i0, len(co)) + w * fix_offsets(c, a, i1, len(co)) + if key is None: + if ob.data.shape_keys is None: + ob.shape_key_add(name="Basis", from_mix=False) + key = ob.shape_key_add(name="uo_cloth", from_mix=False) + key.data.foreach_set("co", co.astype(np.float32).ravel()); key.value = 1.0 + for m in arm: + m.show_viewport = m.show_render = False + ob.data.update() + return True + + +def rest(ob): + for m in ob.modifiers: + if m.type == "ARMATURE": + m.show_viewport = m.show_render = True + if ob.data.shape_keys and "uo_cloth" in ob.data.shape_keys.key_blocks: + ob.data.shape_keys.key_blocks["uo_cloth"].value = 0.0 + + +def preview(scene, *_): + act = rig.animation_data.action if rig.animation_data else None + if act is None or "uo_action" not in act or rig.data.pose_position != "POSE": + for ob in [o for o in scene.objects if "uo_cloth" in o]: + rest(ob) + return + t = (scene.frame_current - 1) / STEP + for ob in [o for o in scene.objects if "uo_cloth" in o]: + show(ob, int(act["uo_action"]), t) + + +def enable_preview(): + for h in [h for h in bpy.app.handlers.frame_change_post if getattr(h, "__name__", "") == "uo_cloth_preview"]: + bpy.app.handlers.frame_change_post.remove(h) + def uo_cloth_preview(scene, *a): + preview(scene) + bpy.app.handlers.frame_change_post.append(uo_cloth_preview) + + +# ---------------------------------------------------------------- main +def bake(item): + """generator (see uo_job.py): bakes one item, yields after every cloth step""" + if not any(m.type == "ARMATURE" for m in item.modifiers): + raise RuntimeError("%s is not bound - run uo_bind_item.py first" % item.name) + if not bpy.data.filepath: + raise RuntimeError("save the .blend first (the bake is written next to it)") + rest(item) + log("uo_cloth_bake: %s - preparing (the first action line comes after a few minutes)" % item.name) + state = dict(pose=rig.data.pose_position, act=rig.animation_data.action, frame=sc.frame_current, + d=rig.get("uo_direction", 0)) + rig.data.pose_position = "REST"; bpy.context.view_layer.update() + sim = make_proxy(item) + pin = pin_weights(sim) + arm = sim.modifiers.new("Armature", "ARMATURE"); arm.object = rig + sim_rest = local_co(sim.data) + sim.data.calc_loop_triangles() + tris = np.array([t.vertices[:] for t in sim.data.loop_triangles], np.int32) + base = item.data.shape_keys.key_blocks[0].data if item.data.shape_keys else item.data.vertices + ico = np.empty(len(item.data.vertices) * 3, np.float32); base.foreach_get("co", ico) + item.data.calc_loop_triangles() + itris = np.array([t.vertices[:] for t in item.data.loop_triangles], np.int32) + fi, bc, off = bind_to_proxy(ico.reshape(-1, 3).astype(np.float64), itris, sim_rest, tris) + made = colliders() + hidden = [o for o in sc.objects if o.type == "MESH" and o is not sim and not o.hide_viewport + and not o.name.startswith(("UO_Floor", "UO_Body_uo_collider"))] + for o in hidden: + o.hide_viewport = True # not evaluated while simulating (faster) + rig.data.pose_position = "POSE"; rig["uo_direction"] = 0 + data = dict(tris=tris, fi=fi, bc=bc, off=off, sim_rest=sim_rest.astype(np.float32), item_sig=signature(item)) + acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) + done = [] + try: + try: + for act in acts: + a = int(act["uo_action"]) + if (ACTIONS and act.name not in ACTIONS) or (23 <= a <= 29 and not MOUNTED): + continue + res = yield from simulate(sim, act) + for i, co in res.items(): + data["a%d_f%d" % (a, i)] = co + data["frames_%d" % a] = np.array(len(res)) + done.append(a) + log("uo_cloth_bake: %s %s: %d frames" % (item.name, act.name, len(res))) + finally: + for o in hidden: + o.hide_viewport = False + for kind, ob, name in made + [("obj", sim, None)]: + if kind == "mod": + ob.modifiers.remove(ob.modifiers[name]) + else: + me = ob.data; bpy.data.objects.remove(ob); bpy.data.meshes.remove(me) + if FIX_GAP > 0 and done: + yield from fix_pass(item, data, done) + finally: + rig.data.pose_position = state["pose"]; rig.animation_data.action = state["act"] + rig["uo_direction"] = state["d"]; sc.frame_set(state["frame"]) + old = load(item) # keep other actions baked earlier + if old is not None and ACTIONS and old["sim_rest"].shape == data["sim_rest"].shape \ + and np.allclose(old["sim_rest"], data["sim_rest"], atol=1e-4) and len(old["fi"]) == len(fi): + for k, v in old.items(): + if k.startswith("frames_"): + a = int(k[7:]) + elif k.startswith(("a", "d")) and "_f" in k: + a = int(k[1:k.index("_f")]) + else: + continue + if a not in done: + data[k] = v + p = cache_path(item); os.makedirs(os.path.dirname(p), exist_ok=True) + np.savez_compressed(p, **data) + _cache.pop(p, None) + item["uo_cloth"] = bpy.path.relpath(p) + log("uo_cloth_bake: %s -> %s (%d vertices simulated, %d pinned)" % (item.name, p, len(sim_rest), (pin > 0.99).sum())) + + +if __name__ == "__main__" and REMOVE: + for ob in [o for o in bpy.context.selected_objects if "uo_cloth" in o]: + rest(ob); del ob["uo_cloth"] + if ob.data.shape_keys and "uo_cloth" in ob.data.shape_keys.key_blocks: + ob.shape_key_remove(ob.data.shape_keys.key_blocks["uo_cloth"]) + log("uo_cloth_bake: %s back to the bound item" % ob.name) +elif __name__ == "__main__": + items = [o for o in bpy.context.selected_objects if o.type == "MESH" and o != body and "_uo_sim" not in o.name] if BAKE else [] + + def job(): + for ob in items: + yield from bake(ob) + + def finish(): + enable_preview() + log("uo_cloth_bake: viewport preview on (play an action of UO_Rig in Pose Position)") + + def abort(why): + log("uo_cloth_bake: %s - the item being baked was not saved (finished items were)" % why) + + # one cloth step per modal step: Blender's window stays alive for the 30-60 minutes (progress in the status bar, ESC cancels) + if "uo_job.py" in bpy.data.texts: + bpy.data.texts["uo_job.py"].as_module().run(job(), "uo_cloth_bake", finish, abort) + else: + for _ in job(): + pass + finish() diff --git a/third_party/UO_Model3D_v13/pipeline/uo_fit_item.py b/third_party/UO_Model3D_v13/pipeline/uo_fit_item.py new file mode 100644 index 0000000..63d483c --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_fit_item.py @@ -0,0 +1,339 @@ +# Fit the SELECTED item meshes onto the UO body (rest pose) before uo_bind_item.py. Place and size the item yourself; +# this script only fixes how it sits on the body: +# 1. Sleeves (MATCH_ARMS): an item made for a body with the arms lower / higher / more forward (or bent) has the UO +# arms sticking out of its sleeves. The script finds the arm pose that fits into the sleeves and turns the sleeves +# (and the item around the shoulders, like a skin) from that pose to the UO body's arms. Items without sleeves +# (vest, cuirass) and sleeves that already sit on the arms are left alone. +# 2. Push: every part closer to the skin than MIN_GAP (or inside the body) is pushed out along the skin normal. A push +# moves the whole area around it the same way and fades out smoothly over max(RADIUS, SPREAD x the push), so a +# sleeve sitting 5 cm too deep is widened / moved as a whole instead of getting a bump; details (folds, rivets) +# move with their area and are kept. Layers (a coat over a tunic) move together and stay in order. +# 3. MAX_GAP > 0 also pulls parts that stand off more than that back towards the skin, only where the whole area +# around (RADIUS) stands off, so the thickness of the item is kept. +# Run it with the item selected (Alt+P); then run uo_bind_item.py. Running it again changes nothing once it fits. +# Existing shape keys get the same change. Faces much bigger than the gap can still cut through the skin between +# their corners: subdivide such an item first (Edit Mode, A, right click > Subdivide, Number of Cuts 2). +import bpy +import numpy as np +from mathutils import Vector +from mathutils.bvhtree import BVHTree +from mathutils.kdtree import KDTree + +KIND = "" # kind of item (as in uo_import_item.py): shirt, pants, boots, gloves, plate, legs, arms, helm, ... ("" = not given) +MIN_GAP = -1.0 # m, no part of the item closer to the skin than this (0 = only out of the body); < 0 = from KIND (GAP_BY_KIND, else 0.015) +# MIN_GAP by KIND, measured on thin body-hugging replicas against the original sprites (test_items.py --fit, IoU at 0.015 / 0.03 / 0.045): +# close-fitting cloth and leather is best at 0.015 (shirt .746/.727/.681, pants .801/.793/.747, boots .771/.755/.693, gloves .579/.576/.526); thick armour, +# helmets and sleeves at 0.03 (plate .702/.725/.706, helm .770/.783/.658, arms .615/.619/.598, legs .667/.673/.651). The sprites agree: shirts, trousers, boots +# stand 1 px (2.8 cm) off the silhouette of the body, plate / helmets / robes 2-4 px (docs/qa/layer_analysis.md). +GAP_BY_KIND = {"shirt": 0.015, "pants": 0.015, "boots": 0.015, "gloves": 0.015, "plate": 0.03, "legs": 0.03, "arms": 0.03, "helm": 0.03} +MAX_GAP = 0.0 # m, > 0: pull parts standing off more than this towards the skin (0 = off) +RADIUS = 0.04 # m, smallest area a push spreads over +SPREAD = 3.0 # a push of d spreads over at least SPREAD * d (bigger = broader, gentler swelling) +ITERATIONS = 12 # push rounds at most (it stops as soon as nothing is too close) +MATCH_ARMS = True # first turn the sleeves onto the arms: finds how much lower / higher / more forward the arms of + # the body the item was made for were, and turns the sleeves (and the item around the shoulders) + # by that much, so the arms sit inside the sleeves before anything is pushed +MAX_TURN = 35 # deg, the most the sleeves may be turned +MIN_GAIN = 3.0 # turn only if it fits the arms clearly better (so running the script again changes nothing) +SLIM = 1.0 # < 1 makes the item narrower below the chest (e.g. 0.85 = 15 % narrower at the hips and below), + # towards the body's middle; sleeves and the chest are left as they are. Run once per change: + # every run slims again + +if MIN_GAP < 0: + MIN_GAP = GAP_BY_KIND.get(KIND, 0.015) + +body = bpy.data.objects["UO_Body"] +rig = bpy.data.objects["UO_Rig"] + + +def body_bvh(): + me = body.data + kb = me.shape_keys.key_blocks["Basis"] if me.shape_keys else None + co = np.empty(len(me.vertices) * 3, np.float32) + (kb.data if kb else me.vertices).foreach_get("co", co) + me.calc_loop_triangles() + tri = [t.vertices[:] for t in me.loop_triangles] + return BVHTree.FromPolygons([Vector(p) for p in co.reshape(-1, 3)], tri) + + +def skin(bvh, P, reach=None): + """nearest skin normal and signed distance (< 0 inside the body) of every point; points farther than `reach` + get S = reach (not looked at closer - quick)""" + N = np.zeros_like(P); S = np.full(len(P), np.inf if reach is None else reach) + for i, p in enumerate(P): + v = Vector(p) + loc, nrm, fi, d = bvh.find_nearest(v) if reach is None else bvh.find_nearest(v, reach) + if loc is not None: + N[i] = nrm; S[i] = (v - loc).dot(nrm) + return N, S + + +def push_field(Q, V, strict=False): + """push vectors V (non-zero at the parts that are too close) -> displacement of every point: each push moves the + points around it by its own vector, fading out over max(RADIUS, SPREAD * |push|); where pushes overlap the biggest + sets how far and the (weighted) mean of their directions sets where to, so the area moves as one""" + mag = np.linalg.norm(V, axis=1) + src = np.nonzero(mag > 1e-5)[0] + src = src[np.argsort(-mag[src])] + F = np.zeros(len(Q)); Dsum = np.zeros_like(Q); Wsum = np.zeros(len(Q)) + for i in src: + if F[i] >= mag[i] and Dsum[i] @ V[i] > 0.95 * np.linalg.norm(Dsum[i]) * mag[i]: + continue # already covered by a bigger push the same way + R = max(RADIUS, SPREAD * mag[i]) + near = np.nonzero(np.abs(Q - Q[i]).max(1) < R)[0] + w = np.clip(1 - np.sum((Q[near] - Q[i]) ** 2, 1) / R ** 2, 0, None) ** 2 + F[near] = np.maximum(F[near], mag[i] * w) + Dsum[near] += (w ** 2)[:, None] * V[i] + Wsum[near] += w ** 2 * mag[i] + if strict: # pushes that disagree do not cancel out + return F[:, None] * Dsum / np.maximum(np.linalg.norm(Dsum, axis=1), 1e-12)[:, None] + return F[:, None] * Dsum / np.maximum(Wsum, 1e-12)[:, None] + + +def rot(axis, ang): + a = np.asarray(axis, float) / np.linalg.norm(axis) + K = np.array([[0, -a[2], a[1]], [a[2], 0, -a[0]], [-a[1], a[0], 0]]) + return np.eye(3) + np.sin(ang) * K + (1 - np.cos(ang)) * K @ K + + +def about(R, p): + T = np.eye(4); T[:3, :3] = R; T[:3, 3] = p - R @ p + return T + + +def subtree(bone): + return {bone.name} | {c.name for c in bone.children_recursive} + + +class Arms: + """the body's arms: joints, the share of every skin vertex that moves with the upper arm / forearm, arm radii""" + def __init__(self): + me = body.data + kb = me.shape_keys.key_blocks["Basis"] if me.shape_keys else None + co = np.empty(len(me.vertices) * 3, np.float32) + (kb.data if kb else me.vertices).foreach_get("co", co) + self.V = co.reshape(-1, 3).astype(np.float64) + B = np.array(body.matrix_world.inverted() @ rig.matrix_world) # armature -> body space + Rw = np.array(body.matrix_world.inverted().to_3x3()) + self.X = Rw @ [1, 0, 0]; self.Y = Rw @ [0, 1, 0]; self.fwd = Rw @ [0, -1, 0] + gi = {g.name: g.index for g in body.vertex_groups} + W = np.zeros((len(self.V), len(body.vertex_groups))) + for v in me.vertices: + for g in v.groups: + W[v.index, g.group] = g.weight + bones = rig.data.bones; self.side = {} + for sd, sg in (("L", 1), ("R", -1)): + if "upper_arm." + sd not in bones: + continue + j = [B[:3, :3] @ bones[n + "." + sd].head_local + B[:3, 3] for n in ("upper_arm", "forearm", "hand")] + wU = W[:, [gi[n] for n in subtree(bones["upper_arm." + sd]) if n in gi]].sum(1) + wF = W[:, [gi[n] for n in subtree(bones["forearm." + sd]) if n in gi]].sum(1) + wH = W[:, [gi[n] for n in subtree(bones["hand." + sd]) if n in gi]].sum(1) + rU = np.percentile(seg_dist(self.V[(wU - wF) > 0.8], j[0], j[1]), 60) + rF = np.percentile(seg_dist(self.V[((wF - wH) > 0.8)], j[1], j[2]), 60) + kE = np.cross(j[1] - j[0], self.fwd); kE /= np.linalg.norm(kE) + self.side[sd] = dict(s=sg, j=j, wU=wU, wF=wF, r=(rU, rF), kE=kE) + + def T(self, sd, up, fw, el): + a = self.side[sd]; j = a["j"] + TU = about(rot(self.Y, -a["s"] * up) @ rot(self.X, -fw), j[0]) + return TU, TU @ about(rot(a["kE"], el), j[1]) + + +def seg_dist(P, a, b): + ab = b - a; t = np.clip((P - a) @ ab / (ab @ ab), 0, 1) + return np.linalg.norm(P - (a + t[:, None] * ab), axis=1) + + +def match_arms(Q, edges, gbvh): + """turn the item from the arm pose it was made in to the body's pose (see MATCH_ARMS); Q: item points, body space""" + arms = Arms(); found = {}; lim = np.radians(MAX_TURN) + dirs = [(np.cos(t), np.sin(t)) for t in np.linspace(0, 2 * np.pi, 8, endpoint=False)] + + def cost(sd, x, misses=False): + TU, TF = arms.T(sd, *x) + j = arms.side[sd]["j"]; rU, rF = arms.side[sd]["r"] + a = TU[:3, :3] @ j[0] + TU[:3, 3]; b = TU[:3, :3] @ j[1] + TU[:3, 3]; c = TF[:3, :3] @ j[2] + TF[:3, 3] + c_ = 0.0; miss = 0 + for p0, p1, r, ts in ((a, b, rU, (0.4, 0.55, 0.7, 0.85, 1.0)), (b, c, rF, (0.15, 0.3, 0.45))): + ax = (p1 - p0) / np.linalg.norm(p1 - p0) + u = np.cross(ax, arms.fwd); u /= np.linalg.norm(u); w = np.cross(ax, u) + for t in ts: + p = Vector(p0 + t * (p1 - p0)) + for cs, sn in dirs: + hit = gbvh.ray_cast(p, Vector(cs * u + sn * w), 0.35) + if hit[0] is None: + c_ += 1.0; miss += 1 # the arm is not inside the item here + else: + c_ += 4 * max(0.0, (r + 0.01 - hit[3]) / r) ** 2 # the item cuts into the arm + return (miss, len(dirs) * 8) if misses else c_ + 2.0 * float(np.sum(np.square(x))) + + tried = [] + for sd in arms.side: + g = np.radians(np.arange(-MAX_TURN, MAX_TURN + 0.1, 5.0)) + ge = np.radians(np.arange(-10, 60.1, 10.0)) # elbow: -10 (straighter) .. 60 deg bent + cand = [(cost(sd, (u, f, e)), (u, f, e)) for u in g for f in g if abs(f) <= np.radians(25) for e in ge] + cand += [(cost(sd, tuple(x)), tuple(x)) for x in tried] # the other sleeve's answer (same numbers = mirrored) + f, x = min(cand, key=lambda r: r[0]) # up, forward and elbow together: a sleeve made + x = list(x) # with a bent elbow is found from any start + for st in np.radians([4.0, 2.0, 1.0, 0.5]): # refine + imp = True + while imp: + imp = False + for k in range(3): + for sg in (1, -1): + y = list(x); y[k] = float(np.clip(y[k] + sg * st, -lim, lim) if k < 2 else np.clip(y[k] + sg * st, -0.2, 1.05)) + fy = cost(sd, y) + if fy < f - 1e-9: + f, x, imp = fy, y, True + tried.append(tuple(x)) + miss, rays = cost(sd, x, True) + if miss > rays // 8: # no sleeve around this arm (vest, cuirass) + continue + if f < cost(sd, (0.0, 0.0, 0.0)) - MIN_GAIN: # else the sleeve already sits on the arm + found[sd] = x + if not found: + return Q, "none" + # the item follows the posed body like the skin under it: weights from the nearest skin point, smoothed over the item + PV = arms.V.copy(); Ts = {} + for sd, x in found.items(): + a = arms.side[sd]; TU, TF = arms.T(sd, *x); Ts[sd] = (TU, TF) + for w, T in ((a["wU"] - a["wF"], TU), (a["wF"], TF)): + PV += w[:, None] * ((arms.V @ T[:3, :3].T + T[:3, 3]) - arms.V) + kd = KDTree(len(PV)) + for i, p in enumerate(PV): + kd.insert(p, i) + kd.balance() + near = np.array([kd.find(p)[1] for p in Q]) + kq = KDTree(len(Q)) # pieces that touch (cuffs, trims, collars) + for i, p in enumerate(Q): # move with what they touch + kq.insert(p, i) + kq.balance() + touch = [(i, j) for i, p in enumerate(Q) for co, j, d in kq.find_range(p, 0.004) if j > i] + if touch: + edges = np.r_[edges, np.array(touch)] + M = np.tile(np.eye(4), (len(Q), 1, 1)) + for sd in found: + a = arms.side[sd]; TU, TF = Ts[sd] + for w, T in ((a["wU"] - a["wF"], TU), (a["wF"], TF)): + wq = w[near] + for _ in range(8): # smooth over the item + acc = wq.copy(); cnt = np.ones(len(Q)) + np.add.at(acc, edges[:, 0], wq[edges[:, 1]]); np.add.at(acc, edges[:, 1], wq[edges[:, 0]]) + np.add.at(cnt, edges[:, 0], 1); np.add.at(cnt, edges[:, 1], 1) + wq = acc / cnt + M += wq[:, None, None] * (T - np.eye(4)) + Qh = np.c_[Q, np.ones(len(Q))] + Qr = np.linalg.solve(M, Qh[:, :, None])[:, :3, 0] + txt = " | ".join("%s: %+.0f up %+.0f fwd %+.0f elbow" % (sd, *np.degrees(x)) for sd, x in found.items()) + return Qr, txt + + +def slim(Q, edges, arms): + """narrower below the chest (see SLIM): each height is scaled towards the middle of the body at that height""" + V = arms.V + armw = sum(a["wU"] for a in arms.side.values()) + B = np.array(body.matrix_world.inverted() @ rig.matrix_world) + zt = (B @ np.r_[list(rig.data.bones["chest"].head_local), 1])[2] # chest: nothing changes above + zf = (B @ np.r_[list(rig.data.bones["pelvis"].head_local), 1])[2] # pelvis: full SLIM below + core = V[armw < 0.3] + kb = np.clip(((core[:, 2] - core[:, 2].min()) / 0.02).astype(int), 0, None) + nb = kb.max() + 1 + cnt = np.bincount(kb, minlength=nb).astype(float) + cx = np.bincount(kb, core[:, 0], nb); cy = np.bincount(kb, core[:, 1], nb) + ok = cnt > 0; ib = np.arange(nb) + cx = np.interp(ib, ib[ok], cx[ok] / cnt[ok]); cy = np.interp(ib, ib[ok], cy[ok] / cnt[ok]) + for _ in range(3): # smooth the middle line over height + cx = np.convolve(np.pad(cx, 2, mode="edge"), np.ones(5) / 5, "valid") + cy = np.convolve(np.pad(cy, 2, mode="edge"), np.ones(5) / 5, "valid") + k = np.clip(((Q[:, 2] - core[:, 2].min()) / 0.02).astype(int), 0, nb - 1) + c = np.c_[cx[k], cy[k]] + kd = KDTree(len(V)) + for i, p in enumerate(V): + kd.insert(p, i) + kd.balance() + aw = armw[np.array([kd.find(p)[1] for p in Q])] + for _ in range(8): # smooth over the item + acc = aw.copy(); n = np.ones(len(Q)) + np.add.at(acc, edges[:, 0], aw[edges[:, 1]]); np.add.at(acc, edges[:, 1], aw[edges[:, 0]]) + np.add.at(n, edges[:, 0], 1); np.add.at(n, edges[:, 1], 1) + aw = acc / n + t = np.clip((zt - Q[:, 2]) / max(zt - zf, 1e-6), 0, 1); t = t * t * (3 - 2 * t) + s = 1 - (1 - SLIM) * t * np.clip(1 - 2 * aw, 0, 1) + out = Q.copy(); out[:, :2] = c + (Q[:, :2] - c) * s[:, None] + return out + + +def fit(ob, bvh): + me = ob.data + M = np.array(body.matrix_world.inverted() @ ob.matrix_world) # item -> body space + Mi = np.linalg.inv(M) + base = me.shape_keys.key_blocks[0] if me.shape_keys else None + co = np.empty(len(me.vertices) * 3, np.float32) + (base.data if base else me.vertices).foreach_get("co", co) + local = co.reshape(-1, 3).astype(np.float64) + P0 = local @ M[:3, :3].T + M[:3, 3] + # vertices at the same place (split at UV seams / sharp edges) move as one, so the item does not tear open + key = np.round(P0 / 1e-5).astype(np.int64) + _, first, node = np.unique(key, axis=0, return_index=True, return_inverse=True) + node = node.ravel(); Q0 = P0[first] + Q = Q0.copy() + S0 = skin(bvh, Q0, MIN_GAP + 0.3)[1][node] + turn = "" + if MATCH_ARMS or SLIM < 1: + me.calc_loop_triangles() + tri = node[np.array([t.vertices[:] for t in me.loop_triangles])] + edges = np.unique(np.sort(np.r_[tri[:, [0, 1]], tri[:, [1, 2]], tri[:, [2, 0]]], 1), axis=0) + edges = edges[edges[:, 0] != edges[:, 1]] + if MATCH_ARMS: + gbvh = BVHTree.FromPolygons([Vector(p) for p in Q0], tri.tolist()) + Q, turn = match_arms(Q0, edges, gbvh) + turn = " | sleeves turned: " + turn + if SLIM < 1: + Q = slim(Q, edges, Arms()) + turn += " | slimmed to %.2f" % SLIM + rounds = 0 + Sn = skin(bvh, Q)[1] + close = np.nonzero(Sn < MIN_GAP + 0.05)[0] # only these can end up too close + for rounds in range(1, ITERATIONS + 1): # push out + N = np.zeros_like(Q); S = np.full(len(Q), np.inf) + N[close], S[close] = skin(bvh, Q[close]) + need = np.maximum(0, MIN_GAP - S) + if not (need > 2e-4).any(): + rounds -= 1 + break + Q = Q + push_field(Q, np.where(need[:, None] > 2e-4, need[:, None] * N, 0), strict=rounds > ITERATIONS // 2) + if MAX_GAP > 0: # pull in (thickness kept) + N, S = skin(bvh, Q) + pull = np.maximum(0, S - MAX_GAP); out = np.zeros(len(Q)) + kd = KDTree(len(Q)) + for i, p in enumerate(Q): + kd.insert(p, i) + kd.balance() + for j in range(len(Q)): + out[j] = min(pull[i] for co, i, d in kd.find_range(Q[j], RADIUS)) + Q = Q - out[:, None] * N + S1 = skin(bvh, Q, MIN_GAP + 0.3)[1][node] + D = (Q - Q0)[node] + delta = D @ Mi[:3, :3].T # back to item space + if me.shape_keys: + for k in me.shape_keys.key_blocks: + c = np.empty(len(me.vertices) * 3, np.float32); k.data.foreach_get("co", c) + k.data.foreach_set("co", (c.reshape(-1, 3) + delta).ravel().astype(np.float32)) + me.vertices.foreach_set("co", (local + delta).ravel().astype(np.float32)) + me.update() + mv = np.linalg.norm(D, axis=1) + print("uo_fit_item: %s | inside body %d -> %d verts | closest %.1f -> %.1f mm | moved %d verts, max %.1f mm | %d rounds" + % (ob.name, (S0 < 0).sum(), (S1 < 0).sum(), S0.min() * 1000, S1.min() * 1000, + (mv > 1e-4).sum(), mv.max() * 1000, rounds) + turn) + + +pose = rig.data.pose_position +rig.data.pose_position = "REST" +bpy.context.view_layer.update() +try: + bvh = body_bvh() + for ob in [o for o in bpy.context.selected_objects if o.type == "MESH" and o != body]: + fit(ob, bvh) +finally: + rig.data.pose_position = pose diff --git a/third_party/UO_Model3D_v13/pipeline/uo_import_item.py b/third_party/UO_Model3D_v13/pipeline/uo_import_item.py new file mode 100644 index 0000000..043d134 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_import_item.py @@ -0,0 +1,153 @@ +# Bring a model from outside (a free 3D model: .glb / .gltf / .fbx / .obj / .dae / .stl / .ply) onto the UO body, ready for uo_fit_item.py and +# uo_bind_item.py. Foreign models come in any size, any place, often with their own skeleton and weights; this script does the dull part: +# 1. imports the file and bakes every mesh as it looks now (its own armature / modifiers applied; shape keys, vertex groups, parents and +# the armature, empties, lights, cameras of the file are dropped: uo_bind_item.py makes the skin weights from the UO body), +# 2. joins the meshes into one object (JOIN) and puts it in the collection "Clothing", selected, +# 3. scales it (uniformly) and moves it so that its height lands where the ORIGINAL UO item of the same KIND stands on the body: the lowest +# and highest point of the original sprites in the rest pose (EXTENTS, measured from anim 431, 434, 449, 468, 477, 527, 528, 529, 530, +# 563; hair, beard, hat, neck: medians of the whole layer). Sideways and front-back it is centred on the body at that height. Tell it SCALE = a number to scale yourself instead. +# Then: check that the FRONT of the item looks at the camera of the front view (Numpad 1) - if it is the other way round, set TURN = 180 and +# run again - run uo_fit_item.py, and uo_bind_item.py with the PART of the table below. Work in Rest Position (UO_Rig > Pose > Rest Position). +# Run from Blender's Text Editor (Alt+P) in UO_Body_0x190.blend, or headless: UO_IMPORT_FILE=... UO_IMPORT_KIND=... (see pipeline/test_import_item.py). +# A file often holds more than the item (the model's body, eyes, helper shapes): the meshes are listed, name the ones to leave out in SKIP. +# Remember to keep the item under ~20k vertices (Decimate modifier) and to check the licence of the model you use. +import os +import bpy +import bmesh +import numpy as np +from mathutils import Matrix + +FILE = "" # path of the model to import ("" = take the SELECTED mesh objects instead, e.g. something you appended yourself) +KIND = "shirt" # shirt, plate, arms, pants, legs, boots, gloves, helm, skirt, cloak, robe, neck, hair, beard, hat ("" = do not scale or move; only clean + join) +SCALE = 0.0 # > 0: uniform scale you give (the item is then only moved), 0 = from the height of KIND +TURN = 0 # deg around the vertical axis (180 when the item came in back to front) +JOIN = True # one object out of all the meshes of the file (False: they stay separate objects, each scaled alike) +SKIP = () # names (parts of names, any case) of meshes of the file to leave out: eyes, the model's body, helper shapes, collision meshes +NAME = "" # name of the result ("" = file name) +PERCENT = 0.5 # the height is measured between the PERCENT and 100 - PERCENT percentile of the vertices (a stray spike does not count) + +# measured on the original sprites (stand, mean of the 5 directions): z of the lowest and highest point of the item in the rest pose, m +# (the ground is z = 0), and the PART of uo_bind_item.py that belongs to the KIND +EXTENTS = {"shirt": (0.999, 1.656, "chest"), "plate": (0.651, 1.643, "chest"), "arms": (0.929, 1.694, "arms"), "pants": (0.057, 1.170, "legs"), + "legs": (-0.107, 1.138, "legs"), "boots": (-0.069, 0.563, "boots"), "gloves": (0.797, 1.245, "gloves"), "helm": (1.504, 1.903, "helm"), + "skirt": (0.026, 1.258, "skirt"), "cloak": (0.095, 1.675, "cloak"), + # medians over the original animations of the layer (docs/qa/layer_analysis.md, pipeline/layer_analysis.py); robe = anim 469. + # hair / beard / hat: the TOP is reliable (hair 1.88-1.93 m for 80 % of the 37 hairstyles), the bottom depends on the style (hair 1.34-1.64): + # for a long hairstyle give SCALE yourself instead of letting the height decide + "hair": (1.52, 1.89, "hair"), "beard": (1.52, 1.72, "beard"), "hat": (1.52, 1.92, "hat"), "neck": (1.48, 1.64, "neck"), + "robe": (0.026, 1.719, "robe")} + +body = bpy.data.objects["UO_Body"] +UO_NAMES = {"UO_Body", "UO_Rig", "UO_Camera", "UO_Sun"} + + +def import_file(path): + ext = os.path.splitext(path)[1].lower() + before = set(bpy.data.objects) + if ext in (".glb", ".gltf"): + bpy.ops.import_scene.gltf(filepath=path) + elif ext == ".fbx": + bpy.ops.import_scene.fbx(filepath=path) + elif ext == ".obj": + bpy.ops.wm.obj_import(filepath=path) + elif ext == ".dae": + bpy.ops.wm.collada_import(filepath=path) + elif ext == ".stl": + bpy.ops.wm.stl_import(filepath=path) + elif ext == ".ply": + bpy.ops.wm.ply_import(filepath=path) + else: + raise ValueError("unsupported file type %r (use .glb .gltf .fbx .obj .dae .stl .ply)" % ext) + return [o for o in bpy.data.objects if o not in before] + + +def bake(ob): + """a new mesh object with the geometry of `ob` as it is evaluated now, in world space (own armature, modifiers applied)""" + dg = bpy.context.evaluated_depsgraph_get() + ev = ob.evaluated_get(dg) + me = bpy.data.meshes.new_from_object(ev, preserve_all_data_layers=True, depsgraph=dg) + me.transform(ob.matrix_world) + bm = bmesh.new(); bm.from_mesh(me) + for lay in list(bm.verts.layers.deform): # weights of the file's own skeleton: uo_bind_item.py makes its own + bm.verts.layers.deform.remove(lay) + bm.to_mesh(me); bm.free() + return bpy.data.objects.new(ob.name, me) + + +def run(): + if FILE: + everything = import_file(FILE) + meshes = [o for o in everything if o.type == "MESH"] + print("uo_import_item: meshes in the file (name, vertices, size in the file's units):") + for o in meshes: + d = np.array(o.dimensions) + print(" %-30s %7d %.3f x %.3f x %.3f%s" % (o.name, len(o.data.vertices), *d, " <- SKIP" if any(k.lower() in o.name.lower() for k in SKIP) else "")) + src = [o for o in meshes if not any(k.lower() in o.name.lower() for k in SKIP)] + imported = True + else: + src = [o for o in bpy.context.selected_objects if o.type == "MESH" and o.name not in UO_NAMES] + imported = False + if not src: + raise RuntimeError("no mesh to work on (FILE is empty and nothing is selected, or the file has no mesh)") + bpy.context.view_layer.update() + clo = bpy.data.collections.get("Clothing") or bpy.data.collections.new("Clothing") + if clo.name not in bpy.context.scene.collection.children: + bpy.context.scene.collection.children.link(clo) + news = [] + for o in src: + n = bake(o) + clo.objects.link(n) + news.append(n) + for o in (everything if imported else src): # drop what the file brought (meshes, armature, empties, lights, cameras) + bpy.data.objects.remove(o, do_unlink=True) + bpy.ops.object.select_all(action="DESELECT") + for n in news: + n.select_set(True) + bpy.context.view_layer.objects.active = news[0] + if JOIN and len(news) > 1: + bpy.ops.object.join() + news = [bpy.context.view_layer.objects.active] + for k, n in enumerate(news): + n.name = (NAME or os.path.splitext(os.path.basename(FILE))[0] or "Item") + ("" if len(news) == 1 else "_%d" % k) + n.data.name = n.name + verts = np.concatenate([np.array([v.co[:] for v in n.data.vertices]) for n in news]) + if TURN: + R = np.array(Matrix.Rotation(np.radians(TURN), 3, "Z")) + c0 = np.array([(verts[:, 0].min() + verts[:, 0].max()) / 2, (verts[:, 1].min() + verts[:, 1].max()) / 2, 0]) + for n in news: + n.data.transform(Matrix.Translation(c0) @ Matrix.Rotation(np.radians(TURN), 4, "Z") @ Matrix.Translation(-c0)) + verts = np.concatenate([np.array([v.co[:] for v in n.data.vertices]) for n in news]) + info = "%d mesh object(s), %d vertices, size %.3f x %.3f x %.3f (as imported)" % (len(news), len(verts), *(verts.max(0) - verts.min(0))) + if KIND: + if KIND not in EXTENTS: + raise ValueError("KIND must be one of %s" % list(EXTENTS)) + zlo, zhi, part = EXTENTS[KIND] + lo, hi = np.percentile(verts[:, 2], [PERCENT, 100 - PERCENT]) + s = SCALE if SCALE > 0 else (zhi - zlo) / max(hi - lo, 1e-9) + # sideways / front-back: the middle of the item on the middle of the body between the same heights + bz = np.array([v.co[:] for v in body.data.vertices]) + bz = (np.array(body.matrix_world)[:3, :3] @ bz.T).T + np.array(body.matrix_world)[:3, 3] + near = bz[(bz[:, 2] > zlo) & (bz[:, 2] < zhi) & (np.abs(bz[:, 0]) < 0.25)] + tx, ty = (np.median(near[:, 0]), (near[:, 1].min() + near[:, 1].max()) / 2) if len(near) else (0.0, 0.0) + ix, iy = [(np.percentile(verts[:, a], PERCENT) + np.percentile(verts[:, a], 100 - PERCENT)) / 2 for a in (0, 1)] + T = Matrix.Translation((tx, ty, zlo)) @ Matrix.Diagonal((s, s, s, 1.0)) @ Matrix.Translation((-ix, -iy, -lo)) + for n in news: + n.data.transform(T) + info += "; KIND %s: scale %.4f (height %.3f -> %.3f m), moved onto the body; PART for uo_bind_item.py: %r" % (KIND, s, hi - lo, zhi - zlo, part) + if not 0.3 < s < 3 and SCALE <= 0: + info += "\n WARNING: scale %.2f is far from 1: check the model's units, or that KIND is the right one" % s + nv = sum(len(n.data.vertices) for n in news) + if nv > 20000: + info += "\n WARNING: %d vertices: add a Decimate modifier (about 20k are enough for a 136x120 frame)" % nv + for n in news: + n.matrix_world = Matrix.Identity(4) + n.select_set(True) + bpy.context.view_layer.objects.active = news[0] + print("uo_import_item: " + info) + return news + + +FILE = os.environ.get("UO_IMPORT_FILE", FILE) +KIND = os.environ.get("UO_IMPORT_KIND", KIND) +SKIP = [k for k in os.environ.get("UO_IMPORT_SKIP", "").split(",") if k] or SKIP +_result = run() diff --git a/third_party/UO_Model3D_v13/pipeline/uo_job.py b/third_party/UO_Model3D_v13/pipeline/uo_job.py new file mode 100644 index 0000000..0c01064 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_job.py @@ -0,0 +1,125 @@ +# Runs a long script (render_uo_layer.py, uo_cloth_bake.py) step by step, so that Blender's window stays alive. +# +# A script that loops for minutes inside "Run Script" never gives control back to Blender: the window is not redrawn, the system +# marks it "Not Responding" (Blender 5.x on Windows shows this much sooner than 4.2) and it looks like a crash. Here the script +# is a generator that yields after every unit of work (a frame, a cloth step); run() feeds it from a modal operator: +# * between two steps Blender redraws; the progress is in the status bar (bottom of the window) and on the mouse cursor; +# * ESC cancels (the script's own clean-up runs, like with a STOP file); the other input is blocked while it works; +# * in background mode (blender -b, the bpy module, the tests) the generator simply runs to the end, exceptions included. +# Usage: uo_job = bpy.data.texts["uo_job.py"].as_module(); uo_job.run(generator, "title", finish, abort) +# generator : yields a short progress text (or None) after each step; raising / being closed ends it +# finish() : called once after the last step abort(why) : called after ESC, an error or STOP (generator already closed) +import time +import traceback + +import bpy + +BUDGET = 0.1 # s: steps run back to back until this much time passed since the last redraw (one step is at least run) + + +def _end(gen, why, finish, abort): + if why is None: + if finish: + finish() + return + try: + gen.close() # runs the finally: blocks of the generator + finally: + if abort: + abort(why) + + +class UO_OT_job(bpy.types.Operator): + bl_idname = "wm.uo_job" + bl_label = "UO job" + bl_options = {"INTERNAL"} + + def invoke(self, context, event): + wm = context.window_manager + self._t = wm.event_timer_add(0.01, window=context.window) + wm.modal_handler_add(self) + self._n = 0 + wm.progress_begin(0, 1000) + self._text(context, "starting (ESC cancels)") + return {"RUNNING_MODAL"} + + def _text(self, context, msg): + title = _job()["title"] + if context.workspace is not None: + context.workspace.status_text_set("%s: %s [ESC = cancel]" % (title, msg)) + if context.window_manager is not None: + context.window_manager.progress_update(self._n % 1000) + + def _done(self, context, why): + wm = context.window_manager + wm.event_timer_remove(self._t) + wm.progress_end() + if context.workspace is not None: + context.workspace.status_text_set(None) + job = dict(_job()); _job().clear() + try: + _end(job["gen"], why, job["finish"], job["abort"]) + except BaseException: + traceback.print_exc() + print("%s: %s" % (job["title"], "finished" if why is None else why), flush=True) + return {"FINISHED"} if why is None else {"CANCELLED"} + + def modal(self, context, event): + if event.type == "ESC" and event.value == "PRESS": + return self._done(context, "cancelled (ESC)") + if event.type != "TIMER": + return {"RUNNING_MODAL"} # nothing else is allowed to touch the scene while it works + t0 = time.time() + try: + while True: + msg = next(_job()["gen"]) + self._n += 1 + if msg: + self._text(context, msg) + if time.time() - t0 > BUDGET: + break + except StopIteration: + return self._done(context, None) + except BaseException as e: # KeyboardInterrupt = the STOP file of the render script + if not isinstance(e, KeyboardInterrupt): + traceback.print_exc() + return self._done(context, "stopped (%s)" % (e if isinstance(e, KeyboardInterrupt) else "error, see the system console")) + return {"RUNNING_MODAL"} + + + + +def _job(): + """the running job; kept in bpy.app.driver_namespace so that it survives as_module() running this text again + (only used in the interface: touching it in background mode made the bpy module crash when it shuts down)""" + return bpy.app.driver_namespace.setdefault("uo_job", {}) + + +def _register(): + old = getattr(bpy.types, "WM_OT_uo_job", None) + if old is not None: + try: + bpy.utils.unregister_class(old) + except Exception: + pass + bpy.utils.register_class(UO_OT_job) + + +def run(gen, title, finish=None, abort=None): + """run the generator `gen` (see the top of the file); returns when it is over (background) or at once (window)""" + if not bpy.app.background and _job(): + print("%s: another job is running (%s) - finish or cancel it with ESC first" % (title, _job()["title"])) + return False + if bpy.app.background or bpy.context.window is None: + try: + for _ in gen: + pass + except BaseException: + _end(gen, "error", finish, abort) + raise + _end(gen, None, finish, abort) + return True + _register() + _job().update(gen=gen, title=title, finish=finish, abort=abort) + bpy.ops.wm.uo_job("INVOKE_DEFAULT") + return True diff --git a/third_party/UO_Model3D_v13/pipeline/uo_layers_setup.py b/third_party/UO_Model3D_v13/pipeline/uo_layers_setup.py new file mode 100644 index 0000000..5411f07 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_layers_setup.py @@ -0,0 +1,127 @@ +"""Add the clothing-layer workflow to the model .blend: UO_Look node group, Clothing collection, example shirt, +render_uo_layer.py + uo_vd_writer.py text blocks.""" +import bpy, sys, os, math, pickle +import numpy as np +from mathutils import Vector + +SRC = sys.argv[sys.argv.index("--src") + 1] +OUT = sys.argv[sys.argv.index("--out") + 1] +os.makedirs(OUT, exist_ok=True) +bpy.context.preferences.filepaths.save_version = 0 +bpy.ops.wm.open_mainfile(filepath=os.path.abspath(SRC)) +sc = bpy.context.scene +body = bpy.data.objects["UO_Body"]; rig = bpy.data.objects["UO_Rig"] +light = pickle.load(open("uo_light.pkl", "rb")) +theta = math.radians(sc["uo_theta_deg"]) +right_w = Vector((1, 0, 0)); up_w = Vector((0, math.sin(theta), math.cos(theta))); tow_w = right_w.cross(up_w) +Lc = light["L_camera"] +Lw = (right_w * Lc[0] + up_w * Lc[1] + tow_w * Lc[2]).normalized() +sc["uo_look"] = 1.0 + +# ---------------------------------------------------------------- node group UO_Look +ng = bpy.data.node_groups.new("UO_Look", "ShaderNodeTree") +ng.interface.new_socket("Albedo", in_out="INPUT", socket_type="NodeSocketColor").default_value = (0.5, 0.5, 0.5, 1) +ng.interface.new_socket("Shader", in_out="OUTPUT", socket_type="NodeSocketShader") +N = ng.nodes.new; L = ng.links.new +gi = N("NodeGroupInput"); gi.location = (-900, 0) +go = N("NodeGroupOutput"); go.location = (600, 0) +bsdf = N("ShaderNodeBsdfPrincipled"); bsdf.location = (-100, 300); bsdf.inputs["Roughness"].default_value = 0.8 +geo = N("ShaderNodeNewGeometry"); geo.location = (-900, -300) +ldir = N("ShaderNodeCombineXYZ"); ldir.location = (-900, -550); ldir.label = "UO light direction (world)" +for i, v in enumerate(Lw): + ldir.inputs[i].default_value = v +dot = N("ShaderNodeVectorMath"); dot.operation = "DOT_PRODUCT"; dot.location = (-650, -350) +mx = N("ShaderNodeMath"); mx.operation = "MAXIMUM"; mx.inputs[1].default_value = 0.0; mx.location = (-450, -350) +mad = N("ShaderNodeMath"); mad.operation = "MULTIPLY_ADD"; mad.location = (-250, -350); mad.label = "ambient + diffuse*cos" +mad.inputs[1].default_value = light["diffuse"]; mad.inputs[2].default_value = light["ambient"] +mul = N("ShaderNodeMix"); mul.data_type = "RGBA"; mul.blend_type = "MULTIPLY"; mul.location = (-50, -150) +mul.inputs["Factor"].default_value = 1.0 +emis = N("ShaderNodeEmission"); emis.location = (200, -150) +mix = N("ShaderNodeMixShader"); mix.location = (420, 0) +look = N("ShaderNodeValue"); look.location = (200, 250); look.label = "UO look (driven by scene['uo_look'])" +fc = look.outputs[0].driver_add("default_value") +fc.driver.type = "AVERAGE" +var = fc.driver.variables.new(); var.type = "SINGLE_PROP" +var.targets[0].id_type = "SCENE"; var.targets[0].id = sc; var.targets[0].data_path = '["uo_look"]' +L(gi.outputs["Albedo"], bsdf.inputs["Base Color"]) +L(geo.outputs["Normal"], dot.inputs[0]); L(ldir.outputs["Vector"], dot.inputs[1]) +L(dot.outputs["Value"], mx.inputs[0]); L(mx.outputs["Value"], mad.inputs[0]) +L(gi.outputs["Albedo"], mul.inputs[6]); L(mad.outputs["Value"], mul.inputs[7]) +L(mul.outputs[2], emis.inputs["Color"]) +L(look.outputs[0], mix.inputs["Fac"]) +L(bsdf.outputs["BSDF"], mix.inputs[1]); L(emis.outputs["Emission"], mix.inputs[2]) +L(mix.outputs["Shader"], go.inputs["Shader"]) + +# ---------------------------------------------------------------- body material -> UO_Look group +mat = bpy.data.materials["UO_Skin"] +nt = mat.node_tree +old_mix = next(n for n in nt.nodes if n.type == "MIX_SHADER") +old_mul = next(n for n in nt.nodes if n.type == "MIX" and n.blend_type == "MULTIPLY") +albedo_socket = old_mul.inputs[6].links[0].from_socket # per-direction albedo selection chain +out = next(n for n in nt.nodes if n.type == "OUTPUT_MATERIAL") +grp = nt.nodes.new("ShaderNodeGroup"); grp.node_tree = ng; grp.location = (450, -100); grp.label = "UO_Look" +nt.links.new(albedo_socket, grp.inputs["Albedo"]) +nt.links.new(grp.outputs["Shader"], out.inputs["Surface"]) +for n in list(nt.nodes): + if n.type in ("MIX_SHADER", "EMISSION", "NEW_GEOMETRY", "COMBXYZ", "VECT_MATH") or n == old_mul \ + or (n.type == "MATH" and n.operation in ("MAXIMUM", "MULTIPLY_ADD")) \ + or (n.type == "VALUE" and n.label.startswith("UO look")): + nt.nodes.remove(n) +# keep a plain Principled for exporters (export.py links it to the output) +bsdf_b = next(n for n in nt.nodes if n.type == "BSDF_PRINCIPLED") +tex_global = next(n for n in nt.nodes if n.type == "TEX_IMAGE" and n.image and n.image.name == "UO_Body_Texture") +nt.links.new(tex_global.outputs["Color"], bsdf_b.inputs["Base Color"]) + +# ---------------------------------------------------------------- Clothing collection + example shirt +col = bpy.data.collections.new("Clothing") +sc.collection.children.link(col) +me = body.data +V = np.array([v.co[:] for v in me.vertices]) +nrm = np.array([v.normal[:] for v in me.vertices]) +gname = {g.index: g.name for g in body.vertex_groups} +W = {} +for v in me.vertices: + for g in v.groups: + W.setdefault(gname[g.group], np.zeros(len(V)))[v.index] = g.weight +shirt_w = sum(W.get(n, 0) for n in ("chest", "spine", "upper_arm.L", "upper_arm.R")) +keepv = shirt_w > 0.5 +keepv &= V[:, 2] > (V[:, 2].min() + 0.93) # not below the belt line +faces = [list(p.vertices) for p in me.polygons if all(keepv[i] for i in p.vertices)] +used = sorted({i for f in faces for i in f}) +remap = {o: n for n, o in enumerate(used)} +sv = V[used] + nrm[used] * 0.012 # 1.2 cm above the skin +sm = bpy.data.meshes.new("Example_Shirt") +sm.from_pydata(sv.tolist(), [], [[remap[i] for i in f] for f in faces]) +sm.update() +for p in sm.polygons: + p.use_smooth = True +shirt = bpy.data.objects.new("Example_Shirt", sm) +col.objects.link(shirt) +for name, w in W.items(): + vg = shirt.vertex_groups.new(name=name) + for n, o in enumerate(used): + if w[o] > 0: + vg.add([n], float(w[o]), "REPLACE") +shirt.parent = rig +mod = shirt.modifiers.new("Armature", "ARMATURE"); mod.object = rig +smat = bpy.data.materials.new("Example_Shirt_Mat"); smat.use_nodes = True +snt = smat.node_tree; snt.nodes.clear() +so = snt.nodes.new("ShaderNodeOutputMaterial"); so.location = (400, 0) +sg = snt.nodes.new("ShaderNodeGroup"); sg.node_tree = ng; sg.location = (150, 0) +sg.inputs["Albedo"].default_value = (0.35, 0.35, 0.35, 1) # grey = hue-able in UO +sp = snt.nodes.new("ShaderNodeBsdfPrincipled"); sp.location = (150, 300) +sp.inputs["Base Color"].default_value = (0.35, 0.35, 0.35, 1) +snt.links.new(sg.outputs["Shader"], so.inputs["Surface"]) +sm.materials.append(smat) +print("example shirt:", len(faces), "faces") + +# ---------------------------------------------------------------- text blocks +for name in ("render_uo_sprites.py",): + if name in bpy.data.texts: + bpy.data.texts.remove(bpy.data.texts[name]) +for name in ("uo_vd_writer.py", "render_uo_layer.py"): + t = bpy.data.texts.get(name) or bpy.data.texts.new(name) + t.from_string(open(name).read()) + t.use_module = False # loaded on demand via as_module(); no auto-run warning +bpy.ops.wm.save_as_mainfile(filepath=os.path.abspath(os.path.join(OUT, "UO_Body_0x190.blend"))) +print("saved") diff --git a/third_party/UO_Model3D_v13/pipeline/uo_materials.py b/third_party/UO_Model3D_v13/pipeline/uo_materials.py new file mode 100644 index 0000000..0930f3c --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_materials.py @@ -0,0 +1,192 @@ +# Put the materials of an item (typically a free model brought in by uo_import_item.py) into the UO look: every material slot is wired to the node group +# "UO_Look" (UO light: albedo x (ambient + diffuse * max(N.L, 0)), flat, no gloss, no reflections), with the colour the model's own material had. +# A foreign model brings PBR materials (metal, roughness, normal maps, emission, environment reflections); rendered as they are they come out with the wrong +# brightness and with reflections of an environment that UO does not have. UO metal (plate, helms, shields) is NOT matte, though: measured on the original +# sprites (plate 527, helm 563 against the same shape lit by UO_Look) it has a bright highlight where the surface faces the light/camera (the light sits at +# the camera), absent from cloth (trousers 431: brightest pixel 90/255, plate 252/255). So metal gets a Phong-like lobe on top of the UO light. +# What this script keeps from the material: +# - the colour: whatever feeds "Base Color" of the Principled BSDF (a texture, a colour attribute, a plain colour), or "Color" of a Diffuse / Emission node, +# or the viewport colour of a material without nodes; +# - the cut-out: whatever feeds "Alpha" (hair cards, lace, chains on a transparent texture) becomes transparency (a pixel is in the sprite when alpha >= 0.5); +# - metal: a material with Metallic >= METAL_AT (or METAL = True) gets the highlight SPEC_STRENGTH * albedo * max(N.L, 0) ^ SPEC_POWER added to the UO light; +# and drops the rest (roughness, normal / bump maps, emission, subsurface, coat, environment reflections): UO draws no such things. Normal maps are not baked into the +# geometry; a model that relies on them for its shape will look flatter than on its own. +# Run from Blender's Text Editor (Alt+P) after uo_import_item.py (the imported object is selected), or on the selected mesh objects of the scene. With nothing +# selected it takes every mesh object of the collection "Clothing". Idempotent: a material already wired to UO_Look is left alone. +# SATURATION = 0 : grey item. In UO items that take a hue (a dye) are drawn in greys, so a dyeable shirt should be SATURATION = 0, BRIGHTNESS = 1. +import bpy + +SATURATION = 1.0 # 1 = the model's colours, 0 = greys only (an item the game tints with a hue), in between = washed out +BRIGHTNESS = 1.0 # multiplier of the albedo (UO items are rarely darker than 0.15 or lighter than 0.9; the light is 0.08 + 0.92 cos) +CLAMP = True # albedo kept between 0.02 and 0.98 (sprites have neither pure black nor pure white, the 1-px outline is added by the renderer) +ALPHA = True # keep transparency from the model's Alpha input (False = opaque) +METAL = None # None = metal where the model's Metallic >= METAL_AT, True = every material is metal (plate), False = none (cloth, leather) +METAL_AT = 0.5 +SPEC_STRENGTH = 1.0 # highlight = SPEC_STRENGTH * albedo * max(N.L, 0) ^ SPEC_POWER, added to the UO light (linear light; the metal tints its own highlight). +SPEC_POWER = 16 # Measured on the metal-named wearable animations of the client (light_items.py, 41 animations, body normals as the proxy): mail / ring / chain + # SPEC_STRENGTH 0.7, power 11; the brightest quartile (plate, helms) 2.0, power 19; cloth and leather: Lambert only (0.3, no better than none). + # 1.0 / 16 is in between; use 2.0 / 19 for shiny plate, 0.7 / 11 for mail. Docs: docs/qa/light_shadow.md +REPORT = True + +_metallic = 0.0 +OUTPUT_TYPES = ("OUTPUT_MATERIAL",) + + +def find_colour_source(nt): + """(socket or None, default colour or None, alpha socket or None, default alpha) of the material's shader tree""" + out = next((n for n in nt.nodes if n.type in OUTPUT_TYPES and n.is_active_output), None) or next((n for n in nt.nodes if n.type in OUTPUT_TYPES), None) + if out is None or not out.inputs["Surface"].links: + return None, None, None, 1.0 + node = out.inputs["Surface"].links[0].from_node + seen = set() + while node.type in ("MIX_SHADER", "ADD_SHADER", "GROUP") and node not in seen: # first shader that carries a colour + seen.add(node) + ins = [i for i in node.inputs if i.type == "SHADER" and i.links] + if not ins: + break + node = ins[0].links[0].from_node + names = {"BSDF_PRINCIPLED": ("Base Color", "Alpha"), "BSDF_DIFFUSE": ("Color", None), "EMISSION": ("Color", None), "BSDF_TOON": ("Color", None), + "BSDF_GLOSSY": ("Color", None), "BSDF_TRANSLUCENT": ("Color", None), "SUBSURFACE_SCATTERING": ("Color", None), "BSDF_SHEEN": ("Color", None)} + if node.type not in names: + return None, None, None, 1.0 + cn, an = names[node.type] + global _metallic + _metallic = node.inputs["Metallic"].default_value if node.type == "BSDF_PRINCIPLED" and not node.inputs["Metallic"].links else \ + (1.0 if node.type == "BSDF_PRINCIPLED" else 0.0) # a Metallic fed by a texture: taken as metal + ci = node.inputs[cn] + col = ci.links[0].from_socket if ci.links else None + default = tuple(ci.default_value) if not ci.links else None + asock, aval = None, 1.0 + if an and ALPHA: + ai = node.inputs[an] + asock = ai.links[0].from_socket if ai.links else None + aval = ai.default_value if not ai.links else 1.0 + return col, default, asock, aval + + +def add_highlight(nt, ng, shader, where, albedo, default): + """shader + Emission(albedo * SPEC_STRENGTH * max(N.L, 0) ^ SPEC_POWER), L = the UO light of the node group (world space)""" + ldir = next(n for n in ng.nodes if n.type == "COMBXYZ") # "UO light direction (world)" + geo = nt.nodes.new("ShaderNodeNewGeometry"); geo.location = (where[0] - 600, where[1] - 420) + lv = nt.nodes.new("ShaderNodeCombineXYZ"); lv.location = (where[0] - 600, where[1] - 600) + for i in range(3): + lv.inputs[i].default_value = ldir.inputs[i].default_value + dot = nt.nodes.new("ShaderNodeVectorMath"); dot.operation = "DOT_PRODUCT"; dot.location = (where[0] - 400, where[1] - 480) + mxn = nt.nodes.new("ShaderNodeMath"); mxn.operation = "MAXIMUM"; mxn.inputs[1].default_value = 0.0; mxn.location = (where[0] - 250, where[1] - 480) + pw = nt.nodes.new("ShaderNodeMath"); pw.operation = "POWER"; pw.inputs[1].default_value = SPEC_POWER; pw.location = (where[0] - 120, where[1] - 480) + em = nt.nodes.new("ShaderNodeEmission") + if albedo is not None: + nt.links.new(albedo, em.inputs["Color"]) + else: + em.inputs["Color"].default_value = default + em.location = (where[0] + 40, where[1] - 400) + ml = nt.nodes.new("ShaderNodeMath"); ml.operation = "MULTIPLY"; ml.inputs[1].default_value = SPEC_STRENGTH; ml.location = (where[0] + 40, where[1] - 520) + nt.links.new(geo.outputs["Normal"], dot.inputs[0]); nt.links.new(lv.outputs["Vector"], dot.inputs[1]) + nt.links.new(dot.outputs["Value"], mxn.inputs[0]); nt.links.new(mxn.outputs["Value"], pw.inputs[0]) + nt.links.new(pw.outputs["Value"], ml.inputs[0]); nt.links.new(ml.outputs["Value"], em.inputs["Strength"]) + add = nt.nodes.new("ShaderNodeAddShader"); add.location = (where[0] + 200, where[1] - 100) + nt.links.new(shader, add.inputs[0]); nt.links.new(em.outputs["Emission"], add.inputs[1]) + return add.outputs["Shader"] + + +def convert(mat, ng): + """rewire `mat` to UO_Look; returns a short description""" + global _metallic + if mat is None: + return None + _metallic = 0.0 + if bpy.app.version < (5, 0, 0) and not mat.use_nodes: # Blender 5: every material has a node tree (use_nodes is deprecated) + d = tuple(mat.diffuse_color) + mat.use_nodes = True + nt = mat.node_tree + col, default, asock, aval = None, d, None, 1.0 + else: + nt = mat.node_tree + if any(n.type == "GROUP" and n.node_tree == ng for n in nt.nodes): + return "%s: already UO_Look" % mat.name + col, default, asock, aval = find_colour_source(nt) + metallic = _metallic + out = next((n for n in nt.nodes if n.type in OUTPUT_TYPES and n.is_active_output), None) or next((n for n in nt.nodes if n.type in OUTPUT_TYPES), None) + if out is None: + out = nt.nodes.new("ShaderNodeOutputMaterial") + where = out.location.x - 300, out.location.y + grp = nt.nodes.new("ShaderNodeGroup"); grp.node_tree = ng; grp.label = "UO_Look"; grp.location = (where[0], where[1]) + how = "colour" + if col is None: + grp.inputs["Albedo"].default_value = default if default is not None else (0.5, 0.5, 0.5, 1.0) + # saturation / brightness / clamp between the colour and the light + cur = col + if SATURATION != 1.0 or BRIGHTNESS != 1.0: + hs = nt.nodes.new("ShaderNodeHueSaturation"); hs.location = (where[0] - 220, where[1]) + hs.inputs["Saturation"].default_value = SATURATION; hs.inputs["Value"].default_value = BRIGHTNESS + if cur is not None: + nt.links.new(cur, hs.inputs["Color"]) + else: + hs.inputs["Color"].default_value = grp.inputs["Albedo"].default_value + cur = hs.outputs["Color"] + if CLAMP: + mapr = nt.nodes.new("ShaderNodeVectorMath"); mapr.operation = "MAXIMUM"; mapr.location = (where[0] - 440, where[1]) + mapr.inputs[1].default_value = (0.02, 0.02, 0.02) + mapx = nt.nodes.new("ShaderNodeVectorMath"); mapx.operation = "MINIMUM"; mapx.location = (where[0] - 330, where[1]) + mapx.inputs[1].default_value = (0.98, 0.98, 0.98) + if cur is not None: + nt.links.new(cur, mapr.inputs[0]) + else: + mapr.inputs[0].default_value = grp.inputs["Albedo"].default_value[:3] + nt.links.new(mapr.outputs["Vector"], mapx.inputs[0]) + cur = mapx.outputs["Vector"] + if cur is not None: + nt.links.new(cur, grp.inputs["Albedo"]) + shader = grp.outputs["Shader"] + if METAL or (METAL is None and metallic >= METAL_AT): # before the cut-out, so that nothing glows where the item is transparent + shader = add_highlight(nt, ng, shader, where, cur, grp.inputs["Albedo"].default_value) + how += " + metal highlight" + if ALPHA and (asock is not None or aval < 1.0): + tr = nt.nodes.new("ShaderNodeBsdfTransparent"); tr.location = (where[0], where[1] - 160) + mx = nt.nodes.new("ShaderNodeMixShader"); mx.location = (where[0] + 150, where[1]) + if asock is not None: + nt.links.new(asock, mx.inputs["Fac"]) + else: + mx.inputs["Fac"].default_value = aval + nt.links.new(tr.outputs["BSDF"], mx.inputs[1]); nt.links.new(shader, mx.inputs[2]) + shader = mx.outputs["Shader"] + how += " + alpha" + nt.links.new(shader, out.inputs["Surface"]) + # blend mode of the viewport / Cycles material: cut-out + try: + mat.blend_method = "CLIP" if "alpha" in how else "OPAQUE" + except Exception: + pass + return "%s: %s%s" % (mat.name, how, "" if col is not None else " (plain colour %s)" % ", ".join("%.2f" % c for c in grp.inputs["Albedo"].default_value[:3])) + + +def run(): + ng = bpy.data.node_groups.get("UO_Look") + if ng is None: + raise RuntimeError("node group UO_Look not found: open UO_Body_0x190.blend") + obs = [o for o in bpy.context.selected_objects if o.type == "MESH" and o.name not in ("UO_Body",)] + if not obs and "Clothing" in bpy.data.collections: + obs = [o for o in bpy.data.collections["Clothing"].all_objects if o.type == "MESH"] + done = set(); lines = [] + for o in obs: + if not o.material_slots: + o.data.materials.append(bpy.data.materials.new(o.name + "_Mat")) + lines.append("%s: had no material, plain grey UO_Look added" % o.name) + for sl in o.material_slots: + if sl.material is None: + sl.material = bpy.data.materials.new(o.name + "_Mat") + m = sl.material + if m.name in done: + continue + done.add(m.name) + r = convert(m, ng) + if r: + lines.append(r) + if REPORT: + print("uo_materials: %d object(s), %d material(s)" % (len(obs), len(done))) + for l in lines: + print(" " + l) + return lines + + +_result = run() diff --git a/third_party/UO_Model3D_v13/pipeline/uo_place_shield.py b/third_party/UO_Model3D_v13/pipeline/uo_place_shield.py new file mode 100644 index 0000000..cb95129 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_place_shield.py @@ -0,0 +1,89 @@ +# Put the SELECTED shield on the left forearm the way UO holds a shield (the bone shield.L: fitted frame by frame to the +# original UO shield, anim 582) and slide it towards the arm until its back touches the forearm. Run it from Blender's +# Text Editor. +# 1. Model / import the shield upright with its face towards the front view (Numpad 1), top up, point down. +# 2. Select it and run this script (the body is put in Rest Position while it works, as it was afterwards). +# 3. Then uo_bind_item.py with PART = "shield". +# Running it again places the shield again (any manual move is replaced). +import bpy, math +import numpy as np +from mathutils import Vector, Matrix +from mathutils.bvhtree import BVHTree + +GAP = 0.01 # m left between the back of the shield and the forearm skin +SHIFT = 0.0 # m, extra move along the shield's own axis after it touches (+ = further out, - = closer) + +# calibration (forearm.L bone space): centre, face normal of the shield disc +CENTRE = Vector((-0.07, 0.21, -0.03)) +NORMAL = Vector((-0.99622, -0.07987, 0.03415)).normalized() + +rig = bpy.data.objects["UO_Rig"] +body = bpy.data.objects["UO_Body"] + + +def arm_skin_bvh(): + """left forearm skin in world space (Rest Position)""" + dg = bpy.context.evaluated_depsgraph_get() + ev = body.evaluated_get(dg); me = ev.to_mesh() + V = [ev.matrix_world @ v.co for v in me.vertices] + names = [g.name for g in body.vertex_groups] + fa = [i for i, n in enumerate(names) if n in ("forearm.L", "forearm_twist.L")] + W = np.zeros(len(me.vertices)) + for v in body.data.vertices: + for g in v.groups: + if g.group in fa: + W[v.index] += g.weight + me.calc_loop_triangles() + tris = [t.vertices[:] for t in me.loop_triangles if np.mean(W[list(t.vertices)]) > 0.5] + ev.to_mesh_clear() + return BVHTree.FromPolygons(V, tris) + + +def place(ob): + if "shield.L" in rig.data.bones: # the shield bone: X width, Y height (top), Z face + M = rig.matrix_world @ rig.data.bones["shield.L"].matrix_local; M3 = M.to_3x3().normalized() + c = M.translation.copy(); n = M3.col[2].normalized(); up = M3.col[1].normalized() + else: # older file: the calibrated disc on forearm.L + b = rig.data.bones["forearm.L"] + M = rig.matrix_world @ b.matrix_local; M3 = M.to_3x3() + c = M @ CENTRE + n = (M3 @ NORMAL).normalized() + up = -(M3 @ NORMAL.cross(Vector((0, 1, 0)))).normalized() + y = -n # model -Y (front) -> n + x = y.cross(up).normalized(); z = x.cross(y).normalized() + R = Matrix((x, y, z)).transposed().to_4x4() + co = np.array([v.co[:] for v in ob.data.vertices]) + mid = Vector(((co.min(0) + co.max(0)) / 2).tolist()) # middle of the shield's bounds + S = Matrix.Diagonal(ob.matrix_world.to_scale()).to_4x4() + base = Matrix.Translation(c) @ R @ S @ Matrix.Translation(-mid) + back = (R.to_3x3() @ Vector((0, 1, 0))).normalized() # towards the arm + bvh = arm_skin_bvh() + P0 = [base @ Vector(p) for p in co] + + def closest(s): + d = back * s + return min(bvh.find_nearest(p + d)[3] for p in P0) + + s = -0.25 # start well away from the arm + while s < 0.25 and closest(s + 0.01) > GAP: + s += 0.01 + for _ in range(10): # refine to 1 mm + if closest(s + 0.001) > GAP: + s += 0.001 + s += SHIFT + ob.rotation_mode = "XYZ" + ob.matrix_world = Matrix.Translation(back * s) @ base + print("uo_place_shield: %s on the left forearm, back %.0f mm from the skin" % (ob.name, closest(s) * 1000)) + + +pose = rig.data.pose_position +rig.data.pose_position = "REST" +bpy.context.view_layer.update() +try: + obs = [o for o in bpy.context.selected_objects if o.type == "MESH" and o != body] + if not obs: + raise RuntimeError("select the shield first") + for ob in obs: + place(ob) +finally: + rig.data.pose_position = pose diff --git a/third_party/UO_Model3D_v13/pipeline/uo_place_weapon.py b/third_party/UO_Model3D_v13/pipeline/uo_place_weapon.py new file mode 100644 index 0000000..a72b195 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_place_weapon.py @@ -0,0 +1,41 @@ +# Put the SELECTED weapon on the shaft line of its class the way UO holds it (2H weapons, staffs, bows: left hand; 1H weapons: right hand), ready for uo_bind_item.py. +# 1. Model the weapon upright: shaft along +Z, head / tip UP (+Z), butt at the lowest point, object origin anywhere (apply scale first). +# 2. Select it, set PART below (polearm = staff, spear, halberd, bardiche, crook; axe2h = 2H axes; bow = bow, crossbow; weapon1h = sword, mace, hammer, 1H axe, dagger, kryss, club), run this (Alt+P). +# 3. Then uo_bind_item.py with the same PART (the weapon follows the bone polearm.L / axe2h.L / bow.L / weapon1h.R, calibrated on the original weapons). +# The shaft goes along the class line (WEAPON_MOTION in weapon_motion.json: point PIVOT, direction DIR in hand.L space, head towards +DIR) with the butt at +# the class's usual butt position (`butt`, m along the line; bows: their middle sits at 0). +# The roll about the shaft (weapon_roll_fit.py): model the head as a flat plate in the XZ plane of the weapon: its wide side along +X (the blade's flat, the +# bit / cutting edge of an axe towards +X), thin along Y. The script turns the weapon about its shaft so that +X lies in the plane the original weapon REF_ANIM +# has at roll 0 of the class (weapon_motion.json: roll.offsets; default the reference weapon of the class); the bone then turns it with the roll per pose +# (uo_weapon_bones.py). A class without "roll" (bows) keeps the turn of the shortest rotation +Z -> DIR. ROLL_DEG overrides the offset (degrees). +# Running it again places the weapon again. +import bpy, json, math +import numpy as np +from mathutils import Vector, Matrix + +PART = "polearm" # "polearm", "axe2h", "bow" or "weapon1h" +REF_ANIM = None # original weapon whose head orientation to copy (anim id, e.g. 624 halberd, 613 executioner's axe, 623 cutlass); None = the reference of the class +ROLL_DEG = None # or: offset of the head about the shaft in degrees (overrides REF_ANIM) +BONE = {"polearm": "polearm.L", "axe2h": "axe2h.L", "bow": "bow.L", "weapon1h": "weapon1h.R"}[PART] + +WM = json.loads(bpy.data.texts["weapon_motion.json"].as_string())[BONE] +rig = bpy.data.objects["UO_Rig"] +H = rig.matrix_world @ rig.data.bones[WM["parent"]].matrix_local # the hand bone (hand.L, hand.R) at rest -> world +piv = H @ Vector(WM["pivot"]); d = (H.to_3x3() @ Vector(WM["dir"])).normalized() +RO = WM.get("roll") +ru = None +if RO: # where +X of the weapon must point (perpendicular to the shaft) + delta = math.radians(ROLL_DEG) if ROLL_DEG is not None else RO["offsets"].get(str(REF_ANIM if REF_ANIM is not None else RO["ref"]), 0.0) + ru = (H.to_3x3() @ (Matrix.Rotation(delta, 3, Vector(WM["dir"]).normalized()) @ Vector(RO["e1"]))).normalized() +for ob in [o for o in bpy.context.selected_objects if o.type == "MESH"]: + co = np.array([ob.matrix_world @ v.co for v in ob.data.vertices]) + z0, ctr = co[:, 2].min(), co[:, :2].mean(0) # butt height, shaft axis (middle of the bounds in XY) + R = Vector((0, 0, 1)).rotation_difference(d).to_matrix().to_4x4() + start = piv + d * WM["butt"] # where the butt goes + Rr = Matrix.Identity(4) + if ru is not None: + x1 = R.to_3x3() @ Vector((1, 0, 0)) + Rr = Matrix.Rotation(math.atan2(d.dot(x1.cross(ru)), x1.dot(ru)), 4, d) + T = Matrix.Translation(start) @ Rr @ R @ Matrix.Translation(-Vector((ctr[0], ctr[1], z0))) + ob.matrix_world = T @ ob.matrix_world + print("uo_place_weapon: %s on the line of %s, butt at %.2f m along it" % (ob.name, BONE, WM["butt"])) diff --git a/third_party/UO_Model3D_v13/pipeline/uo_shield_keys.py b/third_party/UO_Model3D_v13/pipeline/uo_shield_keys.py new file mode 100644 index 0000000..55c8b34 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_shield_keys.py @@ -0,0 +1,31 @@ +# Update the motion of the shield bone (shield.L) in every UO action of THIS file to the latest fit on the original UO +# shield (anim 582). Your shield and its binding stay as they are. Run it once from Blender's Text Editor (Alt+P), then +# render again. Needs a file that already has the bone shield.L. +import bpy, json +import numpy as np +from mathutils import Quaternion, Vector + +# per UO action, per frame: turn (rotation vector, rad) and shift (m) of the shield in the bone's own axes +FRAMES = json.loads('{"0":[[0.25,-0.07,-0.23,0.041,0.015,0.015],[-0.0209,-0.0474,-0.2734,0.0453,0.0275,0.0181],[-0.3086,-0.3786,-0.15,0.0,0.026,0.0],[-0.0676,-0.3272,-0.1922,0.0085,0.0066,0.0043],[-0.3161,-0.3167,-0.2039,0.0242,-0.0394,-0.0081],[-0.2261,-0.2717,-0.2039,0.0392,0.0131,-0.0006],[-0.2261,-0.3167,-0.1589,0.0392,0.0131,0.0069],[-0.1561,-0.3167,-0.2289,0.0282,0.0021,0.0069],[-0.2011,-0.3617,-0.1389,0.0432,0.0096,0.0144],[-0.2011,-0.3167,-0.0939,0.0357,0.0096,0.0294]],"1":[[0.08,-0.17,-0.08,0.0075,-0.0225,-0.0265],[0.0643,0.0538,-0.1574,0.0001,0.0003,0.0179],[-0.025,-0.5686,-0.125,-0.015,-0.03,-0.0035],[0.02,-0.5686,-0.125,-0.03,-0.0225,-0.0035],[0.11,-0.5686,-0.215,0.0,-0.0525,-0.0185],[0.1778,-0.4032,-0.1365,0.0108,-0.0564,-0.0257],[-0.02,-0.6136,-0.105,-0.019,-0.0225,-0.03],[0.09,-0.5036,-0.11,0.0,-0.041,-0.019],[0.09,0.045,-0.125,0.0,-0.03,-0.015],[0.2184,-0.0857,-0.2378,-0.0188,-0.0224,-0.0338]],"2":[[-0.09,-0.1836,0.0,0.034,-0.0005,-0.06],[-0.2274,-0.1515,-0.0733,0.0225,-0.0224,-0.0434],[-0.5236,-0.3986,-0.135,0.0075,0.0075,-0.0075],[-0.4336,-0.3986,-0.135,-0.0075,0.0225,-0.0075],[-0.4136,-0.3186,-0.2,-0.015,0.0,-0.03],[-0.4136,-0.3436,-0.05,0.011,-0.0075,-0.03],[-0.1,-0.5236,-0.17,-0.045,0.0075,-0.03],[-0.27,-0.6136,-0.025,-0.011,-0.0075,-0.015],[-0.315,-0.5236,-0.105,0.004,0.011,0.0],[-0.065,-0.3986,-0.17,0.011,-0.011,-0.0225]],"3":[[-0.215,-0.3786,0.0,0.0,0.015,-0.03],[-0.6486,-0.3986,-0.08,0.015,0.0375,0.0],[-0.045,-0.4336,-0.08,0.0075,-0.03,-0.0375],[-0.02,-0.3886,-0.08,0.011,-0.026,-0.03],[0.06,-0.3886,-0.125,0.011,-0.0295,-0.06],[0.06,-0.3886,-0.055,0.026,-0.041,-0.03],[-0.005,-0.3186,-0.035,0.0415,-0.026,-0.015],[-0.3536,-0.5236,-0.045,0.015,0.015,0.0],[-0.3536,-0.4786,-0.09,0.0,0.011,-0.0035],[0.0174,-0.3956,-0.2445,-0.0014,0.0065,-0.0389]],"4":[[-0.5236,-0.3986,0.215,0.0225,0.0,0.0]],"5":[[-0.08,-0.4436,0.125,0.0,-0.03,-0.015],[-0.3928,-0.3455,0.0418,0.0101,-0.0117,-0.0118],[-0.3282,-0.5938,0.1625,0.0079,-0.0331,-0.0279],[-0.5236,-0.09,0.0,0.019,-0.015,-0.03],[-0.4436,-0.4336,0.045,-0.015,0.004,-0.0375]],"6":[[0.065,-0.3536,0.0,0.03,-0.03,-0.045],[0.2358,-0.6827,-0.0814,0.01,-0.0609,-0.0809],[0.3221,-0.5594,-0.0154,0.0196,-0.0544,-0.0712],[0.4255,-0.6013,-0.0061,0.0252,-0.0503,-0.0997],[-0.3536,-0.6136,0.2086,-0.015,0.0,-0.03]],"7":[[0.3536,-0.025,-0.065,0.06,-0.0375,0.0]],"8":[[-0.3736,-0.125,-0.015,0.015,0.0075,0.015]],"9":[[0.7586,-0.4786,-0.365,-0.0255,0.004,-0.075],[0.9736,-0.3086,-0.28,-0.0595,0.0,-0.03],[0.9936,-0.4786,-0.26,-0.037,-0.015,-0.075],[0.7386,-1.0022,-0.09,-0.0375,-0.03,-0.045],[1.274,-0.6731,-0.2722,-0.015,-0.0177,-0.1052],[0.9172,-0.9372,-0.5436,-0.09,0.0,-0.075],[0.9172,-0.7672,-0.5436,-0.06,0.0,-0.105]],"10":[[0.6736,-0.4836,-0.13,-0.015,-0.0525,-0.049],[0.7986,-0.5936,-0.21,-0.03,-0.03,-0.0715],[0.8786,-0.5036,-0.13,-0.015,-0.03,-0.0715],[0.7886,-0.4586,-0.13,-0.03,-0.03,-0.0755],[0.8686,-0.4586,-0.13,-0.011,-0.045,-0.0565],[0.295,-0.3886,-0.09,-0.0225,-0.0225,-0.015],[0.7386,-0.7522,-0.25,0.0,-0.03,-0.075]],"11":[[0.5236,-0.3136,-0.15,-0.0155,-0.0115,-0.03],[0.7136,-0.6136,-0.09,0.0,-0.0225,-0.0675],[0.7936,-0.3786,-0.09,-0.0115,-0.0375,-0.06],[0.8936,-0.3786,-0.135,0.0185,-0.0225,-0.09],[0.8486,-0.3786,-0.225,-0.0265,-0.015,-0.0525],[0.924,-0.7233,-0.342,-0.0554,0.0019,-0.1042],[1.094,-0.5733,-0.232,-0.0364,-0.0131,-0.1192]],"12":[[0.0,-0.3536,0.045,0.0,0.075,0.03],[0.09,-0.5236,0.2186,-0.03,0.019,0.0],[0.3536,-0.5236,0.145,-0.03,0.0,0.0],[0.4336,-0.4786,-0.09,-0.0115,0.0075,-0.0225],[1.0472,-0.17,-0.2036,0.0,0.0,0.03],[1.0022,-0.045,-0.9572,0.0115,0.015,0.004],[0.2636,-0.6936,-0.0936,-0.026,0.03,-0.06]],"13":[[0.295,-0.8072,-0.0314,0.004,0.0675,-0.0375],[0.215,-0.8522,-0.1214,-0.056,0.075,-0.0525],[0.045,-0.4786,-0.145,-0.0185,0.067,-0.0225],[0.275,-0.7872,-0.125,0.0075,0.0525,-0.0525],[-0.125,-0.9472,-0.2286,0.0,0.0525,-0.075],[0.5236,-0.7836,-0.2286,0.015,0.015,-0.015],[0.4786,-0.5686,-0.3086,0.0075,0.0115,-0.0225]],"14":[[0.6236,-0.9672,0.025,-0.0115,-0.0225,-0.03],[-1.1022,-0.8972,0.4336,-0.004,0.094,-0.045],[0.26,-1.2172,0.6372,-0.045,0.015,-0.045],[0.475,-1.1372,0.5122,-0.038,0.038,-0.0415],[0.5236,-1.0472,0.145,-0.09,0.026,-0.004],[-0.4136,-0.9472,0.5236,-0.075,0.045,0.015],[1.2622,0.42,0.3672,0.21,-0.004,-0.075]],"15":[[0.7386,-0.8322,0.1236,0.0075,0.0635,-0.045],[0.9319,-0.9089,0.0176,0.0164,0.0674,-0.024],[1.0119,-0.9089,0.1076,0.0014,0.0524,-0.039],[0.9482,-0.9063,0.0595,0.0097,0.0767,-0.0299],[0.8191,-0.8937,0.0462,0.0051,0.0522,-0.0341],[0.883,-0.9537,0.0421,0.0075,0.0777,-0.0419],[0.883,-0.9337,0.0421,0.0035,0.0627,-0.0419],[0.8676,-0.9435,0.0536,-0.0005,0.0682,-0.035],[0.6418,-0.9346,0.0448,-0.0075,0.0794,-0.0451],[0.864,-0.8387,0.0796,0.0072,0.0511,-0.0418]],"16":[[1.1922,-0.9222,-0.215,-0.03,-0.015,0.0],[0.2836,-0.2186,-0.125,0.0075,0.06,-0.019],[0.2186,-0.2986,0.0,0.0455,0.045,-0.0265],[0.7136,-0.5236,0.3536,0.06,-0.015,-0.015],[0.5236,-0.4236,0.1,0.015,0.015,0.0],[-0.08,-0.26,1.0372,0.03,0.015,-0.015],[0.5236,-0.3536,0.0,0.0375,0.0225,-0.0335]],"17":[[0.3536,0.3536,0.9536,0.165,-0.03,0.075],[0.6036,1.7058,0.9222,0.18,0.041,-0.0525],[0.5586,2.0458,0.6822,0.199,0.026,-0.0715],[0.5686,1.6608,-0.17,0.165,-0.015,-0.06],[0.7386,1.8308,0.0,0.195,-0.026,-0.06],[1.2172,-0.3536,-0.09,-0.015,-0.03,-0.075],[1.0922,-0.4786,0.015,-0.0375,-0.03,-0.0485]],"18":[[0.0,0.0,-0.15,0.019,0.0715,0.015],[0.5436,-0.19,-0.045,-0.0375,-0.056,0.0],[0.4186,-0.295,-0.045,-0.079,-0.052,-0.018],[1.4908,-0.2636,-0.3536,-0.116,-0.03,-0.056],[1.1951,-0.3574,-0.2946,-0.1161,-0.0189,-0.0021],[1.6477,-0.4376,-0.2296,-0.1006,-0.0166,-0.0402],[0.26,-0.8636,-0.34,-0.015,0.124,0.0]],"19":[[0.4236,-0.5236,-0.3536,-0.079,-0.019,-0.026],[1.0022,-0.6386,-0.26,-0.0375,-0.0565,-0.015],[1.1272,-0.7186,-0.305,-0.0525,-0.0415,-0.015],[1.0923,-0.7774,-0.3598,-0.05,-0.0516,-0.0374],[1.2623,-0.5624,-0.3598,-0.0425,-0.0591,0.0001],[0.7986,-0.3336,-0.3536,-0.0225,-0.03,-0.011],[0.3536,-0.3986,-0.25,-0.0565,0.015,0.03]],"20":[[0.125,-0.3536,0.0,0.015,0.03,-0.03],[0.5236,-0.17,0.045,-0.011,0.0115,0.019],[0.255,-0.5886,-0.135,0.0145,0.004,-0.03],[0.045,-0.6136,-0.045,0.0,0.004,-0.06],[-0.1071,-0.3054,0.0058,0.0208,0.0668,-0.0094]],"21":[[-0.3086,-0.13,0.1386,0.0075,0.0605,0.0],[-0.3536,-0.6936,0.4336,-0.049,0.06,-0.045],[0.02,-0.6486,0.3986,-0.0715,0.041,-0.045],[0.4786,-0.8522,0.5236,-0.0375,-0.03,-0.06],[0.5236,-0.5922,0.2636,-0.0675,-0.015,-0.0825],[0.5236,-0.5022,-0.1664,-0.1425,0.075,-0.0375]],"22":[[-0.17,-0.3536,0.15,0.0075,0.049,-0.03],[-0.8972,-0.6036,0.045,-0.075,0.09,-0.09],[-1.2022,-0.5286,0.27,-0.015,0.12,-0.0525],[0.5236,-0.07,-0.8772,-0.03,0.0675,-0.06],[0.7336,-0.05,-0.6372,-0.075,0.0865,-0.094],[-0.3536,0.09,-0.295,-0.0525,0.0075,-0.12]],"23":[[0.3736,-0.125,-0.5236,0.15,0.049,-0.026],[0.6636,-0.1788,-0.364,0.1468,0.0474,-0.0808],[0.8536,-0.1588,-0.364,0.1358,0.0249,-0.0808],[0.5146,-0.4165,-0.4279,0.1508,0.0334,-0.0911],[0.6846,-0.0765,-0.4279,0.1808,0.0594,-0.0911]],"24":[[0.5436,0.0,-0.3986,0.165,0.056,-0.056],[0.7716,-0.1351,-0.5734,0.1252,0.0559,-0.0807],[0.9166,-0.2801,-0.4284,0.1177,0.0559,-0.0432],[0.7655,-0.179,-0.3643,0.1266,0.0388,-0.0637],[0.8171,0.082,-0.4495,0.1298,0.0689,-0.0638]],"25":[[0.6936,0.0,-0.4336,0.131,0.03,-0.03]],"26":[[0.6936,-0.17,-0.3536,-0.0225,-0.0075,0.0],[0.2699,-0.3708,-0.0892,-0.0125,0.0222,-0.0034],[0.3699,-0.4508,-0.0892,0.0065,0.0297,-0.0034],[-0.2553,-0.6618,-0.1209,-0.0409,0.0522,-0.0528],[-0.0603,-0.6418,-0.0759,-0.1009,0.0522,-0.0488]],"27":[[0.045,-0.8322,-0.215,-0.03,0.075,-0.015],[1.3072,-0.9122,-0.235,-0.0485,0.0225,-0.045],[0.8772,-1.0472,-0.3536,-0.09,0.056,-0.004],[0.9672,-0.9222,-0.3736,-0.056,0.0185,-0.049],[1.3422,-0.8022,-0.495,-0.0185,0.0075,-0.045]],"28":[[-0.5236,0.5436,1.0672,0.0635,-0.06,0.03],[2.0944,-0.6286,-0.7072,-0.0225,-0.0375,-0.0525],[-0.7386,0.2436,-0.6936,0.0225,-0.0075,-0.0525],[-0.5659,0.3481,-0.4821,0.0179,-0.0083,-0.0331],[-0.2042,0.2623,-0.6632,-0.012,0.0018,-0.0658],[-0.3742,0.1373,-0.3232,0.048,-0.0207,-0.0658],[1.0472,-0.6936,-0.3086,-0.0675,-0.015,-0.015]],"29":[[0.6336,1.2372,0.1836,0.165,0.075,-0.09],[0.0786,1.4372,0.0036,0.195,0.071,-0.004],[-0.8386,0.6686,-1.4672,0.21,0.071,0.0525],[-0.17,-0.125,-2.4794,0.184,0.06,0.0375],[0.2989,0.117,-2.8556,0.1343,0.0538,0.0333]],"30":[[0.3336,-0.3986,0.3536,-0.015,-0.004,-0.03],[0.3886,-0.6136,0.09,-0.015,0.03,-0.03],[0.3536,-0.2886,0.2636,0.06,-0.019,0.015],[0.793,-0.0932,2.143,0.1508,0.0234,0.0397],[0.6,1.4186,0.1664,0.21,0.06,-0.075]],"31":[[0.6486,-0.5886,-0.08,-0.0225,0.0185,-0.019],[0.4786,-0.6486,-0.045,-0.0075,0.0335,-0.0225],[0.4192,-0.8101,-0.0528,0.0071,0.0768,-0.0009],[0.25,-0.5236,0.0,-0.015,0.0225,-0.026],[0.25,-0.5236,-0.02,0.011,-0.0115,-0.026],[0.225,-0.5686,0.17,-0.015,0.0185,-0.026],[-0.045,-1.4008,0.6136,-0.12,-0.034,-0.12]],"32":[[-0.045,-0.6286,0.045,0.0225,0.0415,-0.03],[-0.025,-0.5636,-0.075,0.023,0.053,-0.0185],[-0.3536,-0.6936,0.07,-0.0075,0.079,-0.015],[0.6936,-0.5936,0.025,-0.0225,0.0225,0.0],[0.045,-0.6486,0.045,0.0185,0.0375,-0.03]],"33":[[0.0,0.0,0.17,0.0825,0.015,-0.03],[-0.0951,0.1474,-0.0994,0.1087,-0.0243,-0.0252],[-0.466,0.2123,-0.1819,0.1091,-0.0087,-0.0166],[-0.0048,0.1016,-0.0,0.0775,0.0077,-0.0324],[-0.0753,0.133,-0.0897,0.0853,-0.0072,-0.0313]],"34":[[-0.09,-0.7872,-0.0936,0.015,0.015,-0.03],[-0.0399,-0.5953,0.0535,0.0259,0.0006,-0.0508],[0.0051,-0.6403,0.0535,0.0859,0.0196,-0.0133],[-0.2484,-0.6718,0.0628,0.0511,0.0147,-0.0246],[0.045,-0.6136,0.02,0.0225,0.0075,-0.0225]]}') + +rig = bpy.data.objects["UO_Rig"] +if "shield.L" not in rig.pose.bones: + raise RuntimeError("this file has no shield bone (shield.L) - use the current UO_Body_0x190.blend") +pb = rig.pose.bones["shield.L"] +pb.rotation_mode = "QUATERNION" +keep = rig.animation_data.action +n = 0 +for act in [a for a in bpy.data.actions if "uo_action" in a]: + rows = FRAMES.get(str(int(act["uo_action"]))) + if not rows: + continue + rig.animation_data.action = act + for i, p in enumerate(rows[:int(act["uo_frames"])]): + r = Vector(p[:3]); ang = r.length + pb.rotation_quaternion = Quaternion(r / ang, ang) if ang > 1e-9 else Quaternion() + pb.location = p[3:] + pb.keyframe_insert("location", frame=1 + 3 * i, group="shield.L") + pb.keyframe_insert("rotation_quaternion", frame=1 + 3 * i, group="shield.L") + n += 1 +rig.animation_data.action = keep +print("uo_shield_keys: shield.L updated in %d actions" % n) diff --git a/third_party/UO_Model3D_v13/pipeline/uo_transfer_corrections.py b/third_party/UO_Model3D_v13/pipeline/uo_transfer_corrections.py new file mode 100644 index 0000000..9da99e8 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_transfer_corrections.py @@ -0,0 +1,73 @@ +# Copy the per-frame shape corrections of UO_Body onto the SELECTED clothing / armour meshes. +# Use after the item is bound to the rig (Armature modifier + weights, see README). Run with Alt+P in the Text Editor. +# Every vertex takes the correction of the nearest point of the body skin (rest pose) of the bones the item is +# weighted to, so the item follows the corrected body in all 210 UO frames. Run it again after you edit the item's +# shape. uo_bind_item.py does the weights and this step in one run. +import bpy +import numpy as np +from mathutils import Vector +from mathutils.bvhtree import BVHTree +from mathutils.geometry import barycentric_transform + +body = bpy.data.objects["UO_Body"] +rig = bpy.data.objects["UO_Rig"] + + +def transfer(ob): + if body.data.shape_keys is None: # v13 body: no corrections, nothing to copy + print("uo_transfer_corrections: UO_Body has no corrective shape keys - nothing to do for", ob.name) + return + kb = body.data.shape_keys.key_blocks + basis = np.array([v.co[:] for v in kb["Basis"].data], np.float64) + body.data.calc_loop_triangles() + tri = [tuple(t.vertices) for t in body.data.loop_triangles] + # only the skin of the bones the item is weighted to (a breastplate never takes the arm corrections) + names = [g.name for g in body.vertex_groups] + allowed = {g.name for g in ob.vertex_groups} & set(names) + if allowed: + W = np.zeros((len(body.data.vertices), len(names))) + for v in body.data.vertices: + for g in v.groups: + W[v.index, g.group] = g.weight + dom = W[np.array(tri)].sum(1).argmax(1) + tri = [t for t, b in zip(tri, dom) if names[b] in allowed] or tri + bvh = BVHTree.FromPolygons([Vector(p) for p in basis], tri) + M = body.matrix_world.inverted() @ ob.matrix_world # item space -> body space + R = np.array(M.to_3x3().inverted()) # body offsets -> item space + src = [] + for v in ob.data.vertices: + p = M @ v.co + loc, nrm, fi, dist = bvh.find_nearest(p) + a, b, c = tri[fi] + A, B, C = (Vector(basis[k]) for k in (a, b, c)) + w = barycentric_transform(loc, A, B, C, Vector((1, 0, 0)), Vector((0, 1, 0)), Vector((0, 0, 1))) + src.append((a, b, c, w[0], w[1], w[2])) + src = np.array(src) + idx = src[:, :3].astype(int); wts = src[:, 3:] + if ob.data.shape_keys is None: + ob.shape_key_add(name="Basis", from_mix=False) + for k in [k for k in ob.data.shape_keys.key_blocks if k.name.startswith("uo_")]: + ob.shape_key_remove(k) + obasis = np.array([v.co[:] for v in ob.data.shape_keys.key_blocks["Basis"].data], np.float64) + drivers = {d.data_path: d for d in body.data.shape_keys.animation_data.drivers} + for k in [k for k in kb if k.name.startswith("uo_")]: + off = np.array([v.co[:] for v in k.data], np.float64) - basis + o = (off[idx] * wts[..., None]).sum(1) @ R.T + sk = ob.shape_key_add(name=k.name, from_mix=False) + sk.data.foreach_set("co", (obasis + o).ravel().astype(np.float32)) + src_d = drivers['key_blocks["%s"].value' % k.name].driver + d = sk.driver_add("value").driver; d.type = "SCRIPTED" + for sv in src_d.variables: + v = d.variables.new(); v.name = sv.name; v.type = sv.type + v.targets[0].id_type = sv.targets[0].id_type; v.targets[0].id = sv.targets[0].id + v.targets[0].data_path = sv.targets[0].data_path + d.expression = src_d.expression + print("corrections copied to", ob.name, len([k for k in kb if k.name.startswith("uo_")])) + + +pose = rig.data.pose_position +rig.data.pose_position = "REST" +bpy.context.view_layer.update() +for ob in [o for o in bpy.context.selected_objects if o.type == "MESH" and o != body]: + transfer(ob) +rig.data.pose_position = pose diff --git a/third_party/UO_Model3D_v13/pipeline/uo_vd_writer.py b/third_party/UO_Model3D_v13/pipeline/uo_vd_writer.py new file mode 100644 index 0000000..9d61356 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/uo_vd_writer.py @@ -0,0 +1,129 @@ +"""Minimal .vd (UOFiddler animation export) writer: numpy only, usable inside Blender. + +frames are RGBA uint8 arrays on a canvas where the character's ground point is at pixel (anchor_x, anchor_y). +Same format as vdtool.py (see README.md).""" +import struct +import numpy as np + +MAGIC = 6 +END = 0x7FFF7FFF +ACTIONS_BY_TYPE = {0: 22, 1: 13, 2: 35} + + +def rgb_to_c15(rgb): + rgb = np.asarray(rgb, np.int32) + r, g, b = [(rgb[..., i] * 31 + 127) // 255 for i in range(3)] + c = (r << 10) | (g << 5) | b + return np.where(c == 0, 1, c).astype(np.int64) # 0x0000 is transparent in the client + + +def c15_to_rgb(c): + c = np.asarray(c, np.int64) + return np.stack([((c >> 10) & 31) * 255 // 31, ((c >> 5) & 31) * 255 // 31, (c & 31) * 255 // 31], -1) + + +def median_cut(colors, counts, n=256): + """colors (K,3) int, counts (K,) -> palette (<=n,3) float.""" + boxes = [np.arange(len(colors))] + while len(boxes) < n: + spans = [np.ptp(colors[b], axis=0).max() if len(b) > 1 else -1 for b in boxes] + i = int(np.argmax(spans)) + if spans[i] <= 0: + break + b = boxes.pop(i) + ax = int(np.argmax(np.ptp(colors[b], axis=0))) + order = b[np.argsort(colors[b, ax])] + cum = np.cumsum(counts[order]) + k = int(np.searchsorted(cum, cum[-1] / 2)) + 1 + k = min(max(k, 1), len(order) - 1) + boxes += [order[:k], order[k:]] + return np.array([np.average(colors[b], axis=0, weights=counts[b]) for b in boxes]) + + +def build_palette(images): + """images: list of RGBA uint8. Returns (palette[256] 15-bit ints, list of index maps (-1 = transparent)).""" + masks = [im[..., 3] >= 128 for im in images] + c15 = [rgb_to_c15(im[..., :3]) for im in images] + allc = np.concatenate([c[m] for c, m in zip(c15, masks)] + [np.zeros(0, np.int64)]) + used, counts = np.unique(allc, return_counts=True) + if len(used) <= 256: + palette = used.tolist() + else: + pal_rgb = median_cut(c15_to_rgb(used).astype(np.float64), counts.astype(np.float64), 256) + palette = np.unique(rgb_to_c15(np.round(pal_rgb))).tolist() + palette = palette + [0] * (256 - len(palette)) + pal_rgb = c15_to_rgb(np.array(palette)).astype(np.int64) + valid = np.array(palette) > 0 + lut = {c: i for i, c in enumerate(palette) if c} + maps = [] + for im, c, m in zip(images, c15, masks): + idx = np.full(m.shape, -1, np.int16) + cc = c[m] + direct = np.array([lut.get(int(v), -1) for v in cc], np.int16) + miss = direct < 0 + if miss.any(): + src = c15_to_rgb(cc[miss]).astype(np.int64) + dist = ((src[:, None, :] - pal_rgb[None, valid, :]) ** 2).sum(-1) + direct[miss] = np.nonzero(valid)[0][dist.argmin(1)] + idx[m] = direct + maps.append(idx) + return palette, maps + + +def crop_frame(rgba, anchor_x, anchor_y): + """Canvas RGBA -> (cropped RGBA, centerX, centerY). Empty frame -> 1x1 transparent.""" + m = rgba[..., 3] >= 128 + if not m.any(): + return np.zeros((1, 1, 4), np.uint8), 0, -1 + ys, xs = np.nonzero(m) + y0, y1, x0, x1 = ys.min(), ys.max() + 1, xs.min(), xs.max() + 1 + crop = rgba[y0:y1, x0:x1] + return crop, int(anchor_x - x0), int((anchor_y - y0) - (y1 - y0)) + + +def encode_frame(idx, cx, cy): + h, w = idx.shape + out = bytearray(struct.pack("= 0 and x - x0 < 0xFFF: + x += 1 + out += struct.pack(" list of canvas RGBA frames. Missing blocks are written empty.""" + n = ACTIONS_BY_TYPE[anim_type] * 5 + head = bytearray(struct.pack(" 1e-9 else Quaternion() + if ROLL and roll is not None: # the turn of the weapon about its own axis (weapon_roll_fit.py): R' = R * Rot_line(phi) + q = q @ Quaternion(Vector(c["dir"]).normalized(), roll["phi"].get("%d,%d" % (int(act["uo_action"]), i), 0.0)) + pb.rotation_quaternion = q + pb.location = p[3:] + pb.keyframe_insert("location", frame=1 + 3 * i, group=b) + pb.keyframe_insert("rotation_quaternion", frame=1 + 3 * i, group=b) + n += 1 + print("uo_weapon_bones: %s keyed on %d poses" % (b, n)) +rig.animation_data.action = keep diff --git a/third_party/UO_Model3D_v13/pipeline/vd.py b/third_party/UO_Model3D_v13/pipeline/vd.py new file mode 100644 index 0000000..afb384d --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/vd.py @@ -0,0 +1,46 @@ +import struct, json, os +import numpy as np +from PIL import Image + +ACTIONS_PEOPLE = [ + "walk_unarmed","walk_armed","run_unarmed","run_armed","stand","fidget_1","fidget_2", + "combat_idle_1h","combat_idle_2h","attack_1h_slash","attack_1h_pierce","attack_1h_bash", + "attack_2h_bash","attack_2h_slash","attack_2h_pierce","combat_advance","spell_directed", + "spell_area","attack_bow","attack_crossbow","get_hit","die_forward","die_backward", + "mounted_walk","mounted_run","mounted_stand","mounted_attack_1h","mounted_attack_bow", + "mounted_attack_crossbow","mounted_attack_2h","block","punch","bow","salute","eat"] + +def c16(c): + r=(c>>10)&0x1f; g=(c>>5)&0x1f; b=c&0x1f + return (r*255//31, g*255//31, b*255//31) + +def read_vd(path): + d=open(path,'rb').read() + ft,at=struct.unpack_from('>22)&0x3ff); y=yb+((hdr>>12)&0x3ff); n=hdr&0xfff + idx=d[p:p+n]; p+=n + for k,ci in enumerate(idx): + img[y,x+k,:3]=pal[ci]; img[y,x+k,3]=255 + frames.append(dict(cx=cx,cy=cy,w=w,h=h,img=img)) + anims[(a,dr)]=frames + return at,nact,anims diff --git a/third_party/UO_Model3D_v13/pipeline/view3d.py b/third_party/UO_Model3D_v13/pipeline/view3d.py new file mode 100644 index 0000000..e82d0c6 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/view3d.py @@ -0,0 +1,39 @@ +"""Perspective Blender render of the skinned mesh in fitted poses (plausibility check, like the user's viewport).""" +import bpy, sys, pickle, math, os +import numpy as np +from mathutils import Vector +sys.argv = [a for a in sys.argv] +res_file = sys.argv[sys.argv.index("--res") + 1]; a = int(sys.argv[sys.argv.index("--action") + 1]); out = sys.argv[sys.argv.index("--out") + 1] +import jax.numpy as jnp +from posefit_mesh import posed, md +res = pickle.load(open(res_file, "rb"))[a]["poses"] +F = res["trans"].shape[0] +bpy.ops.wm.read_factory_settings(use_empty=True) +sc = bpy.context.scene +sc.render.engine = "CYCLES"; sc.cycles.samples = 8; sc.render.resolution_x, sc.render.resolution_y = 260, 320 +w = bpy.data.worlds.new("W"); sc.world = w; w.use_nodes = True; w.node_tree.nodes["Background"].inputs[0].default_value = (0.2, 0.21, 0.24, 1) +l = bpy.data.lights.new("S", "SUN"); l.energy = 3; lo = bpy.data.objects.new("S", l); lo.rotation_euler = (0.8, 0, -0.6); sc.collection.objects.link(lo) +cam = bpy.data.cameras.new("C"); cam.lens = 50; co = bpy.data.objects.new("C", cam); sc.collection.objects.link(co); sc.camera = co +mat = bpy.data.materials.new("M"); mat.use_nodes = True; mat.node_tree.nodes["Principled BSDF"].inputs["Base Color"].default_value = (0.7, 0.7, 0.7, 1) +tiles = [] +from PIL import Image +for i in range(F): + X = np.asarray(posed({k: jnp.asarray(v[i]) for k, v in res.items()})) + me = bpy.data.meshes.new("B%d" % i); me.from_pydata(X.tolist(), [], md["faces"]); me.update() + for p in me.polygons: p.use_smooth = True + me.materials.append(mat) + ob = bpy.data.objects.new("B%d" % i, me); sc.collection.objects.link(ob) + c = X.mean(0) + for yaw in (30, 120): + r = math.radians(yaw); pos = Vector((c[0] + 4.5 * math.sin(r), c[1] - 4.5 * math.cos(r), c[2] + 1.2)) + co.location = pos; co.rotation_euler = (Vector(c.tolist()) - pos).to_track_quat("-Z", "Y").to_euler() + p = os.path.abspath(f"{out}_{i}_{yaw}.png"); sc.render.filepath = p; bpy.ops.render.render(write_still=True) + tiles.append(p) + bpy.data.objects.remove(ob) +ims = [Image.open(p).convert("RGB") for p in tiles] +cols = 2 +grid = Image.new("RGB", (ims[0].width * F, ims[0].height * cols)) +for i in range(F): + for j in range(cols): + grid.paste(ims[i * cols + j], (i * ims[0].width, j * ims[0].height)) +grid.save(out + "_grid.png") diff --git a/third_party/UO_Model3D_v13/pipeline/viz.py b/third_party/UO_Model3D_v13/pipeline/viz.py new file mode 100644 index 0000000..e10d215 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/viz.py @@ -0,0 +1,18 @@ +import numpy as np +from PIL import Image +def overlay_row(tg, occs, zoom=4): + """tg: (5,H,W,4) uint8, occs: (5,H,W) float -> composite image: sprite with red model silhouette outline tint""" + tiles=[] + for d in range(len(tg)): + t=tg[d].astype(np.float32) + base=np.full(t.shape[:2]+(3,),40.0) + a=t[...,3:4]/255 + base=base*(1-a)+t[...,:3]*a + o=np.asarray(occs[d])[...,None] + # model: blue tint where model only, red where sprite only + col=base.copy() + col=col*(1-0.45*o)+np.array([60,120,255])*0.45*o + tiles.append(np.clip(col,0,255).astype(np.uint8)) + row=np.concatenate(tiles,1) + im=Image.fromarray(row) + return im.resize((im.width*zoom,im.height*zoom),Image.NEAREST) diff --git a/third_party/UO_Model3D_v13/pipeline/weapon_classify.py b/third_party/UO_Model3D_v13/pipeline/weapon_classify.py new file mode 100644 index 0000000..8a40169 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/weapon_classify.py @@ -0,0 +1,43 @@ +"""Which weapon class (bone) fits each original weapon animation best? For every weapon animation of anim..anim5 (list: item_animations.json, layers +OneHanded / TwoHanded) the sprite is fitted with the class line + class motion of every weapon bone of weapon_motion.json (weapon_fit.py `cross`: +the ends along the line are fitted per weapon). Reports the mean chamfer (px) per class and the best class. + + python weapon_classify.py WP.npz VDROOT META.json OUT.json [--procs 4] +VDROOT//anim_.vd (vdtool/mul2vd.py); META.json: {animation id: {file, local, name, layers, frames, complete}} +""" +import os, sys, json +import numpy as np +from multiprocessing import Pool + +HERE = os.path.dirname(os.path.abspath(__file__)) +sys.path.insert(0, HERE) +import weapon_fit as WF # noqa: E402 + +WM = json.load(open(os.path.join(HERE, "weapon_motion.json"))) +BONE_OF = {"polearm.L": "hand.L", "axe2h.L": "hand.L", "bow.L": "hand.L", "weapon1h.R": "hand.R"} + + +def one(args): + wp, vdroot, aid, m = args + path = os.path.join(vdroot, m["file"], "anim_%04d.vd" % m["local"]) + V = WF.Views(wp, path) + res = {} + for cls, C in WM.items(): + poses = {tuple(int(x) for x in k.split(",")): (v[:3], v[3:]) for k, v in C["poses"].items()} + line = {"p0": C["pivot"], "u": C["dir"], "piv": (np.array(C["pivot"]) - np.array(C["dir"]) * (np.array(C["pivot"]) @ np.array(C["dir"]))).tolist()} + per, x = WF.apply_class(V, BONE_OF[cls], line, poses) + per0, _ = WF.apply_class(V, BONE_OF[cls], line, {}) + res[cls] = dict(chamfer=float(per.mean()), rigid=float(per0.mean()), extent=[float(x[0]), float(x[1])]) + best = min(res, key=lambda c: res[c]["chamfer"]) + print(aid, m["name"], best, {c: round(r["chamfer"], 2) for c, r in res.items()}, flush=True) + return aid, dict(name=m["name"], file=m["file"], local=m["local"], views=V.n, classes=res, best=best) + + +if __name__ == "__main__": + wp, vdroot, meta, out = sys.argv[1:5] + procs = int(sys.argv[sys.argv.index("--procs") + 1]) if "--procs" in sys.argv else 4 + meta = json.load(open(meta)) + jobs = [(wp, vdroot, aid, m) for aid, m in sorted(meta.items(), key=lambda kv: int(kv[0]))] + with Pool(procs) as p: + res = dict(p.imap_unordered(one, jobs)) + json.dump(res, open(out, "w"), indent=1) diff --git a/third_party/UO_Model3D_v13/pipeline/weapon_fit.py b/third_party/UO_Model3D_v13/pipeline/weapon_fit.py new file mode 100644 index 0000000..4c87aa4 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/weapon_fit.py @@ -0,0 +1,234 @@ +"""Offline calibration of how UO holds a weapon, from the original weapon animation (anim.mul) and the exported poses of the model. + +A weapon is a straight shaft (a stick: two end points) in the local frame of a hand bone. Metric = symmetric chamfer distance in pixels +between the projected stick and the sprite (mean of: stick samples -> nearest sprite pixel, sprite pixels -> nearest point of the stick), +like the report (8.3). numpy / scipy only. + + python weapon_fit.py rigid WP.npz VDDIR ANIM BONE [--len 1.0] one rigid stick in the bone for all frames (report 8.3) + python weapon_fit.py perpose WP.npz VDDIR ANIM BONE [--len 1.0] [--out F.json] + a correction (turn, shift in the bone frame) per pose +Library: Views (masks, distance transforms, projection), rigid_fit, chamfer. +""" +import os, sys, json +import numpy as np +from scipy import ndimage, optimize + +HERE = os.path.dirname(os.path.abspath(__file__)) +sys.path.insert(0, os.path.join(HERE, "..", "vdtool")) +import vdtool # noqa: E402 + + +class Views: + """all (pose, direction) views of one weapon animation: sprite masks on the canvas of WP.npz, distance transforms, projection rows""" + + def __init__(self, wp_npz, vd_path, bones=None, max_px=60): + d = np.load(wp_npz) + self.bones = [str(b) for b in d["bones"]]; self.W, self.H = (int(x) for x in d["canvas"]); ax, ay = (int(x) for x in d["anchor"]) + _, blocks = vdtool.read_vd(vd_path) + blk = {(b["action"], b["dir"]): b for b in blocks} + keep, masks = [], [] + for n, (a, di, i) in enumerate(d["key"]): + b = blk.get((int(a), int(di))) + if b is None or i >= len(b["frames"]): + continue + f = b["frames"][i]; rgba = vdtool.frame_rgba(f, b["palette"]); h, w = rgba.shape[:2] + m = np.zeros((self.H, self.W), bool); x0, y0 = ax - f["cx"], ay - f["cy"] - f["h"] + ys, xs = slice(max(y0, 0), min(y0 + h, self.H)), slice(max(x0, 0), min(x0 + w, self.W)) + if ys.stop > ys.start and xs.stop > xs.start: + m[ys, xs] = rgba[ys.start - y0:ys.stop - y0, xs.start - x0:xs.stop - x0, 3] > 0 + if m.sum() >= 4: + keep.append(n); masks.append(m) + keep = np.array(keep) + self.n = len(keep); self.key = d["key"][keep]; self.PX = d["PX"][keep]; self.BW = d["BW"][keep]; self.masks = np.array(masks) + self.DT = np.array([ndimage.distance_transform_edt(~m) for m in self.masks]).astype(np.float32) + rng = np.random.default_rng(0) + self.pts = np.zeros((self.n, max_px, 2)); self.npts = np.zeros(self.n, int) + for k, m in enumerate(self.masks): + p = np.argwhere(m)[:, ::-1] + 0.5 + if len(p) > max_px: + p = p[rng.choice(len(p), max_px, replace=False)] + self.pts[k, :len(p)] = p; self.npts[k] = len(p) + + def bone_world(self, bone, unscaled=True): + """world matrices of a bone's pose; unscaled: the scale of the pose (up to 1.3 in the hand) removed from the rotation columns, i.e. what a + child bone with inherit_scale NONE gets""" + M = self.BW[:, self.bones.index(bone)].copy() + if unscaled: + M[:, :3, :3] /= np.linalg.norm(M[:, :3, :3], axis=1, keepdims=True) + return M + + def project(self, Mbone, P): + """points P (..., 3) in the local frame of a bone with world matrices Mbone (n,4,4) -> pixels (n, ..., 2)""" + Pw = np.einsum("nij,...j->n...i", Mbone[:, :3, :3], P) + Mbone[:, :3, 3].reshape((self.n,) + (1,) * (P.ndim - 1) + (3,)) + Pw1 = np.concatenate([Pw, np.ones(Pw.shape[:-1] + (1,))], -1) + return np.einsum("nij,n...j->n...i", self.PX[:, :2], Pw1) + + +def chamfer(V, A, B, ns=40, cap=15.0, parts=False): + """per view symmetric chamfer (px) of the segments A -> B in pixel coordinates (n,2); capped at `cap` px""" + t = np.linspace(0, 1, ns + 1)[None, :, None] + S = A[:, None] + (B - A)[:, None] * t # (n, ns+1, 2) samples of the stick + xi = np.clip(S[..., 0].astype(int), 0, V.W - 1); yi = np.clip(S[..., 1].astype(int), 0, V.H - 1) + d1 = np.minimum(V.DT[np.arange(V.n)[:, None], yi, xi], cap).mean(1) + e = (B - A)[:, None]; ll = (e ** 2).sum(-1) + 1e-9 + tt = np.clip((((V.pts - A[:, None]) * e).sum(-1)) / ll, 0, 1) + dd = np.sqrt(((A[:, None] + e * tt[..., None] - V.pts) ** 2).sum(-1)) + valid = np.arange(V.pts.shape[1])[None] < V.npts[:, None] + d2 = (np.minimum(dd, cap) * valid).sum(1) / np.maximum(V.npts, 1) + return (d1, d2) if parts else 0.5 * (d1 + d2) + + +def unit(th, ph): + return np.array([np.sin(th) * np.cos(ph), np.sin(th) * np.sin(ph), np.cos(th)]) + + +def rigid_fit(V, bone, L0=1.0, grip0=(0, 0, 0), verbose=True): + """one rigid stick (p0, direction, length) in the bone frame for all views; returns dict and per-view chamfer""" + M = V.bone_world(bone) + def f(x): + p0 = x[2:5]; u = unit(x[0], x[1]); a, b = V.project(M, np.array([p0, p0 + u * x[5]]))[:, 0], None + pr = V.project(M, np.array([p0, p0 + u * x[5]])) + return chamfer(V, pr[:, 0], pr[:, 1]).mean() + best = (1e9, None) + for th in np.linspace(0, np.pi, 9): + for ph in np.linspace(-np.pi, np.pi, 16, endpoint=False): + x = np.array([th, ph, *grip0, L0]); v = f(x) + if v < best[0]: best = (v, x) + r = optimize.minimize(f, best[1], method="Powell", options=dict(xtol=1e-3, ftol=1e-5, maxiter=4000)) + x = r.x; p0 = x[2:5]; u = unit(x[0], x[1]); pr = V.project(M, np.array([p0, p0 + u * x[5]])) + per = chamfer(V, pr[:, 0], pr[:, 1]) + if verbose: + print("rigid in %s: grip %s dir %s len %.2f chamfer mean %.2f median %.2f px" % (bone, np.round(p0, 3), np.round(u, 3), x[5], per.mean(), np.median(per))) + return dict(bone=bone, p0=p0.tolist(), u=u.tolist(), length=float(x[5])), per + + +def rodrigues(r): + a = np.linalg.norm(r) + if a < 1e-12: + return np.eye(3) + k = r / a; K = np.array([[0, -k[2], k[1]], [k[2], 0, -k[0]], [-k[1], k[0], 0]]) + return np.eye(3) + np.sin(a) * K + (1 - np.cos(a)) * K @ K + + +def perpose_fit(Vs_, line, extents, bone, ridge=(0.02, 0.2), ns=24, verbose=True): + """per pose (action, frame; the 5 directions share it): turn r (rotation vector, rad) and shift t (m) in the bone frame, applied to the sticks of + the class line (p0, u) about its point nearest to the bone origin, minimising the chamfer over the views of that pose of all weapons in Vs_ (each with its + own extent (s0, s1) along the line). A stick leaves 2 of 6 degrees free (turn about its axis, shift along it): the ridge keeps them at 0. + Returns {(a, i): (r, t)} and the per-view chamfer of every weapon.""" + p0 = np.array(line["p0"]); u = np.array(line["u"]); piv = p0 - u * (p0 @ u) + Ms = [V.bone_world(bone) for V in Vs_] + ends = [np.array([piv + u * e[0], piv + u * e[1]]) for e in extents] + poses = sorted({(int(a), int(i)) for V in Vs_ for a, _, i in V.key}) + out, per = {}, [np.zeros(V.n) for V in Vs_] + for (a, i) in poses: + parts = [] + for w, V in enumerate(Vs_): + sel = np.nonzero((V.key[:, 0] == a) & (V.key[:, 2] == i))[0] + if len(sel): + parts.append((w, sel, _sub(V, sel), Ms[w][sel])) + def res(x): + R = rodrigues(x[:3]); out_ = [] + for w, sel, Vs, Mb in parts: + E = (ends[w] - piv) @ R.T + piv + x[3:] + pr = Vs.project(Mb, E); A, B = pr[:, 0], pr[:, 1] + t = np.linspace(0, 1, ns + 1)[None, :, None]; S = A[:, None] + (B - A)[:, None] * t + d1 = np.stack([ndimage.map_coordinates(Vs.DT[k], [S[k, :, 1] - 0.5, S[k, :, 0] - 0.5], order=1, mode="nearest") for k in range(Vs.n)]) + e = (B - A)[:, None]; ll = (e ** 2).sum(-1) + 1e-9 + tt = np.clip((((Vs.pts - A[:, None]) * e).sum(-1)) / ll, 0, 1) + d2 = np.sqrt(((A[:, None] + e * tt[..., None] - Vs.pts) ** 2).sum(-1)) * (np.arange(Vs.pts.shape[1])[None] < Vs.npts[:, None]) + out_ += [(d1 / np.sqrt(ns + 1)).ravel(), (d2 / np.sqrt(np.maximum(Vs.npts, 1))[:, None]).ravel()] + return np.concatenate(out_ + [x[:3] / ridge[0] * 0.1, x[3:] / ridge[1] * 0.1]) + r = optimize.least_squares(res, np.zeros(6), loss="soft_l1", f_scale=3.0, x_scale=np.array([0.2] * 3 + [0.05] * 3)) + R = rodrigues(r.x[:3]) + for w, sel, Vs, Mb in parts: + E = (ends[w] - piv) @ R.T + piv + r.x[3:] + pr = Vs.project(Mb, E); per[w][sel] = chamfer(Vs, pr[:, 0], pr[:, 1]) + out[(a, i)] = (r.x[:3].tolist(), r.x[3:].tolist()) + if verbose: + print("per-pose fit in %s: chamfer mean %s px" % (bone, ", ".join("%.2f" % p.mean() for p in per))) + return out, per + + +def apply_class(V, bone, line, poses, fit_extent=True): + """stick of a class line (p0, u) moved by the per-pose corrections; only the two ends along the line are fitted for this weapon. + Returns the per-view chamfer and the extent (s0, s1) in m from the point of the line nearest to the bone origin.""" + M = V.bone_world(bone); p0 = np.array(line["p0"]); u = np.array(line["u"]); piv = np.array(line["piv"]) if "piv" in line else p0 - u * (p0 @ u) + Rt = [] + for a, i, _ in [(k[0], k[2], 0) for k in V.key]: + r, t = poses.get((int(a), int(i)), ([0, 0, 0], [0, 0, 0])); Rt.append((rodrigues(np.array(r)), np.array(t))) + def ends(s0, s1): + E = np.array([piv + u * s0, piv + u * s1]) + return np.array([(E - piv) @ R.T + piv + t for R, t in Rt]) # (n, 2, 3) + def pr(s0, s1): + E = ends(s0, s1) + Pw = np.einsum("nij,nkj->nki", M[:, :3, :3], E) + M[:, None, :3, 3] + Pw1 = np.concatenate([Pw, np.ones(Pw.shape[:-1] + (1,))], -1) + return np.einsum("nij,nkj->nki", V.PX[:, :2], Pw1) + f = lambda s: (lambda p: chamfer(V, p[:, 0], p[:, 1]).mean())(pr(*s)) + best = (1e9, None) + for s0 in np.linspace(-1.5, 0.5, 9): + for s1 in np.linspace(s0 + 0.3, s0 + 3.0, 10): + v = f((s0, s1)) + if v < best[0]: best = (v, (s0, s1)) + r = optimize.minimize(f, best[1], method="Powell", options=dict(xtol=1e-3, ftol=1e-5)) + p = pr(*r.x) + return chamfer(V, p[:, 0], p[:, 1]), r.x + + +def _sub(V, sel): + class S: pass + s = S(); s.n = len(sel); s.W, s.H = V.W, V.H + for k in ("key", "PX", "BW", "masks", "DT", "pts", "npts"): setattr(s, k, getattr(V, k)[sel]) + s.project = lambda Mb, P, s=s: Views.project(s, Mb, P) + return s + + +if __name__ == "__main__": + if sys.argv[1] == "class": # class WP.npz VDDIR BONE OUT.json ANIM [ANIM ...] [--line LINE.json] + wp, vd, bone, out = sys.argv[2:6]; anims = [a for a in sys.argv[6:] if a.isdigit()] + Vs = [Views(wp, os.path.join(vd, "anim_%04d.vd" % int(a))) for a in anims] + if "--line" in sys.argv: + rig = json.load(open(sys.argv[sys.argv.index("--line") + 1]))["rigid"] + else: + rig, _ = rigid_fit(Vs[0], bone, 1.6) + poses = {} + for it in range(3): + ex = [apply_class(V, bone, rig, poses)[1] for V in Vs] + print("iteration", it, "extents", [tuple(np.round(e, 2)) for e in ex]) + poses, per = perpose_fit(Vs, rig, ex, bone) + ex = [apply_class(V, bone, rig, poses)[1] for V in Vs] + res = {a: float(apply_class(V, bone, rig, poses)[0].mean()) for a, V in zip(anims, Vs)} + print("final chamfer per weapon:", {a: round(v, 2) for a, v in res.items()}) + json.dump(dict(anims=[int(a) for a in anims], bone=bone, rigid=rig, extents={a: [float(x) for x in e] for a, e in zip(anims, ex)}, chamfer=res, + poses={"%d,%d" % k: v for k, v in poses.items()}), open(out, "w")) + sys.exit() + if sys.argv[1] == "xline": # xline WP.npz VDDIR POLEARM.json BONE ANIM_WITH_OWN_LINE...: own rigid line, polearm motion + wp, vd, cls, bone = sys.argv[2:6]; C = json.load(open(cls)); poses = {tuple(int(x) for x in k.split(",")): v for k, v in C["poses"].items()} + p0 = np.array(C["rigid"]["p0"]); u = np.array(C["rigid"]["u"]); piv = (p0 - u * (p0 @ u)).tolist() + for anim in sys.argv[6:]: + V = Views(wp, os.path.join(vd, "anim_%04d.vd" % int(anim))) + rig, per_r = rigid_fit(V, bone, 1.0, verbose=False); rig["piv"] = piv + per, x = apply_class(V, bone, rig, poses) + print("anim %s: own rigid line %.2f px; own line + polearm motion %.2f px (median %.2f)" % (anim, per_r.mean(), per.mean(), np.median(per))) + sys.exit() + if sys.argv[1] == "cross": # cross WP.npz VDDIR CLASS.json BONE ANIM... + wp, vd, cls, bone = sys.argv[2:6]; C = json.load(open(cls)); poses = {tuple(int(x) for x in k.split(",")): v for k, v in C["poses"].items()} + for anim in sys.argv[6:]: + V = Views(wp, os.path.join(vd, "anim_%04d.vd" % int(anim))) + per0, x0 = apply_class(V, bone, C["rigid"], {}) + per, x = apply_class(V, bone, C["rigid"], poses) + print("anim %s: class line, rigid %.2f px -> with the per-pose motion %.2f px (median %.2f), extent %.2f..%.2f m" % (anim, per0.mean(), per.mean(), np.median(per), x[0], x[1])) + sys.exit() + cmd, wp, vd, anim, bone = sys.argv[1:6] + V = Views(wp, os.path.join(vd, "anim_%04d.vd" % int(anim))) + print("views", V.n) + L0 = float(sys.argv[sys.argv.index("--len") + 1]) if "--len" in sys.argv else 1.0 + if cmd == "rigid": + rig, per = rigid_fit(V, bone, L0) + if "--out" in sys.argv: + json.dump(dict(anim=int(anim), rigid=rig, chamfer=float(per.mean())), open(sys.argv[sys.argv.index("--out") + 1], "w")) + elif cmd == "perpose": + rig, per0 = rigid_fit(V, bone, L0) + _, x = apply_class(V, bone, rig, {}) + fit, per = perpose_fit([V], rig, [x], bone) + if "--out" in sys.argv: + json.dump(dict(anim=int(anim), rigid=rig, poses={"%d,%d" % k: v for k, v in fit.items()}), open(sys.argv[sys.argv.index("--out") + 1], "w")) diff --git a/third_party/UO_Model3D_v13/pipeline/weapon_motion.json b/third_party/UO_Model3D_v13/pipeline/weapon_motion.json new file mode 100644 index 0000000..d6c6235 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/weapon_motion.json @@ -0,0 +1 @@ +{"polearm.L": {"parent": "hand.L", "pivot": [0.0282, 0.035, 0.0101], "dir": [-0.281, -0.0498, 0.9584], "anims": {"648": [-1.03, 0.914], "614": [-1.014, 0.944], "641": [-1.036, 1.247], "624": [-1.028, 1.067], "617": [-1.042, 1.356], "628": [-1.044, 1.244]}, "chamfer": {"648": 0.6, "614": 1.07, "641": 0.69, "624": 0.95, "617": 0.68, "628": 0.67}, "poses": {"0,0": [-0.0806, -0.2075, 0.0295, -0.1915, -0.0157, 0.3574], "0,1": [-0.309, 0.0082, -0.05, -0.0795, 0.0706, 0.3081], "0,2": [-0.2044, 0.0052, -0.0026, -0.0909, 0.0591, 0.3158], "0,3": [0.0786, -0.1114, 0.0084, -0.1271, -0.0487, 0.2975], "0,4": [-0.2447, -0.0797, 0.0263, -0.0905, 0.0495, 0.2805], "0,5": [-0.3235, -0.0463, -0.0667, -0.0822, 0.0637, 0.281], "0,6": [-0.1497, -0.0313, -0.0337, -0.068, 0.0094, 0.2734], "0,7": [-0.183, -0.033, -0.0754, -0.0567, -0.0039, 0.2451], "0,8": [-0.1658, -0.0596, -0.0602, -0.0521, -0.0083, 0.2185], "0,9": [-0.3071, -0.1198, -0.0494, -0.0923, 0.0138, 0.2308], "1,0": [0.0388, -0.2486, -0.0034, -0.0001, 0.0008, 0.0145], "1,1": [0.1353, -0.031, 0.0325, -0.0231, -0.0254, 0.0146], "1,2": [0.1226, 0.1248, 0.0402, 0.0034, 0.0022, 0.0019], "1,3": [0.2205, 0.1762, 0.0823, -0.0061, 0.0035, 0.0095], "1,4": [0.4384, 0.2879, 0.1348, 0.0031, 0.0002, 0.0175], "1,5": [0.2664, 0.3158, 0.0773, -0.0005, -0.0274, 0.01], "1,6": [0.2386, 0.2658, 0.0687, -0.0014, 0.0157, 0.0136], "1,7": [0.3446, 0.0865, 0.098, -0.0079, -0.0046, 0.0123], "1,8": [0.1357, 0.027, 0.0234, 0.0067, 0.0116, -0.0075], "1,9": [0.2853, -0.12, 0.0699, -0.0218, 0.0054, 0.0279], "2,0": [0.2659, -0.3606, 0.0107, 0.0143, -0.014, 0.0019], "2,1": [0.2579, 0.2545, 0.0813, 0.0164, -0.0011, -0.0098], "2,2": [-0.1266, 0.3385, -0.019, 0.0117, -0.0029, 0.0062], "2,3": [-0.003, 0.3736, 0.0513, 0.0031, -0.0048, 0.0172], "2,4": [0.0767, 0.0714, -0.0287, -0.0002, 0.028, 0.0025], "2,5": [0.1435, 0.1238, 0.0412, 0.0197, 0.0322, -0.0043], "2,6": [0.2884, 0.1974, 0.0247, -0.0195, 0.0081, 0.0268], "2,7": [0.187, 0.1387, 0.0516, 0.0138, 0.015, -0.0002], "2,8": [-0.083, 0.1804, -0.0264, 0.0181, 0.0021, 0.0052], "2,9": [-0.1132, 0.0967, -0.0256, 0.015, -0.0094, -0.0002], "3,0": [0.252, 0.1651, 0.0866, -0.0135, -0.0222, -0.0003], "3,1": [-0.0742, 0.4574, 0.0053, 0.0048, -0.0181, 0.0125], "3,2": [0.2196, 0.0866, 0.0634, 0.0013, -0.0047, -0.0017], "3,3": [0.3835, 0.0308, 0.1066, -0.0057, -0.0201, 0.0168], "3,4": [-0.0301, 0.1489, 0.0203, -0.0013, 0.0031, 0.0184], "3,5": [0.2325, -0.0013, 0.0781, 0.0023, -0.0202, 0.0127], "3,6": [0.234, 0.0347, 0.0636, -0.004, -0.0479, 0.0074], "3,7": [-0.1641, 0.2026, -0.0564, 0.0141, -0.008, 0.0141], "3,8": [-0.013, 0.2793, 0.0096, 0.0034, 0.0034, 0.0075], "3,9": [0.4464, 0.2102, 0.1472, -0.0175, -0.019, 0.0301], "4,0": [0.0412, 0.2653, 0.0061, 0.0109, -0.0152, 0.0582], "5,0": [0.699, 0.5167, 0.2085, 0.0028, -0.0482, 0.0334], "5,1": [0.1675, 0.6522, 0.0672, 0.0311, -0.0391, 0.0643], "5,2": [0.3093, 0.7122, 0.091, 0.0345, 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"9,4": 5.0265, "9,5": 5.0265, "9,6": 5.0265, "10,0": 3.9794, "10,1": 3.9794, "10,2": 3.9794, "10,3": 3.9794, "10,4": 3.9794, "10,5": 3.9794, "10,6": 4.0841, "11,0": 4.3982, "11,1": 4.3982, "11,2": 4.1888, "11,3": 3.9794, "11,4": 3.6652, "11,5": 3.5605, "11,6": 3.4558, "12,0": 3.9794, "12,1": 3.9794, "12,2": 3.8746, "12,3": 3.6652, "12,4": 3.5605, "12,5": 3.5605, "12,6": 3.5605, "13,0": 4.0841, "13,1": 3.9794, "13,2": 3.8746, "13,3": 3.8746, "13,4": 3.8746, "13,5": 3.7699, "13,6": 3.5605, "14,0": 4.3982, "14,1": 4.5029, "14,2": 4.6077, "14,3": 4.3982, "14,4": 4.2935, "14,5": 4.1888, "14,6": 4.1888, "15,0": 4.3982, "15,1": 4.2935, "15,2": 4.3982, "15,3": 4.3982, "15,4": 4.3982, "15,5": 4.3982, "15,6": 4.3982, "15,7": 4.2935, "15,8": 4.2935, "15,9": 4.2935, "16,0": 1.5708, "16,1": 1.6755, "16,2": 1.7802, "16,3": 1.6755, "16,4": 1.5708, "16,5": 1.5708, "16,6": 1.3614, "17,0": 4.3982, "17,1": 4.2935, "17,2": 4.2935, "17,3": 4.2935, "17,4": 4.3982, "17,5": 4.5029, "17,6": 4.5029, "18,0": 3.9794, "18,1": 3.9794, "18,2": 3.9794, "18,3": 3.9794, "18,4": 3.9794, "18,5": 4.0841, "18,6": 4.1888, "19,0": 3.7699, "19,1": 3.351, "19,2": 3.0369, "19,3": 3.1416, "19,4": 3.4558, "19,5": 3.6652, "19,6": 3.7699, "20,0": 4.1888, "20,1": 4.1888, "20,2": 4.0841, "20,3": 3.9794, "20,4": 3.9794, "21,0": 4.2935, "21,1": 4.3982, "21,2": 4.5029, "21,3": 4.6077, "21,4": 4.8171, "21,5": 4.9218, "22,0": 4.1888, "22,1": 4.2935, "22,2": 4.2935, "22,3": 4.3982, "22,4": 4.6077, "22,5": 4.7124, "23,0": 5.236, "23,1": 5.236, "23,2": 5.236, "23,3": 5.236, "23,4": 5.236, "24,0": 5.3407, "24,1": 5.4454, "24,2": 5.5501, "24,3": 5.4454, "24,4": 5.3407, "25,0": 5.5501, "26,0": 5.4454, "26,1": 5.236, "26,2": 5.1313, "26,3": 4.9218, "26,4": 4.7124, "27,0": 3.6652, "27,1": 3.7699, "27,2": 3.8746, "27,3": 3.7699, "27,4": 3.7699, "28,0": 4.7124, "28,1": 4.8171, "28,2": 4.9218, "28,3": 4.9218, "28,4": 4.9218, "28,5": 5.0265, "28,6": 4.9218, "29,0": 5.236, "29,1": 5.236, "29,2": 5.3407, "29,3": 5.4454, "29,4": 5.236, "30,0": 3.7699, "30,1": 3.5605, "30,2": 3.4558, "30,3": 3.6652, "30,4": 3.7699, "31,0": 4.1888, "31,1": 4.1888, "31,2": 4.1888, "31,3": 4.1888, "31,4": 4.1888, "31,5": 4.1888, "31,6": 4.1888, "32,0": 4.3982, "32,1": 4.5029, "32,2": 4.6077, "32,3": 4.5029, "32,4": 4.3982, "33,0": 4.2935, "33,1": 4.1888, "33,2": 4.1888, "33,3": 4.0841, "33,4": 4.0841, "34,0": 4.6077, "34,1": 4.5029, "34,2": 4.3982, "34,3": 4.3982, "34,4": 4.3982}, "offsets": {"519": 0.1451, "526": 3.1655, "536": 2.8531, "583": 3.2287, "618": 6.032, "619": 3.1606, "620": 6.0062, "622": 6.1877, "623": 0.0375, "625": 6.1662, "627": 6.1272, "629": 2.9993, "630": 6.0571, "637": 0.0177, "639": 6.0996, "640": 3.1215, "642": 2.8107, "643": 6.0742, "931": 3.2279, "940": 3.1707, "952": 2.8607, "954": 2.934, "955": 0.2628, "959": 3.3215, "960": 3.0767, "961": 2.9879, "972": 2.3999}}}} \ No newline at end of file diff --git a/third_party/UO_Model3D_v13/pipeline/weapon_motion_add.py b/third_party/UO_Model3D_v13/pipeline/weapon_motion_add.py new file mode 100644 index 0000000..17d04c9 --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/weapon_motion_add.py @@ -0,0 +1,21 @@ +"""Put a class fitted by `weapon_fit.py class` into weapon_motion.json (the calibration the weapon bones of uo_weapon_bones.py are keyed from). + + python weapon_motion_add.py CLASS.json weapon_motion.json BONE PARENT +e.g. python weapon_motion_add.py class1h.json weapon_motion.json weapon1h.R hand.R +Entry: the bone sits at `pivot` (point of the class line nearest to the origin of the hand bone, hand space) and `dir` is the line; `anims` = extent (m along the +line, from the pivot) of every fitted weapon, `butt` = their median butt end (where uo_place_weapon.py puts the butt), `poses` = turn (rotation vector, rad) + +shift (m) in the hand axes for each (action, frame). +""" +import json, sys +import numpy as np + +cls, out, bone, parent = sys.argv[1:5] +C = json.load(open(cls)); R = C["rigid"] +p0 = np.array(R["p0"]); u = np.array(R["u"]); piv = p0 - u * (p0 @ u) +ex = {str(a): [round(float(x), 3) for x in e] for a, e in C["extents"].items()} +entry = dict(parent=parent, pivot=[round(float(x), 4) for x in piv], dir=[round(float(x), 4) for x in u], anims=ex, + chamfer={str(a): round(float(v), 2) for a, v in C["chamfer"].items()}, + poses={k: [round(float(x), 4) for x in v[0] + v[1]] for k, v in C["poses"].items()}, butt=round(float(np.median([e[0] for e in ex.values()])), 3)) +M = json.load(open(out)); M[bone] = entry +json.dump(M, open(out, "w"), separators=(",", ": ")) +print("%s: %d poses, butt %.3f m, chamfer %s" % (bone, len(entry["poses"]), entry["butt"], entry["chamfer"])) diff --git a/third_party/UO_Model3D_v13/pipeline/weapon_pose_export.py b/third_party/UO_Model3D_v13/pipeline/weapon_pose_export.py new file mode 100644 index 0000000..33b3b6a --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/weapon_pose_export.py @@ -0,0 +1,65 @@ +"""Export what the weapon calibration needs from the .blend: for each of the 210 UO poses and 5 directions, the world matrix of the hand +bones and the camera (world -> canvas pixels). Offline fits (weapon_fit.py) then run in numpy only. + + python weapon_pose_export.py ../model/UO_Body_0x190.blend OUT.npz [--canvas 256,256 --anchor 128,192] + +Writes: key (N,3) = (action, dir, frame); bones (names); BW (N,nb,4,4) world matrix of the pose bones in `bones`; PX (N,3,4) world -> pixels: +(x, y, depth) = PX @ (X, Y, Z, 1), x to the right and y down in canvas pixels (pixel (i, j) covers [i, i+1) x [j, j+1)). +""" +import sys, os +import numpy as np +import bpy + +STEP = 3 +BONES = ["hand.L", "hand.R", "forearm.L", "forearm.R", "shield.L"] + + +def main(): + args = sys.argv[1:] + blend, out = os.path.abspath(args.pop(0)), os.path.abspath(args.pop(0)) + CW, CH, CANCH = 256, 256, (128, 192) + while args: + a = args.pop(0) + if a == "--canvas": CW, CH = (int(x) for x in args.pop(0).split(",")) + elif a == "--anchor": CANCH = tuple(int(x) for x in args.pop(0).split(",")) + bpy.ops.wm.open_mainfile(filepath=blend) + sc = bpy.context.scene + rig = bpy.data.objects["UO_Rig"] + sc.camera = bpy.data.objects["UO_Camera"]; cd = sc.camera.data + cd.sensor_fit = "HORIZONTAL"; cd.ortho_scale = CW / sc.get("uo_px_per_m", 36.0); cd.shift_x = cd.shift_y = 0.0 + sc.render.resolution_x, sc.render.resolution_y, sc.render.resolution_percentage = CW, CH, 100 + + def cam_matrix(): + bpy.context.view_layer.update(); dg = bpy.context.evaluated_depsgraph_get(); cam = sc.camera.evaluated_get(dg) + return np.array(cam.calc_matrix_camera(dg, x=CW, y=CH)) @ np.array(cam.matrix_world.inverted()) + + def anchor_px(): + P = cam_matrix() @ np.array([0.0, 0.0, sc.get("uo_anchor_height", 0.07), 1.0]) + return np.array([(P[0] / P[3] + 1) * 0.5 * CW, (1 - P[1] / P[3]) * 0.5 * CH]) + + p0 = anchor_px(); cd.shift_x = cd.shift_y = 0.01; p1 = anchor_px(); k = (p1 - p0) / 0.01 + want = np.array(CANCH, float) + (np.array(sc.get("uo_anchor_px", (68.5, 86.0))) - np.array((68, 86))) + sh = (want - p0) / k; cd.shift_x, cd.shift_y = float(sh[0]), float(sh[1]) + assert np.abs(anchor_px() - want).max() < 1e-3 + bones = [b for b in BONES if b in rig.pose.bones] + acts = sorted([a for a in bpy.data.actions if "uo_action" in a], key=lambda a: int(a["uo_action"])) + keys, BW, PX = [], [], [] + for act in acts: + rig.animation_data.action = act + for d in range(5): + rig["uo_direction"] = d + for i in range(int(act["uo_frames"])): + sc.frame_set(1 + i * STEP); rig.update_tag(); bpy.context.view_layer.update() + M = cam_matrix(); Rw = np.array(rig.matrix_world) + assert np.abs(M[3] - [0, 0, 0, 1]).max() < 1e-9 # orthographic + # orthographic: w stays 1; pixel x = (ndc_x + 1) / 2 * CW, y = (1 - ndc_y) / 2 * CH, depth = -view z + V = np.array(sc.camera.evaluated_get(bpy.context.evaluated_depsgraph_get()).matrix_world.inverted()) + px = np.stack([(M[0] + M[3]) * 0.5 * CW, (M[3] - M[1]) * 0.5 * CH, -V[2]]) + keys.append((int(act["uo_action"]), d, i)); PX.append(px) + BW.append([Rw @ np.array(rig.pose.bones[b].matrix) for b in bones]) + print("action", act["uo_action"], "done", flush=True) + np.savez_compressed(out, key=np.array(keys), bones=np.array(bones), BW=np.array(BW), PX=np.array(PX), canvas=np.array([CW, CH]), anchor=np.array(CANCH)) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/weapon_roll_apply.py b/third_party/UO_Model3D_v13/pipeline/weapon_roll_apply.py new file mode 100644 index 0000000..96094ee --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/weapon_roll_apply.py @@ -0,0 +1,48 @@ +"""Write the measured roll of the weapon classes into weapon_motion.json (field "roll" of every class): + + python weapon_roll_apply.py ROLLDIR [--motion weapon_motion.json] + +roll = { "e1": reference vector in the hand frame (hand X without its part along the class line), "phi": {"action,frame": rad}, "ref": anim id of the +reference weapon, "offsets": {anim id: rad} } -- the head of a weapon lies in the plane spanned by the class line and Rot_line(phi + offset) e1 (the wide +side of the blade, the bit of an axe at +). uo_weapon_bones.py composes phi into the keyed turn of the weapon bone; uo_place_weapon.py turns a new weapon +about its shaft by the offset of the original weapon it should look like (REF_ANIM). Only weapons with a trustworthy offset are listed (class roll fits the +sprite clearly better than one fixed roll). +""" +import os, sys, json, glob +import numpy as np + +HERE = os.path.dirname(os.path.abspath(__file__)) + + +def e1_of(u): + u = np.array(u, float); u /= np.linalg.norm(u) + for x in ([1.0, 0, 0], [0, 1.0, 0]): + e = np.array(x) - (np.array(x) @ u) * u + if np.linalg.norm(e) > 0.3: + return (e / np.linalg.norm(e)).tolist() + + +def main(): + rolldir = sys.argv[1]; motion = os.path.join(HERE, "weapon_motion.json") + if "--motion" in sys.argv: + motion = sys.argv[sys.argv.index("--motion") + 1] + WM = json.load(open(motion)) + for f in sorted(glob.glob(os.path.join(rolldir, "roll_*.json"))): + R = json.load(open(f)); cls = R["cls"] + if len(R["core"]) < 3: # bows: no weapon with a measurable roll, the class roll fits worse than none + print(cls, "skipped: only", len(R["core"]), "weapon(s) with a measurable roll"); continue + offs = {} + for a, w in R["weapons"].items(): + if w.get("cls_mismatch") is None: + continue + gain = (w["class_const"] - w["cls_mismatch"]) / max(w["class_const"], 1e-9) + if gain >= 0.1 and w["chamfer"] <= 2.2: + offs[a] = round(float(np.deg2rad(w["delta_deg"])), 4) + WM[cls]["roll"] = dict(e1=[round(x, 5) for x in e1_of(WM[cls]["dir"])], ref=R["core"][0], + phi={k: round(float(np.deg2rad(v)), 4) for k, v in R["phi"].items()}, offsets=offs) + print(cls, "ref", R["core"][0], "roll for", len(R["phi"]), "poses, offsets for", len(offs), "weapons") + json.dump(WM, open(motion, "w")) + + +if __name__ == "__main__": + main() diff --git a/third_party/UO_Model3D_v13/pipeline/weapon_roll_fit.py b/third_party/UO_Model3D_v13/pipeline/weapon_roll_fit.py new file mode 100644 index 0000000..590b6af --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/weapon_roll_fit.py @@ -0,0 +1,150 @@ +"""Roll of every original weapon about its own axis (the turn of a blade / axe head about the shaft), measured from the sprites of anim..anim5. + + python weapon_roll_fit.py WP.npz VDROOT META.json CLASSIFY.json OUTDIR [--procs 4] [--classes polearm.L,axe2h.L,...] [--anims 611,612] + inputs: weapon_pose_export.py (WP.npz), mul2vd.py vd files (VDROOT//anim_.vd), META.json + CLASSIFY.json from weapon_classify.py + output: OUTDIR/roll_.json { phi: {"action,frame": degrees}, weapons: {anim id: {...}} }, OUTDIR/w_.pkl (per-weapon cache) + +Method (weapon_roll_lib.py): a weapon = shaft on the class line (weapon_motion.json) + a FLAT head T(s, u) (blade, axe head, spear leaf, bow limbs) that is +turned about the shaft by the roll phi. For each weapon the roll of every one of the 210 poses is found (all 5 directions share it) by (1) the projected +sprite area, (2) the side the head sticks out to, (3) alternating: learn the plate T as the cells that stay inside the sprite in 85% of the views, and +dynamic programming of the roll along each action (cost: pixels of the plate and the sprite further than 1 px from each other + smoothness). Weapons of one +class then share ONE roll per pose (it is the turn of the hand, our hand bone is only as good as the silhouette) and differ by a constant offset each. +""" +import os, sys, json, time, pickle +import numpy as np +from multiprocessing import Pool + +HERE = os.path.dirname(os.path.abspath(__file__)) +sys.path.insert(0, HERE) +import weapon_roll_lib as L # noqa: E402 + +NOT_WEAPON = { # held things that have their own bone / role: shields, books, lights + "shield": [576, 577, 578, 579, 580, 581, 582, 605, 992, 993, 1263, 1265, 1529, 1571], + "book": [877, 878, 879, 880, 882, 883, 884, 984, 1062], + "light": [500, 501, 502, 503, 504, 505, 1544, 1545, 1550], +} +SKIP = {a: k for k, v in NOT_WEAPON.items() for a in v} +INFO_MIN = 0.15 # (const - fit) / const: how much a per-pose roll helps over one fixed roll = how much roll there is to measure +TOL2_CHAMFER = 1.5 # px: from this class-line error on the tolerance of the comparison is 2 px instead of 1 px +CHAMFER_MAX = 2.2 # px: weapons whose class line is worse than this do not enter the class estimate + + +def load(args): + wp, vdroot, meta, aid = args + pose = _pose(wp); m = meta[str(aid)] + masks, _ = L.load_masks(pose, os.path.join(vdroot, m["file"], "anim_%04d.vd" % m["local"])) + return pose, masks + + +_POSE = {} +def _pose(wp): + if wp not in _POSE: + _POSE[wp] = L.Pose(wp) + return _POSE[wp] + + +def stage1(job): + wp, vdroot, meta, aid, cls, ext, outdir, tol = job + path = os.path.join(outdir, "w_%d.pkl" % aid) + if os.path.exists(path): + return pickle.load(open(path, "rb")) + t0 = time.time(); WM = json.load(open(os.path.join(HERE, "weapon_motion.json"))) + pose, masks = load((wp, vdroot, meta, aid)) + G = L.ClassGeom(pose, WM[cls], cls) + f = L.fit_single(pose, G, masks, ext, tol=tol) + cm, c0 = L.const_mismatch(f["P"], f["T"]) + res = dict(aid=aid, cls=cls, ext=ext, tol=tol, phi_pose=f["phi_pose"], T=f["T"], hist=f["hist"], const=cm, const_phi=c0, fit=f["hist"][-1] if f["hist"] else None, + area_rms=f["area_rms"], views=int(len(f["P"].ok)), sprite_area=float(f["P"].crop.reshape(len(f["P"].crop), -1).sum(1)[f["P"].ok].mean())) + pickle.dump(res, open(path, "wb")) + print("stage1 %d %s: const-roll %.1f -> per-pose %.1f px/view (%.0fs)" % (aid, cls, cm, res["fit"] or -1, time.time() - t0), flush=True) + return res + + +def stage3(job): + """a weapon against the class roll: offset by a local scan (plate re-learned), mismatch with the class roll""" + wp, vdroot, meta, aid, cls, phi_cls, res, outdir = job + WM = json.load(open(os.path.join(HERE, "weapon_motion.json"))) + pose, masks = load((wp, vdroot, meta, aid)) + G = L.ClassGeom(pose, WM[cls], cls); P = L.PlateFit(pose, G, masks, res["ext"], tol=res.get("tol", 1)); pk = L.pose_groups(pose, P.ok) + d0 = [res["phi_pose"][k] - phi_cls[k] for k in pk if k in phi_cls and k in res["phi_pose"]] + r1, r2 = abs(np.exp(1j * np.array(d0)).mean()), abs(np.exp(2j * np.array(d0)).mean()) + delta = L.circ_mean(np.exp(2j * np.array(d0))) / 2 if r1 < 0.8 * r2 else L.circ_mean(np.exp(1j * np.array(d0))) + best = None + for dd in np.deg2rad(np.arange(-12, 13, 6)): + pv = np.zeros(len(pose.key)) + for k, ns in pk.items(): + pv[ns] = phi_cls.get(k, 0.0) + delta + dd + T = P.learn(pv, thr=0.85)[0] + if len(T) < 5: + continue + mm = L.mismatch(P, T, pv) + if best is None or mm < best[0]: + best = (mm, delta + dd, T) + out = dict(res) + if best: + np.save(os.path.join(outdir, "cells_%d.npy" % aid), best[2].astype(np.float32)) + cm2, c2 = L.const_mismatch(P, best[2]) + out.update(class_mismatch=float(best[0]), delta=float(best[1]), consistency360=float(r1), consistency180=float(r2), class_const=cm2, const_abs=c2) + print("stage3 %d: class roll %.1f (const %.1f, own %.1f)" % (aid, out.get("class_mismatch", -1), res["const"], res["fit"] or -1), flush=True) + return out + + +if __name__ == "__main__": + a = sys.argv[1:] + wp, vdroot, metaf, clsf, outdir = a[:5] + procs = int(a[a.index("--procs") + 1]) if "--procs" in a else 4 + only_cls = a[a.index("--classes") + 1].split(",") if "--classes" in a else None + only = {int(x) for x in a[a.index("--anims") + 1].split(",")} if "--anims" in a else None + os.makedirs(outdir, exist_ok=True) + meta = json.load(open(metaf)); C = json.load(open(clsf)) + jobs = [] + for aid, c in sorted(C.items(), key=lambda kv: int(kv[0])): + aid = int(aid) + if aid in SKIP or (only and aid not in only): + continue + cls = c["best"] + if only_cls and cls not in only_cls: + continue + jobs.append((wp, vdroot, meta, aid, cls, tuple(c["classes"][cls]["extent"]), outdir, 2 if c["classes"][cls]["chamfer"] >= TOL2_CHAMFER else 1)) + print(len(jobs), "weapons") + with Pool(procs) as p: + res1 = p.map(stage1, jobs, chunksize=1) + by = {} + for r in res1: + by.setdefault(r["cls"], []).append(r) + pose = _pose(wp); WM = json.load(open(os.path.join(HERE, "weapon_motion.json"))) + for cls, lst in by.items(): + info = {r["aid"]: max(0.0, (r["const"] - r["fit"]) / r["const"]) if r["fit"] else 0.0 for r in lst} + cand = [r for r in lst if info[r["aid"]] >= INFO_MIN and C[str(r["aid"])]["classes"][cls]["chamfer"] <= CHAMFER_MAX] + if len(cand) < 2: + print(cls, "too few informative weapons", [(r["aid"], round(info[r["aid"]], 2)) for r in lst], flush=True) + continue + # reference = the weapon the others agree with most (full 360 deg: its head has a side, so the sign of the roll is known); core = those that + # agree with it mod 180 + def agree(r1, r2, m): + ks = sorted(set(r1["phi_pose"]) & set(r2["phi_pose"])); d = np.array([r1["phi_pose"][k] - r2["phi_pose"][k] for k in ks]) + return abs(np.exp(m * 1j * d).mean()) + score = [sum(info[o["aid"]] * agree(r, o, 1) for o in cand) for r in cand] + ref = cand[int(np.argmax(score))] + core = [ref] + sorted([r for r in cand if r is not ref and agree(ref, r, 2) >= 0.7], key=lambda r: -info[r["aid"]])[:9] + print(cls, "reference", ref["aid"], "core weapons:", [(r["aid"], round(info[r["aid"]], 2)) for r in core], flush=True) + G = L.ClassGeom(pose, WM[cls], cls); fits = [] + for r in core: + pose_, masks = load((wp, vdroot, meta, r["aid"])) + P = L.PlateFit(pose, G, masks, r["ext"], tol=r.get("tol", 1)); pk = L.pose_groups(pose, P.ok) + fits.append(dict(P=P, pk=pk, phi_pose=r["phi_pose"], aid=r["aid"])) + w = [info[r["aid"]] for r in core] + phi, delta, sym = L.merge_class(fits, weights=w, ref=0) + phi, delta, Ts = L.refine_class(pose, fits, phi, delta, log=print, weights=w) + print(cls, "core offsets (deg):", {f["aid"]: int(round(np.rad2deg(d))) for f, d in zip(fits, delta)}, flush=True) + jobs3 = [(wp, vdroot, meta, r["aid"], cls, phi, r, outdir) for r in lst] + with Pool(procs) as p: + res3 = p.map(stage3, jobs3, chunksize=1) + out = dict(cls=cls, core=[r["aid"] for r in core], + phi={"%d,%d" % k: float(np.rad2deg(v)) for k, v in sorted(phi.items())}, + weapons={str(r["aid"]): dict(name=meta[str(r["aid"])]["name"], chamfer=C[str(r["aid"])]["classes"][cls]["chamfer"], info=info[r["aid"]], + const=r["const"], own=r["fit"], cls_mismatch=r.get("class_mismatch"), class_const=r.get("class_const"), + const_abs_deg=float(np.rad2deg(r.get("const_abs", 0))) % 360, delta_deg=float(np.rad2deg(r.get("delta", 0))) % 360, + consistency360=r.get("consistency360"), consistency180=r.get("consistency180"), sprite_area=r["sprite_area"], + core=r["aid"] in [c_["aid"] for c_ in core]) for r in res3}) + json.dump(out, open(os.path.join(outdir, "roll_%s.json" % cls.replace(".", "_")), "w"), indent=1) diff --git a/third_party/UO_Model3D_v13/pipeline/weapon_roll_lib.py b/third_party/UO_Model3D_v13/pipeline/weapon_roll_lib.py new file mode 100644 index 0000000..518c55f --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/weapon_roll_lib.py @@ -0,0 +1,369 @@ +"""Roll of a weapon about its own axis, measured from the original sprites (anim.mul ... anim5.mul). + +A weapon is a shaft (the class line of weapon_motion.json, moved per pose by the class motion) with a head / blade that is NOT round: the flat of +a blade, an axe head, a halberd head. The shaft alone cannot show how the weapon is turned about itself; the projected AREA of the sprite can: a flat +blade whose normal points at the camera shows its full face, one turned edge-on shows only a sliver. This library loads the sprites + the exported poses +(weapon_pose_export.py) and gives, for any roll angle, the geometry of the weapon in every one of the 1050 views. +numpy / scipy only. +""" +import os, sys, json +import numpy as np + +HERE = os.path.dirname(os.path.abspath(__file__)) +sys.path.insert(0, os.path.join(HERE, "..", "vdtool")) +import vdtool # noqa: E402 + +CLASS_BONE = {"polearm.L": "hand.L", "axe2h.L": "hand.L", "bow.L": "hand.L", "weapon1h.R": "hand.R"} + + +def rodrigues(r): + r = np.asarray(r, float); a = np.linalg.norm(r) + if a < 1e-12: + return np.eye(3) + k = r / a; K = np.array([[0, -k[2], k[1]], [k[2], 0, -k[0]], [-k[1], k[0], 0]]) + return np.eye(3) + np.sin(a) * K + (1 - np.cos(a)) * K @ K + + +def axis_rot(u, phi): + return rodrigues(np.asarray(u, float) / np.linalg.norm(u) * phi) + + +class Pose: + """exported poses of the model: world matrices of the hand bones, camera, view directions""" + + def __init__(self, npz): + d = np.load(npz) + self.bones = [str(b) for b in d["bones"]]; self.key = d["key"]; self.BW = d["BW"]; self.PX = d["PX"] + self.W, self.H = (int(x) for x in d["canvas"]); self.anchor = tuple(int(x) for x in d["anchor"]) + v = self.PX[:, 2, :3]; self.view = v / np.linalg.norm(v, axis=1, keepdims=True) # world direction of looking (depth grows along it) + self.index = {(int(a), int(dd), int(i)): n for n, (a, dd, i) in enumerate(self.key)} + + def bone_world(self, bone): + M = self.BW[:, self.bones.index(bone)].copy() + M[:, :3, :3] /= np.linalg.norm(M[:, :3, :3], axis=1, keepdims=True) # without the pose scale (child bones inherit none) + return M + + +def load_masks(pose, vd_path, action_filter=None): + """sprite masks (and rgb) on the canvas of the poses for all (action, dir, frame) present; returns arrays aligned to pose.key (mask all-False if absent)""" + _, blocks = vdtool.read_vd(vd_path) + blk = {(b["action"], b["dir"]): b for b in blocks} + N = len(pose.key); masks = np.zeros((N, pose.H, pose.W), bool); rgb = np.zeros((N, pose.H, pose.W, 3), np.uint8) + ax, ay = pose.anchor + for n, (a, d, i) in enumerate(pose.key): + b = blk.get((int(a), int(d))) + if b is None or i >= len(b["frames"]): + continue + f = b["frames"][i]; r = vdtool.frame_rgba(f, b["palette"]); h, w = r.shape[:2] + x0, y0 = ax - f["cx"], ay - f["cy"] - f["h"] + ys, xs = slice(max(y0, 0), min(y0 + h, pose.H)), slice(max(x0, 0), min(x0 + w, pose.W)) + if ys.stop > ys.start and xs.stop > xs.start: + sub = r[ys.start - y0:ys.stop - y0, xs.start - x0:xs.stop - x0] + masks[n, ys, xs] = sub[..., 3] > 0; rgb[n, ys, xs] = sub[..., :3] + return masks, rgb + + +class ClassGeom: + """class line + per-pose motion of weapon_motion.json: for every view the weapon frame (rotation, origin) in world""" + + def __init__(self, pose, wm, bone): + self.bone = bone; self.pose = pose + self.piv = np.array(wm["pivot"], float); self.u = np.array(wm["dir"], float); self.u /= np.linalg.norm(self.u) + self.M = pose.bone_world(CLASS_BONE[bone]) + # reference frame perpendicular to the axis: e1 = hand-local X without its axis part (fixed in the bone frame, so roll 0 is a bone-frame notion) + x = np.array([1.0, 0, 0]); e1 = x - (x @ self.u) * self.u + if np.linalg.norm(e1) < 0.3: + x = np.array([0, 1.0, 0]); e1 = x - (x @ self.u) * self.u + self.e1 = e1 / np.linalg.norm(e1); self.e2 = np.cross(self.u, self.e1) + N = len(pose.key) + self.R = np.zeros((N, 3, 3)); self.t = np.zeros((N, 3)) + for n, (a, d, i) in enumerate(pose.key): + p = wm["poses"].get("%d,%d" % (a, i), [0] * 6) + self.R[n] = rodrigues(p[:3]); self.t[n] = p[3:] + # axis in world + Rb = self.M[:, :3, :3] @ self.R # bone frame -> world, with the pose turn + self.Rw = Rb # weapon frame (before extra roll) -> world: columns Rb@e1_0 .. + self.d_w = Rb @ self.u # axis direction in world (N,3) + self.o_w = np.einsum("nij,nj->ni", self.M[:, :3, :3], self.piv + self.t) + self.M[:, :3, 3] # point of the axis (the pivot) in world + + def uv(self, phi): + """world directions of the in-plane (u) and normal (v) vectors of a flat head rolled by phi (N,) or scalar, about the axis""" + phi = np.broadcast_to(np.asarray(phi, float), (len(self.d_w),)) + c, s = np.cos(phi)[:, None], np.sin(phi)[:, None] + e1 = self.Rw @ self.e1; e2 = self.Rw @ self.e2 + return c * e1 + s * e2, -s * e1 + c * e2 + + def project_vec(self, vec): + """image 2-vector of world directions vec (N,3)""" + return np.einsum("nij,nj->ni", self.pose.PX[:, :2, :3], vec) + + +# --------------------------------------------------------------------------------------------------------------------------------------------- +# planar head model: the head / blade is a flat plate T(s, u) (s along the shaft, u across, both in m) turned about the shaft by phi +# --------------------------------------------------------------------------------------------------------------------------------------------- +from scipy import ndimage # noqa: E402 + +WIN = 128 # half... full size of the crop window per view (px) + + +class PlateFit: + """all views of one weapon (sprite masks cropped to windows) + the class geometry; learns the plate T for given rolls and scores rolls""" + + def __init__(self, pose, G, masks, ext, step=0.015, umax=0.36, tol=1): + self.pose, self.G, self.tol = pose, G, tol + area = masks.reshape(len(masks), -1).sum(1) + self.ok = np.nonzero(area > 5)[0]; ok = self.ok; n = len(ok) + Lm = pose.PX[:, :2, :3]; c0 = pose.PX[:, :2, 3] + self.c = np.einsum("nij,nj->ni", Lm, G.o_w) + c0 # pixel of the pivot point on the axis (N,2) + self.a = np.einsum("nij,nj->ni", Lm, G.d_w) # px per m along the axis + self.B1 = np.einsum("nij,nj->ni", Lm, G.Rw @ G.e1); self.B2 = np.einsum("nij,nj->ni", Lm, G.Rw @ G.e2) + # window per view: centred on the sprite + self.org = np.zeros((len(masks), 2), int); self.crop = np.zeros((len(masks), WIN, WIN), bool); self.dil = np.zeros((len(masks), WIN, WIN), bool) + for k in ok: + ys, xs = np.nonzero(masks[k]); cy, cx = int(ys.mean()), int(xs.mean()) + y0, x0 = cy - WIN // 2, cx - WIN // 2; self.org[k] = (x0, y0) + m = np.zeros((WIN, WIN), bool) + yy0, xx0 = max(y0, 0), max(x0, 0); yy1, xx1 = min(y0 + WIN, masks.shape[1]), min(x0 + WIN, masks.shape[2]) + m[yy0 - y0:yy1 - y0, xx0 - x0:xx1 - x0] = masks[k, yy0:yy1, xx0:xx1] + self.crop[k] = m; self.dil[k] = ndimage.binary_dilation(m, np.ones((2 * tol + 1, 2 * tol + 1), bool)) + self.step = step + s_lo, s_hi = ext + self.sg = np.arange(s_lo - 0.08, s_hi + 0.08, step); self.ug = np.arange(-umax, umax + 1e-9, step) + S, U = np.meshgrid(self.sg, self.ug, indexing="ij"); self.cells = np.stack([S.ravel(), U.ravel()], 1) # (nc, 2) + + def points(self, k_idx, cells, phi): + """pixel coordinates (n_views, n_cells, 2) in the crop windows of views k_idx for cells (nc,2) at roll phi (scalar or (n_views,))""" + phi = np.broadcast_to(np.asarray(phi, float), (len(k_idx),)) + c, s = np.cos(phi)[:, None], np.sin(phi)[:, None] + b = c * self.B1[k_idx] + s * self.B2[k_idx] # (n,2) px per m across, in the plate plane + x = self.c[k_idx][:, None, :] + cells[None, :, 0:1] * self.a[k_idx][:, None, :] + cells[None, :, 1:2] * b[:, None, :] + return x - self.org[k_idx][:, None, :] + + def learn(self, phis, thr=0.75, k_idx=None, dilate=True): + """plate = cells whose pixel lies in the (3x3 dilated) sprite in at least `thr` of the views; phis: roll per view (N,) (any array indexed by view)""" + k_idx = self.ok if k_idx is None else k_idx + hit = np.zeros(len(self.cells)) + for k in k_idx: + p = self.points(np.array([k]), self.cells, phis[k])[0] + xi = np.floor(p[:, 0]).astype(int); yi = np.floor(p[:, 1]).astype(int) + inside = (xi >= 0) & (xi < WIN) & (yi >= 0) & (yi < WIN) + h = np.zeros(len(self.cells), bool); h[inside] = (self.dil if dilate else self.crop)[k][yi[inside], xi[inside]] + hit += h + score = hit / len(k_idx) + return self.cells[score >= thr], score + + def cost(self, k_idx, T, phi_cands, tol=True): + """pixel count of the mismatch between the splatted plate T and the sprite, per view and candidate roll: (n_views, n_cand). + tol: a pixel only counts when it is more than 1 px (3x3) away from the other mask (the class line is only good to ~1 px)""" + out = np.zeros((len(k_idx), len(phi_cands))) + for j, k in enumerate(k_idx): + p = self.points(np.full(len(phi_cands), k), T, phi_cands) # (nphi, nT, 2) + xi = np.floor(p[..., 0]).astype(int); yi = np.floor(p[..., 1]).astype(int) + inside = (xi >= 0) & (xi < WIN) & (yi >= 0) & (yi < WIN) + img = np.zeros((len(phi_cands), WIN * WIN), bool) + ph = np.broadcast_to(np.arange(len(phi_cands))[:, None], xi.shape) + img[ph[inside], (yi * WIN + xi)[inside]] = True + if not tol: + out[j] = (img ^ self.crop[k].ravel()[None]).sum(1) + continue + im = img.reshape(-1, WIN, WIN); e = im + for _ in range(self.tol): # dilate the splat by tol px (square) + d = e.copy(); d[:, 1:] |= e[:, :-1]; d[:, :-1] |= e[:, 1:] + e = d.copy(); e[:, :, 1:] |= d[:, :, :-1]; e[:, :, :-1] |= d[:, :, 1:] + out[j] = (im & ~self.dil[k][None]).sum((1, 2)) + (self.crop[k][None] & ~e).sum((1, 2)) + return out + + +# --------------------------------------------------------------------------------------------------------------------------------------------- +def area_init(pose, G, masks): + """roll of every pose from the projected sprite area alone: area ~ c0 + Ap |n.view| + Ae |u.view| (plate normal / in-plane vector), mod 180 deg. + Alternates between per-pose roll (grid) and the 3 coefficients; returns {(action, frame): phi} (rad, [0, pi)) and the rms error (px)""" + from scipy.optimize import nnls + area = masks.reshape(len(masks), -1).sum(1).astype(float); ok = area > 5; v = pose.view + grid = np.deg2rad(np.arange(0, 180, 3.0)); F = [] + for ph in grid: + eu, ev = G.uv(ph); F.append(np.stack([np.abs((ev * v).sum(1)), np.abs((eu * v).sum(1))], 1)) + F = np.array(F) + pk = {} + for n, (a, d, i) in enumerate(pose.key): + if ok[n]: + pk.setdefault((int(a), int(i)), []).append(n) + best = None + for seed in range(8): + rng = np.random.default_rng(seed); coef = np.array([area[ok].min(), rng.uniform(20, 200), rng.uniform(20, 200)]); idx = {} + for it in range(6): + for k, ns in pk.items(): + err = ((coef[0] + F[:, ns, 0] * coef[1] + F[:, ns, 1] * coef[2] - area[ns]) ** 2).sum(1); idx[k] = err.argmin() + rows = np.array([[1, F[idx[k], n, 0], F[idx[k], n, 1]] for k, ns in pk.items() for n in ns]); ys = np.array([area[n] for ns in pk.values() for n in ns]) + coef, _ = nnls(rows, ys) + rms = np.sqrt(((rows @ coef - ys) ** 2).mean()) + if best is None or rms < best[0]: + best = (rms, dict(idx), coef) + rms, idx, coef = best + return {k: float(grid[j]) for k, j in idx.items()}, float(rms), coef + + +def head_offset_sign(P, phi_view, s_head): + """sign cue for the 180 deg ambiguity: observed offset of the sprite's head part from the shaft line (px, along the image normal of the axis) + times the predicted normal component of the in-plane vector; returns q (N,): > 0 means 'phi as given', < 0 means 'phi + 180'""" + q = np.zeros(len(P.pose.key)) + for k in P.ok: + ys, xs = np.nonzero(P.crop[k]); X = np.stack([xs + 0.5, ys + 0.5], 1) + a = P.a[k]; na = np.linalg.norm(a) + if na < 1e-6: + continue + t = a / na; nrm = np.array([-t[1], t[0]]) + rel = X + P.org[k] - P.c[k]; sig = rel @ t; nu = rel @ nrm + head = sig > s_head * na + if head.sum() < 3: + continue + b = np.cos(phi_view[k]) * P.B1[k] + np.sin(phi_view[k]) * P.B2[k] + q[k] = nu[head].mean() * (b @ nrm) + return q + + +def viterbi(U, lam, cands): + """best path through per-frame costs U (nf, nc) with a quadratic cost lam * (angle change / 30 deg)^2 between consecutive frames""" + nf, nc = U.shape + d = np.angle(np.exp(1j * (cands[:, None] - cands[None, :]))) + Tr = lam * (d / np.deg2rad(30.0)) ** 2 + cost = U[0].copy(); back = np.zeros((nf, nc), int) + for f in range(1, nf): + tot = cost[None, :] + Tr; back[f] = tot.argmin(1); cost = tot.min(1) + U[f] + path = np.zeros(nf, int); path[-1] = cost.argmin() + for f in range(nf - 1, 0, -1): + path[f - 1] = back[f][path[f]] + return path + + +# --------------------------------------------------------------------------------------------------------------------------------------------- +CANDS = np.deg2rad(np.arange(0, 360, 6.0)) # roll candidates (rad) + + +def pose_groups(pose, ok): + """{(action, frame): [view indices of the 5 directions that have a sprite]}""" + okset = set(int(x) for x in ok); pk = {} + for n, (a, d, i) in enumerate(pose.key): + if n in okset: + pk.setdefault((int(a), int(i)), []).append(n) + return pk + + +def dp_rolls(P, pk, T_list, deltas, smooth=0.25, cands=CANDS, weights=None): + """roll per pose by dynamic programming along every action: sum over weapons w of the mismatch of plate T_w at roll (candidate + delta_w), + plus a quadratic penalty on the roll change between consecutive frames. P, T_list, deltas: one entry per weapon; pk per weapon (same keys needed + only for the union). Returns {(a, i): roll}, total cost, and the unary cost tensor {(a,i): (nc,)}""" + keys = sorted({k for p in pk for k in p}); out = {}; tot = 0.0; unary = {} + weights = weights or [1.0] * len(P) + for a in sorted({k[0] for k in keys}): + fr = sorted(i for (aa, i) in keys if aa == a) + U = np.zeros((len(fr), len(cands))) + for f, i in enumerate(fr): + for w in range(len(P)): + ns = pk[w].get((a, i)) + if ns: + U[f] += weights[w] * P[w].cost(np.array(ns), T_list[w], cands + deltas[w]).sum(0) + unary[(a, i)] = U[f] + lam = smooth * np.median(U.max(1) - U.min(1)) + path = viterbi(U, lam, cands) + for f, i in enumerate(fr): + out[(a, i)] = float(cands[path[f]]); tot += U[f, path[f]] + return out, tot, unary + + +def fit_single(pose, G, masks, ext, iters=4, smooth=0.25, thr=0.85, log=None, sign=True, tol=1): + """roll per pose of ONE weapon on the class geometry G: area init (mod 180) -> sign from the head offset -> alternate plate learning and dynamic + programming. Returns dict(P, T, pk, phi_pose, phi_view, cost_hist, area_rms)""" + P = PlateFit(pose, G, masks, ext, tol=tol); pk = pose_groups(pose, P.ok) + phiA, rms, coef = area_init(pose, G, masks) + phi = np.zeros(len(pose.key)) + for k, ns in pk.items(): + phi[ns] = phiA[k] + if sign: + q = head_offset_sign(P, phi, ext[0] + 0.6 * (ext[1] - ext[0])) + for k, ns in pk.items(): + if q[ns].sum() < 0: + phi[ns] += np.pi + hist = []; T = None + for it in range(iters): + T, _ = P.learn(phi, thr=thr) + if len(T) < 5: + break + pr, tot, _ = dp_rolls([P], [pk], [T], [0.0], smooth=smooth) + for k, v in pr.items(): + phi[pk[k]] = v + hist.append(tot / len(P.ok)) + if log: log(" it %d: plate cells %d, mismatch px/view %.1f" % (it, len(T), hist[-1])) + return dict(P=P, T=T, pk=pk, phi_view=phi, phi_pose={k: float(phi[ns[0]]) for k, ns in pk.items()}, hist=hist, area_rms=rms) + + +def mismatch(P, T, phi_view, per_view=False): + """mean tolerant mismatch (px per view) of plate T at the given roll per view (N,)""" + out = np.zeros(len(P.ok)) + for j, k in enumerate(P.ok): + out[j] = P.cost(np.array([k]), T, np.array([phi_view[k]]))[0, 0] + return out if per_view else float(out.mean()) + + +def const_mismatch(P, T, cands=CANDS): + """best single roll for all views (a weapon rolled by one fixed angle in the class frame): (mismatch px/view, angle)""" + tot = np.zeros(len(cands)) + for k in P.ok: + tot += P.cost(np.array([k]), T, cands)[0] + j = tot.argmin() + return float(tot[j] / len(P.ok)), float(cands[j]) + + +def circ_mean(z): + return float(np.angle(np.sum(z))) + + +def merge_class(fits, weights=None, iters=6, ref=None): + """one roll per pose for the class + one offset per weapon from independent per-weapon rolls (each only known up to its own constant offset, and + mod 180 where the head is symmetric). Returns phi_pose {(a,i): rad}, delta [rad per weapon] (weapon roll = class roll + delta), sym [bool per weapon]""" + nw = len(fits); weights = weights or [1.0] * nw + keys = sorted(set().union(*[f["phi_pose"].keys() for f in fits])) + ref = int(np.argmax(weights)) if ref is None else ref + phi = dict(fits[ref]["phi_pose"]); delta = np.zeros(nw); sym = [False] * nw + for it in range(iters): + for w, f in enumerate(fits): + if w == ref: + continue + common = [k for k in f["phi_pose"] if k in phi] + d = np.array([f["phi_pose"][k] - phi[k] for k in common]) + r1, r2 = abs(np.exp(1j * d).mean()), abs(np.exp(2j * d).mean()) + sym[w] = bool(r1 < 0.8 * r2) # symmetric head: only the 180 deg estimate means anything + delta[w] = circ_mean(np.exp(2j * d)) / 2 if sym[w] else circ_mean(np.exp(1j * d)) + new = {} + for k in keys: + z = 0j + for w, f in enumerate(fits): + if k in f["phi_pose"]: + a = f["phi_pose"][k] - delta[w] + if sym[w] and k in phi and np.cos(a - phi[k]) < 0: + a += np.pi + z += weights[w] * np.exp(1j * a) + new[k] = float(np.angle(z)) if abs(z) > 0 else phi.get(k, 0.0) + phi = new + return phi, delta, sym + + +def refine_class(pose, fits, phi, delta, iters=3, smooth=0.25, thr=0.85, log=None, weights=None): + """all weapons of a class together: learn each plate at (class roll + offset), roll per pose by dynamic programming over the summed mismatch of all + weapons, offsets by a scan; delta snaps to the 6 deg grid""" + Ps = [f["P"] for f in fits]; pks = [f["pk"] for f in fits]; delta = np.array([round(d / np.deg2rad(6)) * np.deg2rad(6) for d in delta]) + for it in range(iters): + Ts = [] + for w, f in enumerate(fits): + pv = np.zeros(len(pose.key)) + for k, ns in pks[w].items(): + pv[ns] = phi[k] + delta[w] + Ts.append(Ps[w].learn(pv, thr=thr)[0]) + phi, tot, unary = dp_rolls(Ps, pks, Ts, delta, smooth=smooth, weights=weights) + for w, f in enumerate(fits): # offset scan: weapon w's mismatch at phi_p + delta' for delta' on the grid + cost = np.zeros(len(CANDS)) + for k, ns in pks[w].items(): + cost += Ps[w].cost(np.array(ns), Ts[w], phi[k] + CANDS).sum(0) + delta[w] = CANDS[cost.argmin()] if w != 0 else delta[w] + if log: log(" class iteration %d: total mismatch %.1f px/view-weapon, offsets %s deg" % (it, tot / sum(len(P.ok) for P in Ps), np.round(np.rad2deg(delta)).astype(int))) + return phi, delta, Ts diff --git a/third_party/UO_Model3D_v13/pipeline/zoom.py b/third_party/UO_Model3D_v13/pipeline/zoom.py new file mode 100644 index 0000000..ea44e6d --- /dev/null +++ b/third_party/UO_Model3D_v13/pipeline/zoom.py @@ -0,0 +1,22 @@ +"""zoom.py poses.pkl a i out.png : row 1 = sprite (5 dirs), row 2 = overlay (grey both, red sprite only, blue model only)""" +import sys, pickle, numpy as np, jax.numpy as jnp +from PIL import Image +from posefit_mesh import * +from posefit_mesh import _posed_j +P = pickle.load(open(sys.argv[1], "rb")); a, i = int(sys.argv[2]), int(sys.argv[3]); out = sys.argv[4] +T = targets(a); m = T[..., 3] > 127; F = len(T) +hid = (horse_masks(a, F) & ~m) if a in HORSE_OF else np.zeros_like(m) +X = _posed_j({k: jnp.asarray(v[i]) for k, v in P[a]["poses"].items()}) +ys, xs = np.nonzero(m[i].any(0)); y0, y1, x0, x1 = max(ys.min() - 5, 0), min(ys.max() + 6, 120), max(xs.min() - 5, 0), min(xs.max() + 6, 136) +top, bot = [], [] +for d in range(5): + s = T[i, d].astype(float); bg = np.array([40, 40, 48.0]); al = s[..., 3:4] / 255 + top.append((bg * (1 - al) + s[..., :3] * al)[y0:y1, x0:x1]) + mk = raster_vec(np.asarray(project(X, d))[tris], CANVAS_W, CANVAS_H) & ~hid[i, d] + img = np.full((120, 136, 3), 30.0); img[hid[i, d]] = (70, 55, 40) + img[mk & m[i, d]] = 200; img[m[i, d] & ~mk] = (230, 60, 60); img[mk & ~m[i, d]] = (70, 120, 255) + bot.append(img[y0:y1, x0:x1]) +sep = np.full((y1 - y0, 2, 3), 90.0) +row = lambda L: np.concatenate(sum([[x, sep] for x in L], [])[:-1], 1) +im = Image.fromarray(np.concatenate([row(top), np.full((2, row(top).shape[1], 3), 90.0), row(bot)], 0).astype(np.uint8)) +im.resize((im.width * 4, im.height * 4), Image.NEAREST).save(out) diff --git a/third_party/UO_Model3D_v13/provenance.json b/third_party/UO_Model3D_v13/provenance.json new file mode 100644 index 0000000..4957f6d --- /dev/null +++ b/third_party/UO_Model3D_v13/provenance.json @@ -0,0 +1,11 @@ +{ + "model": "UO_Model3D v13", + "artist": "Levy", + "license": "shared with permission of the artist (Levy)", + "note": "UO_Body_0x190.blend is the stripped copy: the packed original client frame atlas is removed (pipeline/strip_originals.py).", + "files": { + "model/UO_Body_0x190.blend": "9ff8c601431157943d735b358c9a1fbcb42c713c5b618c8cb01f7ff46a8a63f4", + "model/UO_Body_0x190.fbx": "5ae555aba7ce45cb52c6e37e602998a4a82ca496e224464dbfc7b348233dc9af", + "model/UO_Body_0x190.glb": "802ab9f1fefbdfba135b8d69f6c756a632d4e87f25b5a8462f9274c56a6189d2" + } +} diff --git a/third_party/UO_Model3D_v13/vdtool/mul2vd.py b/third_party/UO_Model3D_v13/vdtool/mul2vd.py new file mode 100644 index 0000000..b3c140a --- /dev/null +++ b/third_party/UO_Model3D_v13/vdtool/mul2vd.py @@ -0,0 +1,37 @@ +"""Extract one animation (body / equipment id) from anim.idx + anim.mul into a .vd file (UOFiddler VD layout).""" +import struct, sys, os + +def base_index(body): + if body < 200: + return body * 110, 22, 0 # high detail monster (22 actions), vd type 0 + if body < 400: + return 22000 + (body - 200) * 65, 13, 1 # low detail / animal (13 actions), vd type 1 + return 35000 + (body - 400) * 175, 35, 2 # people and equipment (35 actions), vd type 2 + +def extract(idx_path, mul_path, body, out): + idx = open(idx_path, "rb").read() + base, n_act, vtype = base_index(body) + entries = [struct.unpack_from(" liczba akcji (high / low / people) +TYPE_NAMES = {0: "high (potwory)", 1: "low (zwierzeta)", 2: "people (ludzie/ekwipunek)"} +PEOPLE_ACTIONS = [ + "walk_unarmed", "walk_armed", "run_unarmed", "run_armed", "stand", "fidget_1", "fidget_2", + "combat_idle_1h", "combat_idle_2h", "attack_1h_slash", "attack_1h_pierce", "attack_1h_bash", + "attack_2h_bash", "attack_2h_slash", "attack_2h_pierce", "combat_advance", "spell_directed", + "spell_area", "attack_bow", "attack_crossbow", "get_hit", "die_forward", "die_backward", + "mounted_walk", "mounted_run", "mounted_stand", "mounted_attack_1h", "mounted_attack_bow", + "mounted_attack_crossbow", "mounted_attack_2h", "block", "punch", "bow", "salute", "eat"] +END = 0x7FFF7FFF +CANVAS_MARGIN = 8 + + +# ----------------------------------------------------------------------------- kolory +def c15_to_rgb(c): + return (((c >> 10) & 31) * 255 // 31, ((c >> 5) & 31) * 255 // 31, (c & 31) * 255 // 31) + + +def rgb_to_c15(rgb): + """rgb: (...,3) uint8 -> (...,) uint16 w formacie 1-5-5-5 (bez bitu alfa).""" + rgb = np.asarray(rgb, np.int32) + r, g, b = [(rgb[..., i] * 31 + 127) // 255 for i in range(3)] + c = (r << 10) | (g << 5) | b + return np.where(c == 0, 1, c).astype(np.uint16) # 0x0000 = przezroczystosc w kliencie -> prawie czarny + + +# ----------------------------------------------------------------------------- odczyt +def action_name(anim_type, a): + if anim_type == 2 and a < len(PEOPLE_ACTIONS): + return PEOPLE_ACTIONS[a] + return "action" + + +def read_vd(path): + d = open(path, "rb").read() + magic, anim_type = struct.unpack_from(" 0 and length > 0: + pal = list(struct.unpack_from("<256H", d, lookup)) + start = lookup + 512 + (fc,) = struct.unpack_from("> 22) & 0x3FF + dy = (hdr >> 12) & 0x3FF + dx = dx - 0x400 if dx & 0x200 else dx + dy = dy - 0x400 if dy & 0x200 else dy + x, y = cx + dx, cy + h + dy + run = np.frombuffer(d, np.uint8, n, p) + if 0 <= y < idx.shape[0]: # a few client frames have runs past + x0, x1 = max(x, 0), min(x + n, idx.shape[1]) # their declared size: clip them + if x1 > x0: + idx[y, x0:x1] = run[x0 - x:x1 - x] + p += n + frames.append(dict(cx=cx, cy=cy, w=w, h=h, idx=idx)) + blk["palette"] = [v & 0x7FFF for v in pal] + blk["frames"] = frames + blocks.append(blk) + return anim_type, blocks + + +def frame_rgba(frame, palette): + idx = frame["idx"] + rgba = np.zeros(idx.shape + (4,), np.uint8) + lut = np.array([c15_to_rgb(c) for c in palette], np.uint8) + m = idx >= 0 + rgba[m, :3] = lut[idx[m]] + rgba[m, 3] = 255 + return rgba[: frame["h"], : frame["w"]] + + +# ----------------------------------------------------------------------------- zapis +def encode_frame(idx, cx, cy): + """idx: (h,w) int16, -1 = przezroczysty. Zwraca bajty ramki (naglowek + RLE + terminator).""" + h, w = idx.shape + out = bytearray(struct.pack("= 0 and x - x0 < 0xFFF: + x += 1 + dx = (x0 - cx) & 0x3FF + dy = (y - cy - h) & 0x3FF + out += struct.pack("= 128 for im in images] + c15 = [rgb_to_c15(im[..., :3]) for im in images] + used = np.unique(np.concatenate([c[m] for c, m in zip(c15, masks)] + [np.zeros(0, np.uint16)])) + if original is not None and set(used.tolist()) <= set(original): + palette = list(original) # niezmienione kolory -> ta sama paleta co w oryginale + elif len(used) <= 256: + palette = used.tolist() + [0] * (256 - len(used)) + else: # >256 kolorow: kwantyzacja wspolna dla calego bloku + opaque = np.concatenate([im[m][:, :3] for im, m in zip(images, masks)]) + side = int(np.ceil(np.sqrt(len(opaque)))) + tile = np.zeros((side * side, 3), np.uint8) + tile[: len(opaque)] = opaque + q = Image.fromarray(tile.reshape(side, side, 3)).quantize(256, method=Image.Quantize.MEDIANCUT, + dither=Image.Dither.NONE) + pal_rgb = np.array(q.getpalette()[: 256 * 3], np.uint8).reshape(-1, 3) + palette = np.unique(rgb_to_c15(pal_rgb)).tolist() + palette += [0] * (256 - len(palette)) + print(f" uwaga: {len(used)} kolorow w bloku -> zredukowano do {len([c for c in palette if c])}") + pal_arr = np.array(palette, np.int64) + pal_rgb = np.array([c15_to_rgb(c) for c in palette], np.int64) + lookup = {c: i for i, c in reversed(list(enumerate(palette))) if c} + idx_maps = [] + for im, c, m in zip(images, c15, masks): + idx = np.full(m.shape, -1, np.int16) + cc = c[m] + direct = np.array([lookup.get(int(v), -1) for v in cc], np.int16) + miss = direct < 0 + if miss.any(): # najblizszy kolor palety + src = im[m][miss][:, :3].astype(np.int64) + valid = pal_arr > 0 + dist = ((src[:, None, :] - pal_rgb[None, valid, :]) ** 2).sum(-1) + direct[miss] = np.nonzero(valid)[0][dist.argmin(1)] + idx[m] = direct + idx_maps.append(idx) + return palette, idx_maps + + +def write_vd(path, anim_type, blocks): + """blocks: lista (w kolejnosci akcja*5+kierunek) dict(palette, frames=[dict(cx,cy,idx)]) lub None.""" + n = len(blocks) + head = bytearray(struct.pack("= 128 + if not m.any(): + imgs.append(np.zeros((1, 1, 4), np.uint8)); centers.append((0, -1)) # pusta klatka 1x1 + continue + ys, xs = np.nonzero(m) + y0, y1, x0, x1 = ys.min(), ys.max() + 1, xs.min(), xs.max() + 1 + crop = im[y0:y1, x0:x1] + h = y1 - y0 + imgs.append(crop); centers.append((int(ax - x0), int((ay - y0) - h))) + if not imgs: + blocks.append(None) + continue + palette, idx_maps = build_palette(imgs, e.get("palette")) + blocks.append(dict(palette=palette, + frames=[dict(cx=c[0], cy=c[1], idx=ix) for c, ix in zip(centers, idx_maps)])) + n_act = meta["actions"] + for a in range(n_act): + counts = [len(blocks[a * 5 + d]["frames"]) if blocks[a * 5 + d] else 0 for d in range(5)] + if len(set(counts)) > 1: + warn += 1 + print(f" uwaga: akcja {a} ma rozna liczbe klatek w kierunkach: {counts}") + write_vd(out, anim_type, blocks) + print(f"zapisano {out}" + (f" ({warn} ostrzezen)" if warn else "")) + + +def cmd_verify(p1, p2): + t1, b1 = read_vd(p1) + t2, b2 = read_vd(p2) + if t1 != t2 or len(b1) != len(b2): + print("ROZNE: typ lub liczba blokow"); return 1 + diff = 0 + for x, y in zip(b1, b2): + if len(x["frames"]) != len(y["frames"]): + print(f" akcja {x['action']} kier. {x['dir']}: liczba klatek {len(x['frames'])} vs {len(y['frames'])}") + diff += 1; continue + for i, (f, g) in enumerate(zip(x["frames"], y["frames"])): + A, B = frame_rgba(f, x["palette"]), frame_rgba(g, y["palette"]) + ax_, ay_ = f["cx"], f["cy"] + f["h"] + bx_, by_ = g["cx"], g["cy"] + g["h"] + # porownanie po wyrownaniu do punktu zaczepienia + W = max(ax_, bx_) + max(f["w"] - ax_, g["w"] - bx_) + H = max(ay_, by_) + max(f["h"] - ay_, g["h"] - by_) + ca = np.zeros((H, W, 4), np.uint8); cb = ca.copy() + ox, oy = max(ax_, bx_), max(ay_, by_) + ca[oy - ay_:oy - ay_ + f["h"], ox - ax_:ox - ax_ + f["w"]] = A + cb[oy - by_:oy - by_ + g["h"], ox - bx_:ox - bx_ + g["w"]] = B + if not np.array_equal(ca, cb): + diff += 1 + print(f" akcja {x['action']} kier. {x['dir']} klatka {i}: piksele sie roznia") + same_bytes = open(p1, "rb").read() == open(p2, "rb").read() + print("IDENTYCZNE BAJT W BAJT" if same_bytes else ("OBRAZ IDENTYCZNY (inne kodowanie)" if not diff else f"ROZNIC: {diff}")) + return 0 if not diff else 1 + + +def main(argv): + if len(argv) < 3 or argv[1] not in ("info", "extract", "pack", "verify"): + print(__doc__); return 2 + cmd = argv[1] + if cmd == "info": + cmd_info(argv[2]) + elif cmd == "extract": + cmd_extract(argv[2], argv[3], raw="--raw" in argv) + elif cmd == "pack": + cmd_pack(argv[2], argv[3]) + elif cmd == "verify": + return cmd_verify(argv[2], argv[3]) + return 0 + + +if __name__ == "__main__": + sys.exit(main(sys.argv))