Rename project to SoccerDiffusion

.github/pull_request_template.md

@@ -10,4 +10,4 @@
 
 - [ ] Write documentation
 - [ ] Create issues for future work
-- [ ] This PR is on our `DDLitLab` project board
+- [ ] This PR is on our [SoccerDiffusion](https://github.com/orgs/bit-bots/projects/26) project board

.github/workflows/test-dataset.yml

@@ -31,7 +31,7 @@ jobs:
 
       - name: Setup DB with alembic migrations
         run: |
-          cd ./ddlitlab2024/dataset
+          cd ./soccer_diffusion/dataset
           poetry run alembic upgrade head
 
       - name: Populate DB with dummy data

.gitignore

@@ -210,7 +210,7 @@ ENV/
 *.pth
 
 # Wandb Logs
-ddlitlab2024/ml/training/wandb/
+soccer_diffusion/ml/training/wandb/
 
 # Input data
 input/

.vscode/launch.json

@@ -4,7 +4,7 @@
       "type": "debugpy",
       "request": "launch",
       "name": "Launch Bit-Bots import",
-      "program": "${workspaceFolder}/ddlitlab2024/dataset/cli/run.py",
+      "program": "${workspaceFolder}/soccer_diffusion/dataset/cli/run.py",
       "args": [
         "import",
         "bit-bots",
@@ -15,7 +15,7 @@
       "type": "debugpy",
       "request": "launch",
       "name": "Launch B-Human import",
-      "program": "${workspaceFolder}/ddlitlab2024/dataset/cli/run.py",
+      "program": "${workspaceFolder}/soccer_diffusion/dataset/cli/run.py",
       "args": [
         "import",
         "b-human",

.vscode/settings.json

@@ -3,16 +3,19 @@
     "bigendian",
     "dateutil",
     "ddlitlab",
+    "denoising",
     "dtype",
     "dtypes",
     "frombuffer",
+    "gamestate",
     "ignoretz",
     "mcap",
     "nanosec",
     "ndarray",
     "ndim",
     "nullable",
     "ollama",
+    "pretraining",
     "pybh",
     "rclpy",
     "resampler",

README.md

@@ -1,12 +1,11 @@
-# DDLitLab2024 Project Hamburg Bit-Bots
+# SoccerDiffusion
 
-End-to-end machine learning for soccer-playing robots. We are experimenting with diffusion-models to generate robot motions based on recent sensor measurements.
+> Toward Learning End-to-End Humanoid Robot Soccer from Gameplay Recordings
 
-> [!IMPORTANT]
-> This is still an ongioing research project.
+Find our (preprint) paper and more information about the project on our [website](https://bit-bots.github.io/SoccerDiffusion/).
 
-> [!NOTE]
-> This repository contains the source code for our [DDLitLab project](https://www.isa.uni-hamburg.de/ddlitlab.html) [Fußballspielende Roboter: Ende-zu-Ende-KI für Wahrnehmung und Steuerung im RoboCup](https://www.isa.uni-hamburg.de/ddlitlab/data-literacy-studierendenprojekte/vierte-foerderrunde/e2e-robot-soccer.html) for the fourth funding round.
+> [!IMPORTANT]
+> This is still an ongoing research project.
 
 ## Getting Started
 
@@ -19,13 +18,13 @@ End-to-end machine learning for soccer-playing robots. We are experimenting with
 1. Download this repo:
 
     ```shell
-    git clone https://github.com/bit-bots/ddlitlab2024.git
+    git clone https://github.com/bit-bots/SoccerDiffusion.git
     ```
 
 2. Go into the downloaded directory:
 
     ```shell
-    cd ddlitlab2024
+    cd soccer_diffusion
     ```
 
 3. Install dependencies using [poetry](https://python-poetry.org/docs/#installation):
@@ -55,3 +54,11 @@ Some tools contained in this repository require additional system-dependencies.
     ```
 
     Then build the Python package as described in [this document](https://docs.b-human.de/master/python-bindings/#local-build).
+
+## Acknowledgements
+
+We gratefully acknowledge funding and support from the project [*Digital and Data Literacy in Teaching Lab (DDLitLab)*](https://www.hcl.uni-hamburg.de/ddlitlab.html) at the University of Hamburg and the [*Stiftung Innovation in der Hochschullehre*](https://stiftung-hochschullehre.de/) foundation.
+We extend our special thanks to the members of the [*Hamburg Bit-Bots*](https://bit-bots.de/) RoboCup team for their continuous support and for providing data and computational resources.
+We also thank the RoboCup teams [*B-Human*](https://b-human.de/) and [*HULKs*](https://hulks.de/) for generously sharing their data for this research.
+Additionally, we are grateful to the [*Technical Aspects of Multimodal Systems (TAMS)*](https://tams.informatik.uni-hamburg.de/) research group at the University of Hamburg for providing computational resources.
+This research was partially funded by the Ministry of Science, Research and Equalities of Hamburg, as well as the German Research Foundation (DFG) and the National Science Foundation of China (NSFC) through the project [*Crossmodal Learning*](https://www.crossmodal-learning.org/home.html) (TRR-169).

pyproject.toml

@@ -3,10 +3,10 @@ requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
-name = "ddlitlab2024"
-version = "0.0.1"
+name = "soccer_diffusion"
+version = "1.0.0"
 readme = "README.md"
-repository = "https://github.com/bit-bots/ddlitlab2024"
+repository = "https://github.com/bit-bots/SoccerDiffusion"
 authors = ["Florian Vahl", "Jan Gutsche", "Joern Griepenburg"]
 description = ""
 
@@ -60,4 +60,4 @@ line-length = 120
 select = ["F", "E", "B", "W", "I", "N", "UP"]
 
 [tool.poetry.scripts]
-cli = "ddlitlab2024.dataset.cli.run:main"
+cli = "soccer_diffusion.dataset.cli.run:main"

ddlitlab2024/__init__.py → soccer_diffusion/__init__.py

@@ -4,13 +4,13 @@
 from pathlib import Path
 from uuid import UUID, uuid4
 
-_project_name: str = "ddlitlab2024"
+_project_name: str = "soccer_diffusion"
 __version__: str = importlib.metadata.version(_project_name)
 
 # Craft LOGGING PATH
 # Get the log directory from the environment variable or use the default
 _logging_dir: str = os.path.abspath(
-    os.environ.get("DDLITLAB_LOG_DIR", os.path.join(os.path.dirname(__file__), "..", "logs"))
+    os.environ.get("SOCCER_DIFFUSION_LOG_DIR", os.path.join(os.path.dirname(__file__), "..", "logs"))
 )
 
 # Verify that the log directory exists and create it if it doesn't
@@ -40,7 +40,9 @@
 
 SESSION_ID: UUID = uuid4()
 
-DB_PATH: Path = Path(os.environ.get("DDLITLAB_DB_PATH", Path.joinpath(Path(__file__).parent, "dataset", "db.sqlite3")))
+DB_PATH: Path = Path(
+    os.environ.get("SOCCER_DIFFUSION_DB_PATH", Path.joinpath(Path(__file__).parent, "dataset", "db.sqlite3"))
+)
 
 DEFAULT_RESAMPLE_RATE_HZ = 50
 IMAGE_MAX_RESAMPLE_RATE_HZ = 10

ddlitlab2024/dataset/__init__.py → soccer_diffusion/dataset/__init__.py

@@ -3,7 +3,7 @@
 
 from rich.logging import RichHandler
 
-from ddlitlab2024 import LOGGING_PATH, SESSION_ID
+from soccer_diffusion import LOGGING_PATH, SESSION_ID
 
 MODULE_NAME: str = "dataset"
 

ddlitlab2024/dataset/cli/args.py → soccer_diffusion/dataset/cli/args.py

@@ -3,8 +3,8 @@
 from enum import Enum
 from pathlib import Path
 
-from ddlitlab2024 import DB_PATH
-from ddlitlab2024.dataset.errors import CLIArgumentError
+from soccer_diffusion import DB_PATH
+from soccer_diffusion.dataset.errors import CLIArgumentError
 
 
 class ImportType(str, Enum):
@@ -29,7 +29,7 @@ def values(cls):
 
 class CLIArgs:
     def __init__(self):
-        self.parser = ArgumentParser(description="ddlitlab dataset CLI")
+        self.parser = ArgumentParser(description="soccer_diffusion dataset CLI")
         self.set_global_args(self.parser)
 
         subparsers = self.parser.add_subparsers(dest="command", help="Command to run")

ddlitlab2024/dataset/cli/run.py → soccer_diffusion/dataset/cli/run.py

@@ -11,18 +11,26 @@
 
 from rich.console import Console
 
-from ddlitlab2024 import DEFAULT_RESAMPLE_RATE_HZ, IMAGE_MAX_RESAMPLE_RATE_HZ, __version__
-from ddlitlab2024.dataset import logger
-from ddlitlab2024.dataset.cli.args import CLIArgs, CLICommand, DBCommand, ImportType
-from ddlitlab2024.dataset.converters.game_state_converter.b_human_game_state_converter import BHumanGameStateConverter
-from ddlitlab2024.dataset.converters.game_state_converter.bit_bots_game_state_converter import BitBotsGameStateConverter
-from ddlitlab2024.dataset.converters.image_converter import BHumanImageConverter, BitbotsImageConverter, ImageConverter
-from ddlitlab2024.dataset.converters.synced_data_converter import SyncedDataConverter
-from ddlitlab2024.dataset.db import Database
-from ddlitlab2024.dataset.imports.model_importer import ImportStrategy
-from ddlitlab2024.dataset.resampling.max_rate_resampler import MaxRateResampler
-from ddlitlab2024.dataset.resampling.original_rate_resampler import OriginalRateResampler
-from ddlitlab2024.dataset.resampling.previous_interpolation_resampler import PreviousInterpolationResampler
+from soccer_diffusion import DEFAULT_RESAMPLE_RATE_HZ, IMAGE_MAX_RESAMPLE_RATE_HZ, __version__
+from soccer_diffusion.dataset import logger
+from soccer_diffusion.dataset.cli.args import CLIArgs, CLICommand, DBCommand, ImportType
+from soccer_diffusion.dataset.converters.game_state_converter.b_human_game_state_converter import (
+    BHumanGameStateConverter,
+)
+from soccer_diffusion.dataset.converters.game_state_converter.bit_bots_game_state_converter import (
+    BitBotsGameStateConverter,
+)
+from soccer_diffusion.dataset.converters.image_converter import (
+    BHumanImageConverter,
+    BitbotsImageConverter,
+    ImageConverter,
+)
+from soccer_diffusion.dataset.converters.synced_data_converter import SyncedDataConverter
+from soccer_diffusion.dataset.db import Database
+from soccer_diffusion.dataset.imports.model_importer import ImportStrategy
+from soccer_diffusion.dataset.resampling.max_rate_resampler import MaxRateResampler
+from soccer_diffusion.dataset.resampling.original_rate_resampler import OriginalRateResampler
+from soccer_diffusion.dataset.resampling.previous_interpolation_resampler import PreviousInterpolationResampler
 
 err_console = Console(stderr=True)
 
@@ -36,7 +44,7 @@ def main():
         logger.debug(f"Parsed CLI args: {args}")
 
         if args.version:
-            logger.info(f"running ddlitlab2024 CLI v{__version__}")
+            logger.info(f"running soccer_diffusion CLI v{__version__}")
             sys.exit(0)
 
         should_create_schema = args.command == CLICommand.DB and args.db_command == DBCommand.CREATE_SCHEMA
@@ -46,17 +54,17 @@ def main():
             case CLICommand.DB:
                 match args.db_command:
                     case DBCommand.RECORDING2MCAP:
-                        from ddlitlab2024.dataset.recording2mcap import recording2mcap
+                        from soccer_diffusion.dataset.recording2mcap import recording2mcap
 
                         recording2mcap(db.session, args.recording, args.output_dir)
 
                     case DBCommand.DUMMY_DATA:
-                        from ddlitlab2024.dataset.dummy_data import insert_dummy_data
+                        from soccer_diffusion.dataset.dummy_data import insert_dummy_data
 
                         insert_dummy_data(db.session, args.num_recordings, args.num_samples_per_rec, args.image_step)
 
             case CLICommand.IMPORT:
-                from ddlitlab2024.dataset.imports.model_importer import ImportMetadata, ModelImporter
+                from soccer_diffusion.dataset.imports.model_importer import ImportMetadata, ModelImporter
 
                 import_strategy: ImportStrategy
                 import_path: Path = Path(args.file)
@@ -65,7 +73,7 @@ def main():
 
                 match args.type:
                     case ImportType.BIT_BOTS:
-                        from ddlitlab2024.dataset.imports.strategies.bit_bots import BitBotsImportStrategy
+                        from soccer_diffusion.dataset.imports.strategies.bit_bots import BitBotsImportStrategy
 
                         logger.info(f"Trying to import file '{args.file}' to database...")
 
@@ -90,7 +98,7 @@ def main():
                         )
 
                     case ImportType.B_HUMAN:
-                        from ddlitlab2024.dataset.imports.strategies.b_human import BHumanImportStrategy
+                        from soccer_diffusion.dataset.imports.strategies.b_human import BHumanImportStrategy
 
                         metadata = ImportMetadata(
                             allow_public=False,

ddlitlab2024/dataset/converters/converter.py → soccer_diffusion/dataset/converters/converter.py

@@ -1,8 +1,8 @@
 from abc import ABC, abstractmethod
 
-from ddlitlab2024.dataset.imports.data import InputData, ModelData
-from ddlitlab2024.dataset.models import Recording
-from ddlitlab2024.dataset.resampling.resampler import Resampler
+from soccer_diffusion.dataset.imports.data import InputData, ModelData
+from soccer_diffusion.dataset.models import Recording
+from soccer_diffusion.dataset.resampling.resampler import Resampler
 
 
 class Converter(ABC):

ddlitlab2024/dataset/converters/game_state_converter/b_human_game_state_converter.py → soccer_diffusion/dataset/converters/game_state_converter/b_human_game_state_converter.py

@@ -1,10 +1,10 @@
 from enum import Enum, auto
 
-from ddlitlab2024.dataset import logger
-from ddlitlab2024.dataset.converters.converter import Converter
-from ddlitlab2024.dataset.imports.data import InputData, ModelData
-from ddlitlab2024.dataset.models import GameState, Recording, RobotState, TeamColor
-from ddlitlab2024.dataset.resampling.original_rate_resampler import OriginalRateResampler
+from soccer_diffusion.dataset import logger
+from soccer_diffusion.dataset.converters.converter import Converter
+from soccer_diffusion.dataset.imports.data import InputData, ModelData
+from soccer_diffusion.dataset.models import GameState, Recording, RobotState, TeamColor
+from soccer_diffusion.dataset.resampling.original_rate_resampler import OriginalRateResampler
 
 # ruff: noqa: N815
 

ddlitlab2024/dataset/converters/game_state_converter/bit_bots_game_state_converter.py → soccer_diffusion/dataset/converters/game_state_converter/bit_bots_game_state_converter.py

@@ -1,10 +1,10 @@
 from enum import Enum
 
-from ddlitlab2024.dataset import logger
-from ddlitlab2024.dataset.converters.converter import Converter
-from ddlitlab2024.dataset.imports.data import InputData, ModelData
-from ddlitlab2024.dataset.models import GameState, Recording, RobotState, TeamColor
-from ddlitlab2024.dataset.resampling.original_rate_resampler import OriginalRateResampler
+from soccer_diffusion.dataset import logger
+from soccer_diffusion.dataset.converters.converter import Converter
+from soccer_diffusion.dataset.imports.data import InputData, ModelData
+from soccer_diffusion.dataset.models import GameState, Recording, RobotState, TeamColor
+from soccer_diffusion.dataset.resampling.original_rate_resampler import OriginalRateResampler
 
 
 class GameStateMessage(int, Enum):

ddlitlab2024/dataset/converters/image_converter.py → soccer_diffusion/dataset/converters/image_converter.py

@@ -3,11 +3,11 @@
 import cv2
 import numpy as np
 
-from ddlitlab2024.dataset import logger
-from ddlitlab2024.dataset.converters.converter import Converter
-from ddlitlab2024.dataset.imports.data import InputData, ModelData
-from ddlitlab2024.dataset.models import DEFAULT_IMG_SIZE, Image, Recording
-from ddlitlab2024.dataset.resampling.max_rate_resampler import MaxRateResampler
+from soccer_diffusion.dataset import logger
+from soccer_diffusion.dataset.converters.converter import Converter
+from soccer_diffusion.dataset.imports.data import InputData, ModelData
+from soccer_diffusion.dataset.models import DEFAULT_IMG_SIZE, Image, Recording
+from soccer_diffusion.dataset.resampling.max_rate_resampler import MaxRateResampler
 
 
 class ImageConverter(Converter, abc.ABC):

ddlitlab2024/dataset/converters/synced_data_converter.py → soccer_diffusion/dataset/converters/synced_data_converter.py

@@ -1,8 +1,8 @@
-from ddlitlab2024.dataset.converters.converter import Converter
-from ddlitlab2024.dataset.imports.data import InputData, ModelData
-from ddlitlab2024.dataset.models import JointCommands, JointStates, Recording, Rotation
-from ddlitlab2024.dataset.resampling.previous_interpolation_resampler import PreviousInterpolationResampler
-from ddlitlab2024.utils.utils import shift_radian_to_positive_range
+from soccer_diffusion.dataset.converters.converter import Converter
+from soccer_diffusion.dataset.imports.data import InputData, ModelData
+from soccer_diffusion.dataset.models import JointCommands, JointStates, Recording, Rotation
+from soccer_diffusion.dataset.resampling.previous_interpolation_resampler import PreviousInterpolationResampler
+from soccer_diffusion.utils.utils import shift_radian_to_positive_range
 
 
 class SyncedDataConverter(Converter):

ddlitlab2024/dataset/db.py → soccer_diffusion/dataset/db.py

@@ -3,8 +3,8 @@
 from sqlalchemy import Engine, create_engine, event
 from sqlalchemy.orm import Session, sessionmaker
 
-from ddlitlab2024.dataset import logger
-from ddlitlab2024.dataset.models import Base
+from soccer_diffusion.dataset import logger
+from soccer_diffusion.dataset.models import Base
 
 
 @event.listens_for(Engine, "connect")

ddlitlab2024/dataset/dummy_data.py → soccer_diffusion/dataset/dummy_data.py

@@ -7,8 +7,8 @@
 from sqlalchemy.orm import Session
 from tqdm import tqdm
 
-from ddlitlab2024.dataset import logger
-from ddlitlab2024.dataset.models import (
+from soccer_diffusion.dataset import logger
+from soccer_diffusion.dataset.models import (
     GameState,
     Image,
     JointCommands,

ddlitlab2024/dataset/imports/data.py → soccer_diffusion/dataset/imports/data.py

@@ -1,8 +1,8 @@
 from dataclasses import dataclass, field
 from typing import Any
 
-from ddlitlab2024.dataset.models import GameState, Image, JointCommands, JointStates, Recording, Rotation
-from ddlitlab2024.utils.utils import camelcase_to_snakecase
+from soccer_diffusion.dataset.models import GameState, Image, JointCommands, JointStates, Recording, Rotation
+from soccer_diffusion.utils.utils import camelcase_to_snakecase
 
 
 def joints_dict_from_msg_data(joints_data: list[tuple[str, float]]) -> dict[str, float]:

ddlitlab2024/dataset/imports/model_importer.py → soccer_diffusion/dataset/imports/model_importer.py

@@ -1,9 +1,9 @@
 from abc import ABC, abstractmethod
 from pathlib import Path
 
-from ddlitlab2024.dataset.converters.converter import Converter
-from ddlitlab2024.dataset.db import Database
-from ddlitlab2024.dataset.imports.data import ImportMetadata, ModelData
+from soccer_diffusion.dataset.converters.converter import Converter
+from soccer_diffusion.dataset.db import Database
+from soccer_diffusion.dataset.imports.data import ImportMetadata, ModelData
 
 
 class ImportStrategy(ABC):