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CloudScope

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CloudScope is a desktop and browser application for viewing, annotating, and analyzing acquisition-backed microscopy files. It is designed for scientific image-analysis workflows where the same data and analysis code should be available from the GUI, from scripts, and from reproducible examples.

The desktop app, browser app, and Python scripting workflows all use the same acqstore scientific backend. This is central to CloudScope's reproducibility model: GUI workflows and scripted workflows should execute the same backend analysis code rather than separate reimplementations.

Try CloudScope

The web app is the fastest way to try CloudScope before installing a desktop build. The desktop apps provide the same core GUI and backend analysis workflow for local use on macOS and Windows.

Supported file formats

CloudScope provides native support for commercial microscopy formats and open scientific image formats, including:

  • Olympus / Evident .oir
  • Zeiss .czi
  • TIFF .tif
  • OME-Zarr .ome.zarr

Scientific workflows

CloudScope supports ROI-based image analysis workflows including velocity analysis and diameter analysis. The GUI is optimized for interactive use with linked panels and widgets, while the backend analysis engine remains scriptable through Python.

Visualization and analysis are optimized separately. CloudScope can use image pyramids to display only the resolution required for the current view while preserving full-resolution image data for backend acqstore analysis. Intensive analysis paths can use multiprocessing or multithreading where available, and the same acceleration paths are available from the GUI and scripts.

Sample data

Example datasets are maintained in the companion repository:

https://github.com/mapmanager/cloudscope-data

The CloudScope GUI includes a menu item to load sample data. The same data can also be fetched from Python scripts and notebooks through acqstore.sample_data.

Documentation

Full documentation is built with MkDocs and organized by user type:

  • End users: installing, launching, opening data, running analysis, and using the GUI.
  • Scientific users and data scientists: algorithms, parameters, results, notebooks, and scripting with acqstore.
  • Developers: architecture, local development, testing, desktop builds, deployment, and contributing.

Documentation site: https://mapmanager.github.io/cloudscope/

Minimal developer workflow

Clone the repository, install dependencies with uv, and run the app locally:

uv sync
uv run python src/cloudscope/app.py

Run in browser mode:

CLOUDSCOPE_NATIVE=0 uv run python src/cloudscope/app.py

Run tests:

uv run pytest

Build and serve docs locally:

uv sync --group docs
uv run mkdocs serve

See the developer documentation for Docker, environment variables, testing with coverage, and release builds.