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Turn Python-based image processing workflows into algorithms that gain extra functionalities.

stardist_blobs.mp4
oripy_threshold.mp4
tiles.mp4
yolo-stream.mp4

Getting started

The documentation is available on this page.

Supported image analysis tasks

Task Examples Napari QuPath
Image segmentation CellPose, StarDist, Instanseg, SAM-2, Rembg, CellPose4 (GPU)
Points detection Spotiflow
Boxes detection Ultralytics YOLO
Vectors detection OrientationPy
Image registration StackReg, Spam
Image denoising Noise2Void
Paths detection SplineBox
Tracking Trackpy, Trackastra
Image generation Stable Diffusion
Live updates Webcam stream

Roadmap

July 2026

The Imaging Server Kit is being actively developed! Here is what we're up to:

  • Developing a bridge with QuPath via qubalab
  • Introducing new types (sk.Any, sk.Plot, sk.Table)
  • Developing tiled inference via dask or ome-zarr
  • Integration with fastapi deploy
  • Investigating gRPC for remote calls

Contributors

  • Mallory Wittwer, EPFL Center for Imaging (mallory.wittwer@epfl.ch)
  • Dr. Edward Andò, EPFL Center for Imaging
  • Dr. Maud Barthélémy, EPFL Center for Imaging
  • Dr. Florian Aymanns, EPFL Center for Imaging

Acknowledgements

We acknowledge the Personalized Health and Related Technologies (PHRT) initiative for supporting this project.

Pinned Loading

  1. imaging-server-kit imaging-server-kit Public

    Deploy image processing algorithms in FastAPI servers and easily run them in Napari, QuPath, and more.

    Python 10 1

  2. qupath-extension-serverkit qupath-extension-serverkit Public

    Run image processing algorithms in QuPath using a client/server interface

    Java 1 1

  3. napari-serverkit napari-serverkit Public

    Run Imaging Server Kit algorithms interactively in Napari

    Python 1

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