Quantifying 2D cell shape and epithelial tissue dynamics

Workflow step:
Image segmentation
Image modality:
Fluorescence microscopy
Confocal microscopy

Licence PyPI Python Version tests Documentation coverage napari hub

EpiTools is a Python package and associated napari plugin to extract the membrane signal from epithelial tissues and analyze it with the aid of computer vision.

The development of EpiTools was inspired by the challenges in analyzing time-lapses of growing Drosophila imaginal discs.

The folded morphology, the very small apical cell surfaces and the long time series required a new automated cell recognition to accurately study growth dynamics.


First, install napari.

The recommended way to install EpiTools is via pip

python -m pip install epitools

To install the latest development version of EpiTools clone this repository and run

python -m pip install -e .

If working on Apple Silicon make sure to also install the following package from conda-forge.

conda install -c conda-forge pyqt

To also install the recommended plugins for the EpiTools workflow run

python -m pip install epitools[wf]


python -m pip install -e .[wf]

When installing with Apple Mac OS X terminal, you might need to add '"' to [wf] as in:

python -m pip install -e ."[wf]"

If working on Apple Silicon make sure to also install the following package from conda-forge

conda install -c conda-forge cvxopt

which is required for btrack.


If you encounter any problems, please file an issue along with a detailed description.


Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.


  • 0.0.12

Last updated:

  • 15 August 2023

First released:

  • 04 May 2023


Supported data:

Open extension:

Save extension:

Save layers:

GitHub activity:

  • Stars: 6
  • Forks: 0
  • Issues + PRs: 24

Python versions supported:

Operating system:


  • PartSeg
  • magicgui
  • matplotlib
  • napari
  • networkx
  • numpy
  • pandas
  • scikit-image >=0.20
  • scipy

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