A segmentation plugin to adapt Omnipose implementation to partial labelling.

License GNU GPL v3.0 PyPI Python Version tests codecov napari hub

A plugin to adapt the Omnipose implementation to frugal labeling. It aims to facilitate the training from scratch or the use of transfer learning with little data, by not needing to draw entire cells, but a few squiggles instead (see GIF below).

If you use this plugin please cite the paper:

Clément Cazorla, Nathanaël Munier, Renaud Morin, Pierre Weiss. Sketchpose: Learning to Segment Cells with Partial Annotations. 2023. ffhal-04330824f

      TITLE = {{Sketchpose: Learning to Segment Cells with Partial Annotations}},
      AUTHOR = {Cazorla, Cl{\'e}ment and Munier, Nathana{\"e}l and Morin, Renaud and Weiss, Pierre},
      URL = {},
      NOTE = {working paper or preprint},
      YEAR = {2023},
      MONTH = Dec,
      KEYWORDS = {Cellpose -Segmentation -Frugal learning -Napari -Deep learning -Distance map},
      PDF = {},
      HAL_ID = {hal-04330824},
      HAL_VERSION = {v1},

Image Credit: Eduard Muzhevskyi

This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.


First, we advise you to create a conda environment in Python 3.10, in which you will run Napari:

conda create -n sketchpose_env python=3.10
conda activate sketchpose_env
conda install pip
python -m pip install "napari[all]" --upgrade

You can install napari_sketchpose via pip:

pip install napari_sketchpose


For Windows users, CUDA version of PyTorch may not be installed properly. When the plugin starts for the first time, it checks whether CUDA version is installed. If not, it tries to install it using light-the-torch library. If this does not work, you should re-install CUDA torch and torchvision versions manually, otherwise the plugin will not work properly.


We strongly recommend reading the documentation to get the most out of the plugin. A step-by-step tutorial illustrated with GIFs will guide you through the various stages.


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.


Distributed under the terms of the GNU GPL v3.0 license, "napari-sketchpose" is free and open source software


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


  • 0.1.8

Last updated:

  • 08 December 2023

First released:

  • 07 November 2023


Supported data:

  • Information not submitted

Open extension:

Save extension:

Save layers:

GitHub activity:

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

Python versions supported:

Operating system:


  • numpy
  • magicgui
  • qtpy
  • cellpose-omni ==0.9.1
  • omnipose ==0.4.4
  • pyqtgraph ==0.13.3
  • matplotlib
  • light-the-torch

Sign up to receive updates