A plugin for quantifying shape and neighborhoods from images.

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A plugin for quantifying shape and neighborhoods from images.

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


conda environment file

You can install morphometrics via our conda environment file. To do so, first install anaconda or miniconda on your computer. Then, download the environment.yml file (right click the link and "Save as..."). In your terminal, navigate to the directory you downloaded the environment.yml file to:

cd <path/to/downloaded/environment.yml>

Then create the morphometrics environment using

conda env create -f environment.yml

Once the environment has been created, you can activate it and use morphometrics as described below.

conda activate morphometrics

If you are on Mac OS or Linux install the following:


conda install -c conda-forge ocl_icd_wrapper_apple


conda install -c conda-forge ocl-icd-system

Development installation

To install latest development version :

pip install git+

Example applications

measure the distance between surfaces

napari plugin for measuring properties of segmented objects (regionprops)

object classification

mesh binary mask


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 BSD-3 license, "morphometrics" is free and open source software


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


  • 0.0.8

Last updated:

  • 02 February 2023

First released:

  • 17 March 2022


Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 2
  • Forks: 0
  • Issues + PRs: 0

Python versions supported:

Operating system:


  • glasbey
  • imageio (!=2.11.0,!=2.22.1,>=2.5.0)
  • leidenalg
  • napari-skimage-regionprops
  • napari
  • numba
  • numpy
  • qtpy
  • pandas
  • pooch
  • pyclesperanto-prototype (>=0.8.0)
  • pymeshfix
  • pyqtgraph
  • scanpy
  • scikit-image (>0.19.0)
  • scikit-learn (>=0.24.2)
  • tqdm
  • trimesh[easy]