Scikit-Shapes: Shape analysis in Python

Welcome to the documentation of Scikit-Shapes, an open source library for shape analysis in Python. Our source code is available on GitHub.

To get started, check out the installation instructions and have a look at the examples.

Warning

This library is still in very active development. We expect to release a first usable version by the end of 2026.

Licensing and citations

This library is licensed under the permissive MIT license, which is fully compatible with both academic and commercial applications.

Scikit-Shapes provides a user-friendly interface for a collection of research papers, whose authors must be credited. If you use this library in an academic context, please run the following piece of code to print a list of the references that have been used in your experiment:

import skshapes as sks

# Run your code here
...

# At the end of your script, print the relevant references.
# This list is updated dynamically by calls to the library functions
# and may be displayed in both bibtex and plain text (APA) formats:
print(sks.bibliography(style="bibtex"))
print(sks.bibliography(style="APA"))

Acknowledgements

Authors:

This library is maintained in the HeKA team, a joint research group between INRIA, INSERM and the Université Paris Cité. It is funded by INRIA, the PRAIRIE-PSAI institute, and is distributed under the permissive MIT license.

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