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 in September 2025.

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.

Content