Stable (release notes)






Image processing in Python

scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers.

If you find this project useful, please cite: [BiBTeX]

Stéfan van der Walt, Johannes L. Schönberger, Juan Nunez-Iglesias, François Boulogne, Joshua D. Warner, Neil Yager, Emmanuelle Gouillart, Tony Yu and the scikit-image contributors. scikit-image: Image processing in Python. PeerJ 2:e453 (2014)


  • Release! Version 0.17.1 2020-05-08

  • Release! Version 0.16.1 2019-10-14

  • Release! Version 0.14.3 2019-06-11

  • Release! Version 0.15.0 2019-04-02

  • Release! Version 0.14.2 2019-01-18

  • CZI announces funding support for scikit-image! 2018-12-07

  • Release! Version 0.14.1 2018-10-02

Getting Started

Filtering an image with scikit-image is easy! For more examples, please visit our gallery.

from skimage import data, io, filters

image = data.coins()
# ... or any other NumPy array!
edges = filters.sobel(image)
_images/coins-small.png _images/sobel-coins-small.png

You can read more in our user guide.

Our Team

Along with a large community of contributors, scikit-image development is guided by the following core team:

Avatar picture of @alexdesiqueira
Alexandre de Siqueira
Avatar picture of @JDWarner
Josh Warner
Avatar picture of @rfezzani
Riadh Fezzani
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Egor Panfilov

Emeritus Developers

We thank these previously-active core developers for their contributions to scikit-image.

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Tony S Yu
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