index.rst

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) https://doi.org/10.7717/peerj.453

News

• Release! Version 0.25.0 2024-12-13
• Release! Version 0.24.0 2024-06-18
• Release! Version 0.23.2 2024-04-20
• Release! Version 0.22.0 2023-10-03
• Release! Version 0.21.0 2023-06-02
• Release! Version 0.20.0 2023-02-28
• As part of CZI's 5th EOSS grant cycle, scikit-image received funding to create a typed, discoverable, and extensible API! 2022-11-30

Getting Started

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

import skimage as ski

image = ski.data.coins()
# ... or any other NumPy array!
edges = ski.filters.sobel(image)
ski.io.imshow(edges)
ski.io.show()

You can read more in our user guide. For an introduction to image processing using scikit-image, see this lesson by Data Carpentry.