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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.

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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

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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()
_images/coins-small.png _images/sobel-coins-small.png

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

Our Team

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

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Gregory Lee
@grlee77
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Jarrod Millman
@jarrodmillman
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Josh Warner
@JDWarner
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Riadh Fezzani
@rfezzani
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Egor Panfilov
@soupault

Emeritus Developers

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

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Alexandre de Siqueira
@alexdesiqueira
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Tony S Yu
@tonysyu
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