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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) http://dx.doi.org/10.7717/peerj.453

News

  • Release! Version 0.13.1 2017-09-28
  • Sprint! SciPy2017, Austin, 10–6 July 2017
  • Release! Version 0.13 2017-03-29

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)
io.imshow(edges)
io.show()
_images/coins-small.png _images/sobel-coins-small.png

You can read more in our user guide.