scikit-image is a collection of algorithms for image processing. Itis 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]St茅fan van der Walt, Johannes L. Sch枚nberger, Juan Nunez-Iglesias,Fran莽ois Boulogne, Joshua D. Warner, Neil Yager, Emmanuelle Gouillart,Tony Yu and the scikit-image contributors. scikit-image: Imageprocessing in Python. PeerJ 2:e453 (2014)https://doi.org/10.7717/peerj.453
News露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鈥檚 5th EOSS grant cycle, scikit-image received funding tocreate a typed, discoverable, and extensible API! 2022-11-30
Getting Started露Filtering an image with scikit-image is easy! For more examples, pleasevisit our gallery.
import skimage as skiimage = 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, seethis lesson by Data Carpentry.
Our Team露Along with a large community of contributors, scikit-image developmentis guided by the following core team:
Mark Harfouche@hmaarrfk
Jarrod Millman@jarrodmillman
Josh Warner@JDWarner
Juan Nunez-Iglesias@jni
Lars Gr眉ter@lagru
Marianne Corvellec@mkcor
Egor Panfilov@soupault
Stefan van der Walt@stefanvEmeritus Developers露We thank these previously-active core developers for their contributions to scikit-image.
Johannes Sch枚nberger@ahojnnes
Alexandre de Siqueira@alexdesiqueira
Andreas Mueller@amueller
Steven Silvester@blink1073
Emmanuelle Gouillart@emmanuelle
Gregory Lee@grlee77
Riadh Fezzani@rfezzani
Fran莽ois Boulogne@sciunto
Tony S Yu@tonysyu
Zachary Pincus@zpincus