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scikit-image

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scikit-image
File:Scikit-image logo and wordmark.png
Original author(s)Stéfan van der Walt
Initial releaseAugust 2009; 16 years ago (2009-08)
Written inPython, Cython, and C.
Engine
    Operating systemLinux, Mac OS X, Microsoft Windows
    TypeLibrary for image processing
    LicenseBSD License
    Websitescikit-image.org

    Search Scikit-image on Amazon.

    scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language.[1] It includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more.[2] It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

    Overview

    The scikit-image project started as scikits.image, by Stéfan van der Walt. Its name stems from the notion that it is a "SciKit" (SciPy Toolkit), a separately-developed and distributed third-party extension to SciPy.[3] The original codebase was later extensively rewritten by other developers. Of the various scikits, scikit-image as well as scikit-learn were described as "well-maintained and popular" in November 2012.[4] Scikit-image has also been active in the Google Summer of Code.[5]

    Implementation

    scikit-image is largely written in Python, with some core algorithms written in Cython to achieve performance.

    References

    1. S van der Walt; JL Schönberger; J Nunez-Iglesias; F Boulogne; JD Warner; N Yager; E Gouillart; T Yu; the scikit-image contributors (2014). "scikit-image: image processing in Python". PeerJ. 2:e453: e453. arXiv:1407.6245. Bibcode:2014PeerJ...2..453V. doi:10.7717/peerj.453. PMC 4081273. PMID 25024921.
    2. Chiang, Eric (2014). "Image Processing with scikit-image".
    3. Dreijer, Janto. "scikit-image".
    4. Eli Bressert (2012). SciPy and NumPy: an overview for developers. O'Reilly. p. 43. ISBN 9781449361624. Search this book on
    5. Birodkar, Vighnesh (2014). "GSOC 2014 – Signing Off".

    External links


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