scikit-image
 | |
| Original author(s) | Stéfan van der Walt |
|---|---|
| Initial release | August 2009 |
| Stable release | 0.23.2[1]
/ 20 April 2024 |
| Repository | |
| Written in | Python, Cython, and C. |
| Operating system | Linux, Mac OS X, Microsoft Windows |
| Type | Library for image processing |
| License | BSD License |
| Website | scikit-image |
scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language.[2] It includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more.[3] It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.
Overview[edit]
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.[4] 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[update].[5] Scikit-image has also been active in the Google Summer of Code.[6]
Implementation[edit]
scikit-image is largely written in Python, with some core algorithms written in Cython to achieve performance.
References[edit]
- ^ "Release 0.23.2". 20 April 2024. Retrieved 25 April 2024.
- ^ 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.
{{cite journal}}:|author9=has generic name (help) - ^ Chiang, Eric (2014). "Image Processing with scikit-image".
- ^ Dreijer, Janto. "scikit-image".
- ^ Eli Bressert (2012). SciPy and NumPy: an overview for developers. O'Reilly. p. 43. ISBN 9781449361624.
- ^ Birodkar, Vighnesh (2014). "GSOC 2014 – Signing Off".