scikit-image
 | |
| Original author(s) | Stéfan van der Walt |
|---|---|
| Initial release | August 2009 |
| Stable release |
0.12.3
/ March 8, 2016[1] |
| Repository |
github |
| 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
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.[5] Scikit-image has also been active in the Google Summer of Code.[6]
Implementation
scikit-image is largely written in Python, with some core algorithms written in Cython to achieve performance.
References
- ↑ Stéfan van der Walt. "scikit-image". Python Package Index.
- ↑ 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. doi:10.7717/peerj.453.
- ↑ 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.
- ↑ Birodkar, Vighnesh (2014). "GSOC 2014 – Signing Off".