What is scikit-image?
The scikit-image library provides a diverse array of tools and algorithms for manipulating and analyzing digital images using the Python programming language. This robust and feature-rich library supports a wide range of image processing tasks, including image filtering, segmentation, feature extraction, and color space transformations. Developers can leverage the comprehensive set of functions within scikit-image to automate complex image processing workflows, enabling efficient and scalable image-based data processing and analysis. Backed by a large and active community of contributors, the open-source scikit-image project offers continuous improvements and expansions to its capabilities, making it a versatile choice for both academic research and industrial applications that require advanced image processing capabilities in a Python environment
Highlights
- Extensive set of image processing algorithms covering filtering, segmentation, feature extraction, and color space transformations
- Supports a diverse range of image data formats, including standard image file formats and scientific data formats
- Integrates with other popular Python libraries, such as NumPy and SciPy, for seamless integration with scientific computing workflows
- Actively maintained and expanded by a large community of contributors, ensuring ongoing development and support
- Open-source and freely available, allowing for customization and integration into a wide range of projects
Features
Released under BSD-3-Clause license
Provides I/O, filtering, morphology,
Written in Python with a well-commented source
Has had 5,709 commits made by 116 contributors