A collection of algorithms for image processing in Python. Built on NumPy, SciPy, and Cython. It focuses on scientific image analysis including segmentation, geometric transformations, color space manipulation, analysis, and filtering.
Quickly install scikit-image AI skill to your development environment via command line
Source: tondevrel/scientific-agent-skills.
scikit-image treats images as NumPy arrays. It provides a comprehensive suite of algorithms for filtering, feature detection, and object measurement, making it the standard for research-grade image analysis.
Official docs: https://scikit-image.org/ User Guide: https://scikit-image.org/docs/stable/userguide.html Search patterns: skimage.filters, skimage.segmentation, skimage.feature, skimage.morphology
Images are NumPy Arrays A grayscale image is a 2D array (M, N). A color image is a 3D array (M, N, 3). A multichannel 3D volume is (P, M, N, C).
A collection of algorithms for image processing in Python. Built on NumPy, SciPy, and Cython. It focuses on scientific image analysis including segmentation, geometric transformations, color space manipulation, analysis, and filtering. Source: tondevrel/scientific-agent-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/tondevrel/scientific-agent-skills --skill scikit-imageA collection of algorithms for image processing in Python. Built on NumPy, SciPy, and Cython. It focuses on scientific image analysis including segmentation, geometric transformations, color space manipulation, analysis, and filtering. Source: tondevrel/scientific-agent-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/tondevrel/scientific-agent-skills --skill scikit-image Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/tondevrel/scientific-agent-skills