inspirit / jsfeat

JavaScript Computer Vision library.

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jsfeat

JavaScript Computer Vision library

The project aim is to explore JS/HTML5 possibilities using modern & state-of-art computer vision algorithms.

Examples and Documentation

Features

  • Custom data structures
  • Basic image processing methods (grayscale, derivatives, box-blur, resample, etc.)
  • grayscale (Demo)
  • box blur (Demo)
  • gaussian blur (Demo)
  • equalize histogram (Demo)
  • canny edges (Demo)
  • sobel deriv (Demo)
  • scharr deriv (Demo)
  • find more at Examples and Documentation page
  • Linear Algebra module
  • LU (Gaussian elimination) solver
  • Cholesky solver
  • SVD decomposition, solver and pseudo-inverse
  • Eigen Vectors and Values
  • Multiview module (Demo)
  • Affine2D motion kernel
  • Homography2D motion kernel
  • RANSAC motion estimator
  • LMEDS motion estimator
  • Matrix Math module for various matrix operation such as traspose, multiply etc.
  • Features 2D
  • Fast Corners feature detector (Demo)
  • YAPE06 feature detector (Demo)
  • YAPE feature detector (Demo)
  • ORB feature descriptor (Demo)
  • Lucas-Kanade optical flow (Demo - click to add points)
  • HAAR object detector (Demo)
  • BBF object detector (Demo)

About

JavaScript Computer Vision library.

License:MIT License


Languages

Language:JavaScript 100.0%