A Python package (Python3 ready!) that contains implementations of various OpenCV algorithms are are not available in OpenCV or OpenCV-contrib. This package is intended to be used with OpenCV 3.

Some performance-critical algorithms are written in optimized C code. The C code is accessed using cffi.

Currently implemented:

• Morphological algorithms

  • Guo-Hall thinning (C-optimized)
  • Zhang-Suen thinning (C-optimized)
  • Difference-of-Gaussian transform

• Algorithms on contours

  • Masking extraction of convex polygon area from image without rotation
  • Scale around reference point or center
  • Fast computation of center by coordinate averaging
  • Center-invariant rescaling of upright bounding rectangle by x/y factors
  • Filter by min/max area
  • Sort by area
  • Create binary contour mask
  • Grassfire transform

• Colorspace metrics & utilities:

  • Convert image to any colorspace supported by OpenCV
  • Extract any channel from any colorspace directly
  • Euclidean RGB distance

• Other structural algorithms

  • Which neighboring pixels are set in a binary image?

• Algorithms on text rendering

  • Center text at coordinates
  • Auto-scale text to fix into box

• Other algorithms

  • Remove n percent of image borders
  • Popcount (number of one bits) for 8, 16, 32 and 64 bit numpy arrays

As cv2 represents images as numpy arrays, most algorithms generically work with numpy arrays.

# Python2
$ sudo pip install git+https://github.com/ulikoehler/cv_algorithms.git
# or (Python3)
$ sudo pip3 install git+https://github.com/ulikoehler/cv_algorithms.git

Difference of Gaussian transform documentation & example

Grassfire transform documentation & example

Thinning documentation & example

Here's a simple usage showcase:

import cv_algorithms
# img must be a binary, single-channel (grayscale) image.
thinned = cv_algorithms.guo_hall(img)

Contributions of any shape or form are welcome. Please submit a pull request or file an issue on GitHub.

Copyright (c) 2016 Uli Köhler <ukoehler@techoverflow.net>