Optimized OpenCV extra algorithms for Python2/3
APACHE-2.0 License
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:
As OpenCV's Python bindings (cv2
) represents images as numpy arrays, most algorithms generically work with numpy1 arrays.
Install the stable version:
pip install cv_algorithms
How to install the bleeding-edge version from GitHub
pip install git+https://github.com/ulikoehler/cv_algorithms.git
How to build yourself - we use Poetry:
poetry build
Potentially, you need to install OpenCV if not already present. I recommend first trying to install without that, since modern Python versions will take care of that automatically.
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) 2016-2022 Uli Köhler <[email protected]>