scikit-surgeryimage implements image processing tools and alogrithms for Image Guided Surgery.
scikit-surgeryimage is a python only project to implement image processing algorithms that are useful for image-guided surgery.
scikit-surgeryimage was developed at the Wellcome EPSRC Centre for Interventional and Surgical Sciences in University College London (UCL).
requirements.txt specifies a dependency on opencv-contrib-python-headless, so you can use any OpenCV python therein. In addition, this project provides:
Convenience classes for video read and write.
Utilities to detect the number of cameras and prepare text for overlay on video.
A PointDetector interface for video camera calibration and implementations such as OpenCV chessboard, ArUco, ChArUco and combinations.
Generate ChArUco patterns
Convenience wrappers for erosion and dilation.
You can pip install directly from the repository as follows:
pip install scikit-surgeryimage
You can clone the repository using the following command:
git clone https://github.com/SciKit-Surgery/scikit-surgeryimage
Running the tests
You can run the unit tests by installing and running tox:
pip install tox tox
Please check list of common issues.
Please see the contributing guidelines.
Licensing and copyright
Copyright 2018 University College London. scikit-surgeryimage is released under the BSD-3 license. Please see the license file for details.
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