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).
Features
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.
Installing
You can pip install directly from the repository as follows:
pip install scikit-surgeryimage
Developing
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
Encountering Problems?
Please check list of common issues.
Contributing
Please see the contributing guidelines.
Useful links
Licensing and copyright
Copyright 2018 University College London. scikit-surgeryimage is released under the BSD-3 license. Please see the license file for details.
Acknowledgements
2 maintainers
Release files for scikit-surgeryimage 1.1.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| scikit_surgeryimage-1.1.0.tar.gz | 50.3 kB | Details |
Release files / scikit_surgeryimage-1.1.0.tar.gz
| Download URL | scikit_surgeryimage-1.1.0.tar.gz |
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