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scikit-surgeryimage implements image processing tools and alogrithms for Image Guided Surgery.

Project description

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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, 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.

  • Functions to make charuco boards, and detect charuco markers.

  • Interlacing and deinterlacing.

  • Convenience wrappers for erosion and dilation.

  • A PointDetector interface for video camera calibration and implementations such as OpenCV chessboard, ArUco, ChArUco and combinations.

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/UCL/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.

Acknowledgements

Supported by Wellcome and EPSRC.

Project details


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scikit-surgeryimage-0.7.3.tar.gz (44.0 kB view hashes)

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