scikit-surgeryimage 1.0.4

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).

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

• Interlacing and deinterlacing.

• 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

• Source code repository

• Documentation

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

Supported by Wellcome and EPSRC.