Description:
scikitsurgeryarucotracker 1.0.3
Author: Stephen Thompson
scikit-surgeryarucotracker provides a simple Python interface between OpenCV’s ARuCo marker tracking libraries and other Python packages designed around scikit-surgerytrackers. It allows you to treat an object tracked using ARuCo markers in the same way as an object tracked using other tracking hardware (e.g. aruco - scikit-surgerynditracker).
scikit-surgeryarucotracker is part of the SciKit-Surgery software project, developed at the Wellcome EPSRC Centre for Interventional and Surgical Sciences, part of University College London (UCL).
scikit-surgeryarucotracker is tested with Python 3.6 and may support other Python versions.
Installing
pip install scikit-surgeryarucotracker
Using
Configuration is done using Python libraries. Tracking data is returned in NumPy arrays.
from sksurgeryarucotracker.arucotracker import ArUcoTracker
config = {
"video source" : 0
}
tracker = ArUcoTracker(config)
tracker.start_tracking()
print(tracker.get_frame())
tracker.stop_tracking()
tracker.close()
Developing
Cloning
You can clone the repository using the following command:
git clone https://github.com/SciKit-Surgery/scikit-surgeryarucotracker
Running the tests
You can run the unit tests by installing and running tox:
pip install tox
tox
Contributing
Please see the contributing guidelines.
Useful links
Source code repository
Documentation
Licensing and copyright
Copyright 2019 University College London.
scikit-surgeryarucotracker is released under the BSD-3 license. Please see the license file for details.
Acknowledgements
Supported by Wellcome and EPSRC.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Customer Reviews
There are no reviews.
