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.
pip install scikit-surgeryarucotracker
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()
You can clone the repository using the following command:
git clone https://github.com/SciKit-Surgery/scikit-surgeryarucotracker
You can run the unit tests by installing and running tox:
pip install tox tox
Please see the contributing guidelines.
Copyright 2019 University College London. scikit-surgeryarucotracker is released under the BSD-3 license. Please see the license file for details.