scikit-surgeryarucotracker 0.0.1

scikit-surgeryarucotracker is a simple tracking interface using ARuCo markers

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 usinng other tracking hardware (e.g. NDI - scikit-surgerynditracker).

scikit-surgeryarucotracker is part of the SNAPPY software project, developed at the Wellcome EPSRC Centre for Interventional and Surgical Sciences, part of University College London (UCL).

scikit-surgeryarucotracker supports Python 2.7 and Python 3.6.

Installing

pip install scikit-surgeryarucotracker

Using

Configuration is done using Python libraries. Tracking data is returned in NumPy arrays.

from sksurgerarucotracker.tracker import ARuCoTracker
SETTINGS = {
    "video source" : 0
        }
TRACKER = ARuCo()
TRACKER.connect(SETTINGS)

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://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/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-surgerytracker is released under the BSD-3 license. Please see the license file for details.

Acknowledgements

Supported by Wellcome and EPSRC.