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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.

Acknowledgements

Supported by Wellcome and EPSRC.

Release files for scikit-surgeryarucotracker 1.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for scikit-surgeryarucotracker 1.1.0
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