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scikit-surgeryarucotracker is a simple tracking interface using ARuCo markers

Project description

Logo GitHub CI test status Test coverage Documentation Status The SciKit-Surgery paper Software DOI

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)




You can clone the repository using the following command:

git clone

Running the tests

You can run the unit tests by installing and running tox:

pip install tox


Please see the contributing guidelines.


Supported by Wellcome and EPSRC.

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