
idtracker.ai tracks up to 100 unmarked animals from videos recorded in laboratory conditions using artificial intelligence. Free and open source.
This work has been published in Nature Methods (pdf here), please include the following reference if you use this software in your research:
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Romero-Ferrero, F., Bergomi, M.G., Hinz, R.C., Heras, F.J.H., de Polavieja, G.G., idtracker.ai: tracking all individuals in small or large collectives of unmarked animals. Nature Methods 16, 179 (2019).
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@article{idtrackerai2019,
title={idtracker.ai: tracking all individuals in small or large collectives of unmarked animals},
author={Romero-Ferrero, Francisco and Bergomi, Mattia G and Hinz, Robert C and Heras, Francisco JH and de Polavieja, Gonzalo G},
journal={Nature methods},
volume={16},
number={2},
pages={179--182},
year={2019},
publisher={Nature Publishing Group US New York}
}
Visit our website to find more information about the software, installation instructions, and user guides.
Installation for developers
On an environment with Python>=3.10 and a working installation of Pytorch (Torch and Torchvision) you can install the latest published idtracker.ai version by installing directly form the GitLab repo:
pip install git+https://gitlab.com/polavieja_lab/idtrackerai
Or install the developing version from the develop branch:
pip install git+https://gitlab.com/polavieja_lab/idtrackerai@develop
There exist two extra dependencies options:
dev
to install tools for formatting, static analysis, building, publishing, etc.
docs
to install needed packages to build documentation (sphinx and some plugins).
Contributors
- Jordi Torrents (2022-)
- Tiago Costa (2024)
- Antonio Ortega (2021-2023)
- Francisco Romero-Ferrero (2015-2022)
- Mattia G. Bergomi (2015-2018)
- Ricardo Ribeiro (2018-2020)
- Francisco J.H. Heras (2015-2022)
For more information please send an email (info@idtracker.ai) or use the tools available at https://gitlab.com/polavieja_lab/idtrackerai.