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NAPS (NAPS is ArUco Plus SLEAP)

NAPS is a tool for researchers with two goals: (1) to quantify animal behavior over a long timescale and high resolution, with minimal human bias, and (2) to track the behavior of individuals with a high level of identity-persistence. This could be of use to researchers studying social network analysis, animal communication, task specialization, or gene-by-environment interactions. By combining deep-learning based pose estimation software with easily read and minimally invasive fiducial markers (“tags”), we provide an easy-to-use solution for producing high-quality, high-dimensional behavioral data.

Features

  • Easy, direct installation across platforms

  • Built directly on top of OpenCV and SLEAP with a modular, extensible codebase

  • Flexible API that allows drop in of different methods for marker identification

Getting NAPS

Easy install (Windows/Linux)

conda:

Caution

This is the recommended installation method for Windows and Linux users only. If you are using an Apple Silicon Mac, please see the NAPS Installation Instructions page for instructions on how to install NAPS.

conda create -n naps naps-track -c kocherlab -c sleap -c nvidia -c conda-forge

References

Manuscript: https://doi.org/10.1101/2022.12.07.518416

@article{wolf2022naps,
   title={NAPS: Integrating pose estimation and tag-based tracking},
   author={Wolf, Scott W and Ruttenberg, Dee M and Knapp, Daniel Y and Webb, Andrew E and Traniello, Ian M and McKenzie-Smith, Grace C and Leheny, Sophie A and Shaevitz, Joshua W and Kocher, Sarah D},
   journal={bioRxiv},
   year={2022},
   publisher={Cold Spring Harbor Laboratory}
}

Issues

  1. Check the docs.

  2. Search the issues on GitHub or open a new one.

Contributors

  • Scott Wolf, Lewis-Sigler Institute for Integrative Genomics, Princeton University

  • Dee Ruttenberg, Lewis-Sigler Institute for Integrative Genomics, Princeton University

  • Daniel Knapp, Department of Physics, Princeton University

  • Andrew Webb, Department of Ecology and Evolutionary Biology and Lewis-Sigler Institute for Integrative Genomics, Princeton University

  • Ian Traniello, Lewis-Sigler Institute for Integrative Genomics, Princeton University

  • Grace McKenzie-Smith, Department of Physics and Lewis-Sigler Institute for Integrative Genomics, Princeton University

  • Sophie Leheny, Department of Molecular Biology, Princeton University

  • Joshua Shaevitz, Department of Physics and Lewis-Sigler Institute for Integrative Genomics, Princeton University

  • Sarah Kocher, Department of Ecology and Evolutionary Biology and Lewis-Sigler Institute for Integrative Genomics, Princeton University

NAPS was created in the Kocher and Shaevitz labs at Princeton University.

License

NAPS is licensed under the MIT license. See the LICENSE file for details.

Acknowledgements

Much of the structure and content of the README and the documentation is borrowed from the SLEAP repository.