SLEAPyFaces
A package for extracting facial expressions from SLEAP analyses with sensible assumptions.
Based on these scripts
Description
Sleapyfaces is a data analysis package for extracting facial expressions of mice from SLEAP analyses. It is designed to work with the SLEAP software package, which provides a graphical user interface for annotating animal behavioral videos. More information on SLEAP is available at https://sleap.ai. This package also depends on many assumptions about the data format and structure of the SLEAP analyses. It is not intended to be a general tool for extracting facial expressions from SLEAP analyses, but rather a tool for extracting facial expressions from the specific data format and structure used in the lab of Dr. Kay Tye at The Salk Institute for Biological Studies.
Table of Contents
Pages
Citing:
If you use SLEAPyFaces in your research, this does not fall under standard software according to the Publication Manual for the APA, MLA, AMA, Turabian, IEEE, Vancouver style, Harvard style, or Chicago style guides. Please cite the following:
A. Ehler, J. Delahantey, A. Coley, D. LeDuke, L. Keyes, T.D. Pereira, and K. Tye. SLEAPyFaces: A package for extracting facial expressions from SLEAP analyses with sensible assumptions. SLEAPyFaces python package, v1.0.1, 2023. Retrieved from https://github.com/annie444/sleapyfaces/
BibTeX:
@misc{Ehler2023sleapyfaces,
title={SLEAPyFaces: A package for extracting facial expressions from SLEAP analyses with sensible assumptions.},
author={
Ehler, Analetta and
Delahantey, Jeremey and
Coley, Austin and
LeDuke, Deryn and
Keyes, Laurel and
Pereira, Talmo D and
Tye, Kay},
url={https://github.com/annie444/sleapyfaces/},
journal={SLEAPyFaces python package},
publisher={GitHub repository},
volume={v1.0.1},
year={2023},
month={Dec},
day={27}
}
Please also cite the original SLEAP paper:
T.D. Pereira, N. Tabris, A. Matsliah, D. M. Turner, J. Li, S. Ravindranath, E. S. Papadoyannis, E. Normand, D. S. Deutsch, Z. Y. Wang, G. C. McKenzie-Smith, C. C. Mitelut, M. D. Castro, J. D’Uva, M. Kislin, D. H. Sanes, S. D. Kocher, S. S-H, A. L. Falkner, J. W. Shaevitz, and M. Murthy. Sleap: A deep learning system for multi-animal pose tracking. Nature Methods, 19(4), 2022
BibTeX:
@ARTICLE{Pereira2022sleap,
title={SLEAP: A deep learning system for multi-animal pose tracking},
author={Pereira, Talmo D and
Tabris, Nathaniel and
Matsliah, Arie and
Turner, David M and
Li, Junyu and
Ravindranath, Shruthi and
Papadoyannis, Eleni S and
Normand, Edna and
Deutsch, David S and
Wang, Z. Yan and
McKenzie-Smith, Grace C and
Mitelut, Catalin C and
Castro, Marielisa Diez and
D'Uva, John and
Kislin, Mikhail and
Sanes, Dan H and
Kocher, Sarah D and
Samuel S-H and
Falkner, Annegret L and
Shaevitz, Joshua W and
Murthy, Mala},
journal={Nature Methods},
volume={19},
number={4},
year={2022},
publisher={Nature Publishing Group}
}
}
License
sleapyfaces
is distributed under the terms of the MIT license. The full license text is available in the LICENSE file.