Multi-animal pose estimation, identification, and tracking with DeepLabCut

Jessy Lauer, Mu Zhou, Shaokai Ye, William Menegas, Steffen Schneider, Tanmay Nath, Mohammed Mostafizur Rahman, Valentina Di Santo, Daniel Soberanes, Guoping Feng, Venkatesh N. Murthy, George Lauder, Catherine Dulac, Mackenzie Weygandt Mathis*, and Alexander Mathis*. Nature Methods 2022 | Code and data for reproducing main results.

Quick start:

• git clone this folder git clone https://github.com/DeepLabCut/maDLC_NatureMethods2022.git

• we suggest using the deeplabcut conda environment, as then all (and more) dependencies are met. Thus, activate the environment and navigate into the cloned folder.

• from the terminal launch jupyter notebook and select the Figure you wish to explore (each figure has one notebook in https://github.com/DeepLabCut/maDLC_NatureMethods2022/tree/main/notebooks)

If you use code from this repo we kindly ask that you cite:

  @article{Lauer2022MultianimalPE,
  title={Multi-animal pose estimation, identification and tracking with DeepLabCut},
  author={Jessy Lauer and Mu Zhou and Shaokai Ye and William Menegas and Steffen Schneider and Tanmay Nath and Mohammed Mostafizur Rahman and Valentina       Di Santo and Daniel Soberanes and Guoping Feng and Venkatesh N. Murthy and George Lauder and Catherine Dulac and M. Mathis and Alexander Mathis},
  journal={Nature Methods},
  year={2022},
  volume={19},
  pages={496 - 504}
  }