DeepLabCut

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Description

deeplabcut website  

DeepLabCut is a toolbox for markerless pose estimation of animals performing various tasks. Originally, we demonstrated the capabilities for trail tracking, reaching in mice and various Drosophila behaviors during egg-laying (see Mathis et al. for details). There is, however, nothing specific that makes the toolbox only applicable to these tasks and/or species. The toolbox has also already been successfully applied (by us and others) to rats, humans, various fish species, bacteria, leeches, various robots, cheetahs, mouse whiskers and race horses. This work utilizes the feature detectors (ResNets + readout layers) of one of the state-of-the-art algorithms for human pose estimation by Insafutdinov et al., called DeeperCut, which inspired the name for our toolbox (see references below).

Environment Modules

Run module spider deeplabcut to find out what environment modules are available for this application.

System Variables

  • HPC_{{#uppercase:deeplabcut}}_DIR - installation directory
  • HPC_{{#uppercase:deeplabcut}}_BIN - executable directory




Citation

If you publish research that uses deeplabcut you have to cite it as follows:

If you use this code or data please cite Mathis et al, 2018 and if you use the Python package (DeepLabCut2.0) please also cite Nath, Mathis et al, 2019.