DeepLabCut is a toolbox for markerless pose estimation of animals performing various tasks.

Software Category: bio

For detailed information, visit the DeepLabCut website.

Available Versions

To find the available versions and learn how to load them, run:

module spider deeplabcut

The output of the command shows the available DeepLabCut module versions.

For detailed information about a particular DeepLabCut module, including how to load the module, run the module spider command with the module’s full version label. For example:

module spider deeplabcut/
ModuleVersion Module Load Command
deeplabcut2.2.1.1-anipose module load singularity/3.7.1 deeplabcut/
deeplabcut2.2 module load singularity/3.7.1 deeplabcut/2.2


We cannot use the official Docker image on Rivanna because:

  • the CUDA version is incompatible with our NVIDIA driver version (as of August 2021);
  • at runtime it tries to download pretrained models inside the container, which is not possible via Singularity.

For further details please visit here.


Python script

Please submit jobs to the GPU partition. A Slurm script template is provided below.

#SBATCH -A mygroup      # your allocation account
#SBATCH -p gpu          # partition
#SBATCH --gres=gpu:1    # number of GPUs
#SBATCH -N 1            # number of nodes
#SBATCH -c 1            # number of cores
#SBATCH -t 10:00:00     # time

module purge
module load singularity deeplabcut

singularity run --nv $CONTAINERDIR/deeplabcut-2.2.sif


Please request a Desktop session on the GPU partition via our Open OnDemand portal. Open a terminal and load the module. Then execute:

singularity run --nv $CONTAINERDIR/deeplabcut-2.2.sif -m deeplabcut