sleap-docker-container

This repository stores a containerized version of the sleap-nn library, a standalone package for PyTorch-based training/inference pipelines. The layout of this repository follows the guidance for creating applications in Pennsieve, to enable running SLEAP workflows through the Pennsieve platform.

Requirements

• Docker
• (Optional) NVIDIA GPU + NVIDIA Container Toolkit

Build the Docker Image

From the root of the repository:

docker build -t sleap-uv .

Run the Container (Interactive Shell)

Mount a local data directory into the container:

docker run --rm -it \
  -v "$(pwd)/data":/workspace \
  sleap-uv \
  bash

Inside the container:

cd /workspace
sleap-nn --help

Run sleap-nn Directly

Instead of launching a shell, you can run commands directly:

docker run --rm -it \
  -v "$(pwd)/data":/workspace \
  sleap-uv \
  sleap-nn predict --help

All input/output files should live in the mounted directory (/workspace) so results persist on the host.

GPU Usage

If running on a machine with an NVIDIA GPU:

docker run --rm -it \
  --gpus all \
  -v "$(pwd)/data":/workspace \
  sleap-uv \
  sleap-nn train ...