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sleap-io

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Standalone utilities for working with animal pose tracking data.

This is intended to be a complement to the core SLEAP package that aims to provide functionality for interacting with pose tracking-related data structures and file formats with minimal dependencies. This package does not have any functionality related to labeling, training, or inference.

Features

The main purpose of this library is to provide utilities to load/save from different formats for pose data and standardize them into our common Data Model.

This enables ease-of-use through format-agnostic operations that make it easy to work with pose data, including utilities for common tasks. Some of these include:

See Examples for more usage examples and recipes.

Installation

From PyPI

pip install sleap-io

or

conda install -c conda-forge sleap-io

From source (latest version)

pip install git+https://github.com/talmolab/sleap-io.git@main

Optional Dependencies

For video backend support, install with extras:

pip install sleap-io[opencv]  # For OpenCV backend
pip install sleap-io[av]       # For PyAV backend  
pip install sleap-io[all]      # For all video backends

Development Installation

For development, use one of the following:

uv sync --all-extras           # Recommended: install with uv
conda env create -f environment.yml
pip install -e .[dev,all]      # Install with all extras for development

Support

For technical inquiries specific to this package, please open an Issue with a description of your problem or request.

For general SLEAP usage, see the main website.

Other questions? Reach out to talmo@salk.edu.

License

This package is distributed under a BSD 3-Clause License and can be used without restrictions. See LICENSE for details.