UDMT v1.1.1

This release provides a frozen, citable snapshot of the UDMT codebase corresponding to the version used in the accompanying manuscript.

Scope

• This release is intended solely for reproducibility purposes.
• The code snapshot matches the implementation used to generate the results reported in the manuscript.
• No further feature development or refactoring is intended for this release.

Main contents

• Complete implementation of UDMT (Unsupervised Deep Multi-animal Tracking).
• Training, inference, and evaluation pipelines as described in the paper.
• Graphical user interface (GUI) for training, tracking, and visualization.

Reproducibility notes

• The recommended software environment (OS, Python, PyTorch, CUDA) is described in the README.
• Python dependencies are specified in requirements.txt and requirements_custom.txt.
• Large datasets are not included in the repository and should be obtained as described in the paper and README.

License

• The code is released under an Academic or Non-profit, Non-commercial Research Use Only license.
• See the LICENSE file for full terms and conditions.

Citation

• If you use this code, please cite the accompanying paper as described in the Citation section of the README.

UDMT v1.0.0

This release provides a frozen, citable snapshot of the UDMT codebase corresponding to the version used in the accompanying manuscript.

Scope

• This release is intended solely for reproducibility purposes.
• The code snapshot matches the implementation used to generate the results reported in the manuscript.
• No further feature development or refactoring is intended for this release.

Main contents

• Complete implementation of UDMT (Unsupervised Deep Multi-animal Tracking).
• Training, inference, and evaluation pipelines as described in the paper.
• Graphical user interface (GUI) for training, tracking, and visualization.

Reproducibility notes

• The recommended software environment (OS, Python, PyTorch, CUDA) is described in the README.
• Python dependencies are specified in requirements.txt and requirements_custom.txt.
• Large datasets are not included in the repository and should be obtained as described in the paper and README.

License

• The code is released under an Academic or Non-profit, Non-commercial Research Use Only license.
• See the LICENSE file for full terms and conditions.

Citation

• If you use this code, please cite the accompanying paper as described in the Citation section of the README.