https://github.com/p-sira/deeplabcut2yolo

Convert DeepLabCut to YOLO
https://github.com/p-sira/deeplabcut2yolo

ai deeplabcut yolo yolov8 yolov8-pose yolov8-segmentation yolov8n

Last synced: 8 months ago
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Convert DeepLabCut to YOLO

• Host: GitHub
• URL: https://github.com/p-sira/deeplabcut2yolo
• Owner: p-sira
• License: other
• Created: 2024-11-17T13:49:50.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2025-01-25T04:17:28.000Z (9 months ago)
• Last Synced: 2025-01-25T04:32:40.876Z (9 months ago)
• Topics: ai, deeplabcut, yolo, yolov8, yolov8-pose, yolov8-segmentation, yolov8n
• Language: Python
• Homepage:
• Size: 20.9 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE
  • Citation: CITATION.bib

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README

          
# deeplabcut2yolo

**Convert DLC to YOLO,**\

**Lightning-fast and hassle-free.**

[![License: GPL v3](https://img.shields.io/badge/license-GPLv3-red.svg)](https://www.gnu.org/licenses/gpl-3.0)

[![PyPI Package Version](https://img.shields.io/pypi/v/deeplabcut2yolo?label=pypi%20package&color=a190ff)](https://pypi.org/project/deeplabcut2yolo/)

[![Package Total Downloads](https://img.shields.io/pepy/dt/deeplabcut2yolo)](https://pepy.tech/projects/deeplabcut2yolo)

[![Documentation](https://img.shields.io/badge/docs-passing-default)](https://p-sira.github.io/deeplabcut2yolo/)

**deeplabcut2yolo** facilitates training [DeepLabCut datasets](https://benchmark.deeplabcut.org/datasets.html) on [YOLO](https://docs.ultralytics.com/) models. Deeplabcut2yolo automatically converts DeepLabCut (DLC) labels to COCO-like format compatible with YOLO, while providing customizability for more advanced users, so you can spend your energy on what matters!

![Results from d2y](d2y-trimouse.jpg "DLC Tri-mouse dataset converted for YOLO training")

*All DeepLabCut datasets belong to their respective owner under CC BY-NC 4.0. This particular image is the training data for YOLO, converted using deeplabcut2yolo from the Tri-Mouse dataset (Lauer et al., 2022).*

## Quick Start

```python

import deeplabcut2yolo as d2y

d2y.convert("./deeplabcut-dataset/")

# To also generate data.yml

d2y.convert(

    dataset_path,

    train_paths=train_paths,

    val_paths=val_paths,

    skeleton_symmetric_pairs=skeleton_symmetric_pairs,

    data_yml_path="data.yml",

    class_names=class_names,

    verbose=True,

)

```

To install deeplabcut2yolo using pip:

```

pip install deeplabcut2yolo

```

For more information, see [examples](https://github.com/p-sira/deeplabcut2yolo/tree/main/examples) and [documentation](https://p-sira.github.io/deeplabcut2yolo/).

## Contribution

You can contribute to deeplabcut2yolo by making pull requests. Currently, these are high-priority features:

- Testing module and test cases

- Documentation

## Citation

Citation is not required but is greatly appreciated. If this project helps you, 

please cite using the following APA-style reference

> Pornsiriprasert, S. (2025). *Deeplabcut2yolo: A Python Library for Converting DeepLabCut Dataset to YOLO Format* (Version 2.2.4) [Computer software]. GitHub. https://github.com/p-sira/deeplabcut2yolo/

or this BibTeX entry.

```

@software{deeplabcut2yolo,

    author = {{Pornsiriprasert, S}},

    title = {Deeplabcut2yolo: A Python Library for Converting DeepLabCut Dataset to YOLO Format},

    url = {https://github.com/p-sira/deeplabcut2yolo/},

    version = {2.2.4},

    publisher = {GitHub},

    year = {2025},

    month = {1},

}

```