---
title: LibreYOLO
emoji: 🔍
colorFrom: indigo
colorTo: blue
sdk: static
pinned: false
---

<div align="center">

# LibreYOLO

**MIT-licensed open-source computer vision.**

Inference and training for a wide range of detection models, behind one familiar Python and CLI interface.

![LibreYOLO detection example](https://raw.githubusercontent.com/LibreYOLO/libreyolo/dev/libreyolo/assets/parkour_result.jpg)

</div>

## What is LibreYOLO?

LibreYOLO is an MIT-licensed computer vision library with inference and training support for a variety of models. It provides a familiar high-level Python and CLI interface and reads common YOLO-format datasets, so existing workflows port over with minimal changes. There is no AGPL anywhere in the dependency chain, so you can use it in closed-source or commercial products.

```python
from libreyolo import LibreYOLO, SAMPLE_IMAGE

model = LibreYOLO("LibreYOLO9t.pt")
result = model(SAMPLE_IMAGE, save=True)
```

The flagship families are **YOLOv9** (CNN) and **RF-DETR** (transformer) for detection and segmentation. The weights hosted in this organization auto-download on first use.

## Try it in your browser

No install required. Run detection, segmentation, pose, and depth on your own images in the live demo:

**[LibreYOLO live demo (Gradio)](https://huggingface.co/spaces/LibreYOLO/libreyolo-demo)**

## Links

[Website](https://www.libreyolo.com/) · [GitHub](https://github.com/LibreYOLO/libreyolo) · [Hugging Face](https://huggingface.co/LibreYOLO) · [Benchmarks (Vision Analysis)](https://www.visionanalysis.org/) · [LinkedIn](https://www.linkedin.com/company/libreyolo/) · [Reddit](https://www.reddit.com/r/LibreYOLO/)

---

MIT-licensed open-source computer vision. If you find it useful, a ⭐ on [GitHub](https://github.com/LibreYOLO/libreyolo) helps a lot.