Instructions to use LibreYOLO/libreyolo-web with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LibreYOLO
How to use LibreYOLO/libreyolo-web with LibreYOLO:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
LibreYOLO Web β Model Zoo
Pre-exported ONNX models for libreyolo-web, the browser-based multi-family YOLO detection library.
Usage
npm install libreyolo-web onnxruntime-web
import { loadModel } from 'libreyolo-web';
// Auto-downloads from this repo, zero config
const model = await loadModel('yolox-nano');
const result = await model.predict(imageElement);
Available Models
YOLOX (letterbox + BGR + 0-255)
| Name | Input | Size | File |
|---|---|---|---|
yolox-nano |
416 | 3.6MB | yolox_n.onnx |
yolox-tiny |
416 | 19MB | yolox_t.onnx |
yolox-small |
640 | 34MB | yolox_s.onnx |
yolox-medium |
640 | 97MB | yolox_m.onnx |
yolox-large |
640 | 207MB | yolox_l.onnx |
yolox-xlarge |
640 | 378MB | yolox_x.onnx |
YOLO9 (resize + RGB + /255)
| Name | Input | Size | File |
|---|---|---|---|
yolo9-tiny |
640 | 8MB | yolo9_t.onnx |
yolo9-small |
640 | 28MB | yolo9_s.onnx |
yolo9-medium |
640 | 77MB | yolo9_m.onnx |
yolo9-compact |
640 | 97MB | yolo9_c.onnx |
RF-DETR (resize + ImageNet norm, no NMS)
| Name | Input | Size | File |
|---|---|---|---|
rfdetr-nano |
384 | 103MB | rfdetr_n.onnx |
rfdetr-small |
512 | 109MB | rfdetr_s.onnx |
rfdetr-medium |
576 | 115MB | rfdetr_m.onnx |
rfdetr-large |
704 | 116MB | rfdetr_l.onnx |
Training
All models were trained on COCO using libreyolo (Python) and exported to ONNX with model.export(format='onnx', simplify=True).
License
MIT