https://github.com/wkentaro/yolo-world-onnx
ONNX models of YOLO-World (an open-vocabulary object detection).
https://github.com/wkentaro/yolo-world-onnx
computer-vision deep-learning foundation-models object-detection
Last synced: 6 months ago
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ONNX models of YOLO-World (an open-vocabulary object detection).
- Host: GitHub
- URL: https://github.com/wkentaro/yolo-world-onnx
- Owner: wkentaro
- License: gpl-3.0
- Created: 2024-06-16T06:53:41.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-06-29T00:53:49.000Z (over 1 year ago)
- Last Synced: 2025-03-28T21:01:47.459Z (7 months ago)
- Topics: computer-vision, deep-learning, foundation-models, object-detection
- Language: Python
- Homepage:
- Size: 2.9 MB
- Stars: 18
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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## ONNX Models
[Download](https://github.com/wkentaro/yolo-world-onnx/releases/latest)
## Installation
Option 1: Install all for PyTorch inference, export, and ONNX inference:
```
make install
```Option 2: Install only for ONNX inference:
```
make install_for_onnx
```## Usage
### Inference with PyTorch
Run inference using the PyTorch pre-trained model:
```
./infer_pytorch.py
./infer_pytorch.py --class-names person,shoes
./infer_pytorch.py --image-file data/images/dogs.jpg \
--class-names dog,eye,nose,ear,tail \
--iou-threshold 0.5 \
--score-threshold 0.09
```### Export ONNX
Export YOLO-World and NMS models to ONNX format:
```
./export_onnx.py
./export_nms_onnx.py
```### Inference with ONNX
Run inference using the exported ONNX model:
```
./infer_onnx.py
./infer_onnx.py --class-names person,shoes
./infer_onnx.py --image-file data/images/dogs.jpg \
--class-names dog,eye,nose,ear,tail \
--iou-threshold 0.5 \
--score-threshold 0.09
```## Acknowledgements
YOLO-World is an open-vocabulary object detection model published in CVPR2024.
Check out the following resources for more information: [Paper](https://arxiv.org/abs/2401.17270), [Code](https://github.com/AILab-CVC/YOLO-World)
## License
GPLv3