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--- |
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license: gpl-3.0 |
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tags: |
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- object-detection |
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- computer-vision |
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- yolov6 |
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- pypi |
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datasets: |
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- detection-datasets/coco |
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--- |
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### Model Description |
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[YOLOv6:](https://arxiv.org/abs/2209.02976) A single-stage object detection framework dedicated to industrial applications. |
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[YOLOv6 v3.0](https://arxiv.org/abs/2301.05586): A Full-Scale Reloading |
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[YOLOv6-Pip: Packaged version of the Yolov6 repository](https://github.com/kadirnar/yolov6-pip/) |
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[Paper Repo: Implementation of paper - YOLOv6](https://github.com/meituan/YOLOv6/) |
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### Installation |
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``` |
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pip install yolov6detect |
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``` |
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### Yolov6 Inference |
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```python |
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from yolov6 import YOLOV6 |
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model = YOLOV6(weights='kadirnar/yolov6s-v2.0', device='cuda:0', hf_model=True) |
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model.classes = None |
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model.conf = 0.25 |
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model.iou = 0.45 |
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model.show = False |
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model.save = True |
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pred = model.predict(source='data/images',yaml='data/coco.yaml', img_size=640) |
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``` |
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### BibTeX Entry and Citation Info |
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``` |
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@article{li2022yolov6, |
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title={YOLOv6: A single-stage object detection framework for industrial applications}, |
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author={Li, Chuyi and Li, Lulu and Jiang, Hongliang and Weng, Kaiheng and Geng, Yifei and Li, Liang and Ke, Zaidan and Li, Qingyuan and Cheng, Meng and Nie, Weiqiang and others}, |
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journal={arXiv preprint arXiv:2209.02976}, |
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year={2022} |
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} |
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``` |
