<div align="center">
<h2>
Yolov6-Pip: Packaged version of the Yolov6 repository
</h2>
<h4>
<img width="800" alt="teaser" src="docs/speed_comparision_v3.png">
</h4>
<div>
<a href="https://pepy.tech/project/yolov6detect"><img src="https://pepy.tech/badge/yolov6detect" alt="downloads"></a>
<a href="https://badge.fury.io/py/yolov6detect"><img src="https://badge.fury.io/py/yolov6detect.svg" alt="pypi version"></a>
<a href="https://huggingface.co/spaces/kadirnar/yolov6"><img src="https://img.shields.io/badge/%20HuggingFace%20-Demo-blue.svg" alt="HuggingFace Spaces"></a>
</div>
</div>
## <div align="center">Overview</div>
This repo is a packaged version of the [Yolov6](https://github.com/meituan/YOLOv6/) model.
## Benchmark
| Model | Size | mAP<sup>val<br/>0.5:0.95 | Speed<sup>T4<br/>trt fp16 b1 <br/>(fps) | Speed<sup>T4<br/>trt fp16 b32 <br/>(fps) | Params<br/><sup> (M) | FLOPs<br/><sup> (G) |
| :----------------------------------------------------------- | ---- | :----------------------- | --------------------------------------- | ---------------------------------------- | -------------------- | ------------------- |
| [**YOLOv6-N**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6n.pt) | 640 | 37.5 | 779 | 1187 | 4.7 | 11.4 |
| [**YOLOv6-S**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6s.pt) | 640 | 45.0 | 339 | 484 | 18.5 | 45.3 |
| [**YOLOv6-M**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6m.pt) | 640 | 50.0 | 175 | 226 | 34.9 | 85.8 |
| [**YOLOv6-L**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6l.pt) | 640 | 52.8 | 98 | 116 | 59.6 | 150.7 |
| | | | | |
| [**YOLOv6-N6**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6n6.pt) | 1280 | 44.9 | 228 | 281 | 10.4 | 49.8 |
| [**YOLOv6-S6**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6s6.pt) | 1280 | 50.3 | 98 | 108 | 41.4 | 198.0 |
| [**YOLOv6-M6**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6m6.pt) | 1280 | 55.2 | 47 | 55 | 79.6 | 379.5 |
| [**YOLOv6-L6**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6l6.pt) | 1280 | 57.2 | 26 | 29 | 140.4 | 673.4 |
### Installation
```
pip install yolov6detect
```
### Yolov6 Inference
```python
from yolov6 import YOLOV6
model = YOLOV6(weights='yolov6s.pt', device='cuda:0')
#model = YOLOV6(weights='kadirnar/yolov6t-v2.0', device='cuda:0', hf_model=True)
model.classes = None
model.conf = 0.25
model.iou_ = 0.45
model.show = False
model.save = True
pred = model.predict(source='data/images',yaml='data/coco.yaml', img_size=640)
```
### Citation
```bibtex
@article{li2022yolov6,
title={YOLOv6: A single-stage object detection framework for industrial applications},
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},
journal={arXiv preprint arXiv:2209.02976},
year={2022}
}
```
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"description": "<div align=\"center\">\n<h2>\n Yolov6-Pip: Packaged version of the Yolov6 repository \n</h2>\n<h4>\n <img width=\"800\" alt=\"teaser\" src=\"docs/speed_comparision_v3.png\">\n</h4>\n<div>\n <a href=\"https://pepy.tech/project/yolov6detect\"><img src=\"https://pepy.tech/badge/yolov6detect\" alt=\"downloads\"></a>\n <a href=\"https://badge.fury.io/py/yolov6detect\"><img src=\"https://badge.fury.io/py/yolov6detect.svg\" alt=\"pypi version\"></a>\n <a href=\"https://huggingface.co/spaces/kadirnar/yolov6\"><img src=\"https://img.shields.io/badge/%20HuggingFace%20-Demo-blue.svg\" alt=\"HuggingFace Spaces\"></a>\n</div>\n</div>\n\n## <div align=\"center\">Overview</div>\n\nThis repo is a packaged version of the [Yolov6](https://github.com/meituan/YOLOv6/) model.\n## Benchmark\n| Model | Size | mAP<sup>val<br/>0.5:0.95 | Speed<sup>T4<br/>trt fp16 b1 <br/>(fps) | Speed<sup>T4<br/>trt fp16 b32 <br/>(fps) | Params<br/><sup> (M) | FLOPs<br/><sup> (G) |\n| :----------------------------------------------------------- | ---- | :----------------------- | --------------------------------------- | ---------------------------------------- | -------------------- | ------------------- |\n| [**YOLOv6-N**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6n.pt) | 640 | 37.5 | 779 | 1187 | 4.7 | 11.4 |\n| [**YOLOv6-S**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6s.pt) | 640 | 45.0 | 339 | 484 | 18.5 | 45.3 |\n| [**YOLOv6-M**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6m.pt) | 640 | 50.0 | 175 | 226 | 34.9 | 85.8 |\n| [**YOLOv6-L**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6l.pt) | 640 | 52.8 | 98 | 116 | 59.6 | 150.7 |\n| | | | | |\n| [**YOLOv6-N6**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6n6.pt) | 1280 | 44.9 | 228 | 281 | 10.4 | 49.8 |\n| [**YOLOv6-S6**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6s6.pt) | 1280 | 50.3 | 98 | 108 | 41.4 | 198.0 |\n| [**YOLOv6-M6**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6m6.pt) | 1280 | 55.2 | 47 | 55 | 79.6 | 379.5 |\n| [**YOLOv6-L6**](https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6l6.pt) | 1280 | 57.2 | 26 | 29 | 140.4 | 673.4 |\n### Installation\n```\npip install yolov6detect\n```\n\n### Yolov6 Inference\n```python\nfrom yolov6 import YOLOV6\n\nmodel = YOLOV6(weights='yolov6s.pt', device='cuda:0') \n#model = YOLOV6(weights='kadirnar/yolov6t-v2.0', device='cuda:0', hf_model=True)\n\nmodel.classes = None\nmodel.conf = 0.25\nmodel.iou_ = 0.45\nmodel.show = False\nmodel.save = True\n\npred = model.predict(source='data/images',yaml='data/coco.yaml', img_size=640)\n```\n### Citation\n```bibtex\n@article{li2022yolov6,\n title={YOLOv6: A single-stage object detection framework for industrial applications},\n 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},\n journal={arXiv preprint arXiv:2209.02976},\n year={2022}\n}\n```\n",
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