{"id":13642832,"url":"https://github.com/kadirnar/yolov6-pip","last_synced_at":"2025-04-13T08:43:32.285Z","repository":{"id":64938125,"uuid":"579765602","full_name":"kadirnar/yolov6-pip","owner":"kadirnar","description":"This repo is a packaged version of the Yolov6 model.","archived":false,"fork":false,"pushed_at":"2023-01-21T19:46:34.000Z","size":18174,"stargazers_count":4,"open_issues_count":2,"forks_count":2,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-27T00:22:33.362Z","etag":null,"topics":["computer-vision","object-detection","yolov6"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":["Other Versions of YOLO"],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\u003ch2\u003e\n  Yolov6-Pip: Packaged version of the Yolov6 repository  \n\u003c/h2\u003e\n\u003ch4\u003e\n    \u003cimg width=\"800\" alt=\"teaser\" src=\"docs/speed_comparision_v3.png\"\u003e\n\u003c/h4\u003e\n\u003cdiv\u003e\n    \u003ca href=\"https://pepy.tech/project/yolov6detect\"\u003e\u003cimg src=\"https://pepy.tech/badge/yolov6detect\" alt=\"downloads\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://badge.fury.io/py/yolov6detect\"\u003e\u003cimg src=\"https://badge.fury.io/py/yolov6detect.svg\" alt=\"pypi version\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://huggingface.co/spaces/kadirnar/yolov6\"\u003e\u003cimg src=\"https://img.shields.io/badge/%20HuggingFace%20-Demo-blue.svg\" alt=\"HuggingFace Spaces\"\u003e\u003c/a\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\n## \u003cdiv align=\"center\"\u003eOverview\u003c/div\u003e\n\nThis repo is a packaged version of the [Yolov6](https://github.com/meituan/YOLOv6/) model.\n## Benchmark\n| Model                                                        | Size | mAP\u003csup\u003eval\u003cbr/\u003e0.5:0.95 | Speed\u003csup\u003eT4\u003cbr/\u003etrt fp16 b1 \u003cbr/\u003e(fps) | Speed\u003csup\u003eT4\u003cbr/\u003etrt fp16 b32 \u003cbr/\u003e(fps) | Params\u003cbr/\u003e\u003csup\u003e (M) | FLOPs\u003cbr/\u003e\u003csup\u003e (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","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkadirnar%2Fyolov6-pip","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkadirnar%2Fyolov6-pip","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkadirnar%2Fyolov6-pip/lists"}