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| card_template_text = """ | |
| --- | |
| license: agpl-3.0 | |
| library_name: ultralytics | |
| repo_url: https://github.com/THU-MIG/yolov10 | |
| tags: | |
| - object-detection | |
| - computer-vision | |
| - yolov10 | |
| datasets: | |
| - detection-datasets/coco | |
| inference: false | |
| --- | |
| ### Model Description | |
| [YOLOv10: Real-Time End-to-End Object Detection](https://arxiv.org/abs/2405.14458v1) | |
| - arXiv: https://arxiv.org/abs/2405.14458v1 | |
| - github: https://github.com/THU-MIG/yolov10 | |
| ### Installation | |
| ``` | |
| pip install git+https://github.com/THU-MIG/yolov10.git | |
| ``` | |
| ### Training and validation | |
| ```python | |
| from ultralytics import YOLOv10 | |
| model = YOLOv10.from_pretrained('jameslahm/yolov10n') | |
| # Training | |
| model.train(...) | |
| # after training, one can push to the hub | |
| model.push_to_hub("your-hf-username/yolov10-finetuned") | |
| # Validation | |
| model.val(...) | |
| ``` | |
| ### Inference | |
| Here's an end-to-end example showcasing inference on a cats image: | |
| ```python | |
| from ultralytics import YOLOv10 | |
| model = YOLOv10.from_pretrained('jameslahm/yolov10n') | |
| source = 'http://images.cocodataset.org/val2017/000000039769.jpg' | |
| model.predict(source=source, save=True) | |
| ``` | |
| which shows: | |
|  | |
| ### BibTeX Entry and Citation Info | |
| ``` | |
| @article{wang2024yolov10, | |
| title={YOLOv10: Real-Time End-to-End Object Detection}, | |
| author={Wang, Ao and Chen, Hui and Liu, Lihao and Chen, Kai and Lin, Zijia and Han, Jungong and Ding, Guiguang}, | |
| journal={arXiv preprint arXiv:2405.14458}, | |
| year={2024} | |
| } | |
| ``` | |
| """.strip() |