Push model using huggingface_hub.
Browse files- README.md +62 -0
- config.json +86 -0
- model.safetensors +3 -0
README.md
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---
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license: agpl-3.0
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library_name: ultralytics
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tags:
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- object-detection
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- computer-vision
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- yolov10
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datasets:
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- detection-datasets/coco
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repo_url: https://github.com/THU-MIG/yolov10
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inference: false
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---
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### Model Description
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[YOLOv10: Real-Time End-to-End Object Detection](https://arxiv.org/abs/2405.14458v1)
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- arXiv: https://arxiv.org/abs/2405.14458v1
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- github: https://github.com/THU-MIG/yolov10
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### Installation
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```
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pip install git+https://github.com/THU-MIG/yolov10.git
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```
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### Training and validation
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```python
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from ultralytics import YOLOv10
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model = YOLOv10.from_pretrained('jameslahm/yolov10n')
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# Training
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model.train(...)
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# after training, one can push to the hub
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model.push_to_hub("your-hf-username/yolov10-finetuned")
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# Validation
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model.val(...)
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```
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### Inference
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Here's an end-to-end example showcasing inference on a cats image:
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```python
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from ultralytics import YOLOv10
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model = YOLOv10.from_pretrained('jameslahm/yolov10n')
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source = 'http://images.cocodataset.org/val2017/000000039769.jpg'
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model.predict(source=source, save=True)
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```
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which shows:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/628ece6054698ce61d1e7be3/tBwAsKcQA_96HCYQp7BRr.png)
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### BibTeX Entry and Citation Info
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```
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@article{wang2024yolov10,
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title={YOLOv10: Real-Time End-to-End Object Detection},
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author={Wang, Ao and Chen, Hui and Liu, Lihao and Chen, Kai and Lin, Zijia and Han, Jungong and Ding, Guiguang},
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journal={arXiv preprint arXiv:2405.14458},
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year={2024}
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}
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```
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config.json
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{
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"model": "yolov10n.yaml",
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"names": {
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"0": "person",
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"1": "bicycle",
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"2": "car",
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"3": "motorcycle",
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"4": "airplane",
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"5": "bus",
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"6": "train",
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"7": "truck",
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"8": "boat",
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"9": "traffic light",
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"10": "fire hydrant",
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"11": "stop sign",
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"12": "parking meter",
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"13": "bench",
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"14": "bird",
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"15": "cat",
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"16": "dog",
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"17": "horse",
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"18": "sheep",
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"19": "cow",
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"20": "elephant",
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"21": "bear",
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"22": "zebra",
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"23": "giraffe",
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"24": "backpack",
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"25": "umbrella",
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"26": "handbag",
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"27": "tie",
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"28": "suitcase",
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"29": "frisbee",
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"30": "skis",
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"31": "snowboard",
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"32": "sports ball",
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"33": "kite",
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"34": "baseball bat",
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"35": "baseball glove",
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"36": "skateboard",
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"37": "surfboard",
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"38": "tennis racket",
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"39": "bottle",
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"40": "wine glass",
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"41": "cup",
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"42": "fork",
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"43": "knife",
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"44": "spoon",
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"45": "bowl",
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"46": "banana",
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"47": "apple",
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"48": "sandwich",
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"49": "orange",
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"50": "broccoli",
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"51": "carrot",
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"52": "hot dog",
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"53": "pizza",
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"54": "donut",
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"55": "cake",
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"56": "chair",
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"57": "couch",
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"58": "potted plant",
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"59": "bed",
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"60": "dining table",
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"61": "toilet",
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"62": "tv",
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"63": "laptop",
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"64": "mouse",
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"65": "remote",
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"66": "keyboard",
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"67": "cell phone",
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"68": "microwave",
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"69": "oven",
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"70": "toaster",
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"71": "sink",
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"72": "refrigerator",
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"73": "book",
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"74": "clock",
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"75": "vase",
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"76": "scissors",
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"77": "teddy bear",
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"78": "hair drier",
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"79": "toothbrush"
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},
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"task": "detect"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:98e5b4d81a20d1e8a972cd0be947944838ccd61f7f7e61828349a647d3607433
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size 11245792
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