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First draft
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README.md
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README.md
@ -43,12 +43,12 @@ COCO
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| Model | Test Size | #Params | FLOPs | AP<sup>val</sup> | Latency |
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|:---------------|:----:|:---:|:--:|:--:|:--:|
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| [YOLOv10-N](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10n.pt) | 640 | 2.3M | 6.7G | 38.5% | 1.84ms |
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| [YOLOv10-S](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10s.pt) | 640 | 7.2M | 21.6G | 46.3% | 2.49ms |
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| [YOLOv10-M](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10m.pt) | 640 | 15.4M | 59.1G | 51.1% | 4.74ms |
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| [YOLOv10-B](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10b.pt) | 640 | 19.1M | 92.0G | 52.5% | 5.74ms |
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| [YOLOv10-L](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10l.pt) | 640 | 24.4M | 120.3G | 53.2% | 7.28ms |
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| [YOLOv10-X](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10x.pt) | 640 | 29.5M | 160.4G | 54.4% | 10.70ms |
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| [YOLOv10-N](https://huggingface.co/jameslahm/yolov10n) | 640 | 2.3M | 6.7G | 38.5% | 1.84ms |
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| [YOLOv10-S](https://huggingface.co/jameslahm/yolov10s) | 640 | 7.2M | 21.6G | 46.3% | 2.49ms |
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| [YOLOv10-M](https://huggingface.co/jameslahm/yolov10m) | 640 | 15.4M | 59.1G | 51.1% | 4.74ms |
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| [YOLOv10-B](https://huggingface.co/jameslahm/yolov10b) | 640 | 19.1M | 92.0G | 52.5% | 5.74ms |
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| [YOLOv10-L](https://huggingface.co/jameslahm/yolov10l) | 640 | 24.4M | 120.3G | 53.2% | 7.28ms |
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| [YOLOv10-X](https://huggingface.co/jameslahm/yolov10x) | 640 | 29.5M | 160.4G | 54.4% | 10.70ms |
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## Installation
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`conda` virtual environment is recommended.
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@ -60,15 +60,14 @@ pip install -e .
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```
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## Demo
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```
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wget https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10s.pt
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python app.py
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# Please visit http://127.0.0.1:7860
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```
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## Validation
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[`yolov10n.pt`](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10n.pt) [`yolov10s.pt`](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10s.pt) [`yolov10m.pt`](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10m.pt) [`yolov10b.pt`](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10b.pt) [`yolov10l.pt`](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10l.pt) [`yolov10x.pt`](https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10x.pt)
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[`yolov10n.pt`](https://huggingface.co/jameslahm/yolov10n) [`yolov10s.pt`](https://huggingface.co/jameslahm/yolov10s) [`yolov10m.pt`](https://huggingface.co/jameslahm/yolov10m) [`yolov10b.pt`](https://huggingface.co/jameslahm/yolov10b) [`yolov10l.pt`](https://huggingface.co/jameslahm/yolov10l) [`yolov10x.pt`](https://huggingface.co/jameslahm/yolov10x)
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```
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yolo val model=yolov10n/s/m/b/l/x.pt data=coco.yaml batch=256
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yolo val size="nano" data=coco.yaml batch=256
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```
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## Training
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app.py
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app.py
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import gradio as gr
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from ultralytics import YOLOv10
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def yolov10_inference(image, model_path, image_size, conf_threshold):
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model = YOLOv10(model_path)
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def yolov10_inference(image, image_size, conf_threshold):
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model = YOLOv10.from_pretrained("jameslahm/yolov10n")
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model.predict(source=image, imgsz=image_size, conf=conf_threshold, save=True)
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