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Undo yolo val

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Niels 2024-06-02 11:12:59 +02:00
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@ -65,9 +65,9 @@ python app.py
``` ```
## Validation ## Validation
[`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) [`yolov10n`](https://huggingface.co/jameslahm/yolov10n) [`yolov10s`](https://huggingface.co/jameslahm/yolov10s) [`yolov10m`](https://huggingface.co/jameslahm/yolov10m) [`yolov10b`](https://huggingface.co/jameslahm/yolov10b) [`yolov10l`](https://huggingface.co/jameslahm/yolov10l) [`yolov10x`](https://huggingface.co/jameslahm/yolov10x)
``` ```
yolo val size="nano" data=coco.yaml batch=256 yolo val model=yolov10n/s/m/b/l/x.pt data=coco.yaml batch=256
``` ```
Or Or
@ -76,7 +76,7 @@ from ultralytics import YOLOv10
model = YOLOv10('yolov10{n/s/m/b/l/x}.pt') model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
# or # or
model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}.pt') model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
model.val(data='coco.yaml', batch=256) model.val(data='coco.yaml', batch=256)
``` ```
@ -96,7 +96,7 @@ model = YOLOv10()
# pretrained weights like below # pretrained weights like below
# model = YOLOv10('yolov10{n/s/m/b/l/x}.pt') # model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
# Or # Or
# model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}.pt') # model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
model.train(data='coco.yaml', epochs=500, batch=256, imgsz=640) model.train(data='coco.yaml', epochs=500, batch=256, imgsz=640)
# Note that you can upload your trained model to HuggingFace Hub like below # Note that you can upload your trained model to HuggingFace Hub like below
@ -115,7 +115,7 @@ from ultralytics import YOLOv10
model = YOLOv10('yolov10{n/s/m/b/l/x}.pt') model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
# or # or
model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}.pt') model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
model.predict() model.predict()
``` ```