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21 lines
1.1 KiB
Python
21 lines
1.1 KiB
Python
from ultralytics import YOLOv10
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# model = YOLOv10()
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#model = YOLOv10('ultralytics/cfg/models/v10/yolov10s.yaml')
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#model = YOLOv10('runs/detect/runs_1010_1205_width0.375/weights/last.pt')
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#model = YOLOv10('runs/detect/train4/weights/last.pt')
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model = YOLOv10('ckpts/weights/yolov10n.pt')
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# If you want to finetune the model with pretrained weights, you could load the
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# pretrained weights like below
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# model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
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# or
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# wget https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10{n/s/m/b/l/x}.pt
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# model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
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# model = YOLOv10('yolov10s.pt')
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#model.train(data='coco.yaml', epochs=1, batch=64, imgsz=640)
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#model.train(data='coco128_cls10_0924.yaml', epochs=300, batch=64, imgsz=640, resume=False)
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#model.train(data='coco128_cls10_1010.yaml', epochs=300, batch=128, imgsz=640, resume=False)
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model.train(data='gift.yaml', epochs=400, batch=32, imgsz=224, resume=False, save_dir='/ckpts')
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#model.train(data='coco128_cls10_1010_1205.yaml', epochs=300, batch=32, imgsz=640, resume=True) |