21 lines
1.3 KiB
YAML
21 lines
1.3 KiB
YAML
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train:
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- /workspace2/yolo_dataset/train_4_with_small_lab/train/images
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- /workspace2/yolo_dataset/2025-01-15-sea-salt_81/train/images
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val:
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- /workspace2/yolo_dataset/train_4_with_small_lab/valid/images
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- /workspace2/yolo_dataset/2025-01-15-sea-salt_81/valid/images
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nc: 80
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names: ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',
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'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
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'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
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'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
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'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
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'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
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'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
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'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
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'hair drier', 'toothbrush']
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# 全部预埋件数据重新训练
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# python train.py --data data/ymj_02-26.yaml --batch-size 32 --device=0 --epoch=50 --weights yolov5s.pt --imgsz 640
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