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- from ultralytics import YOLO
- if __name__ == "__main__":
- model = YOLO('yolov12n.yaml')
- model.load("yolov12n.pt")
- # Train the model
- results = model.train(
- data='/Users/jsonxu/code/ai/train/6017/data.yaml',
- project='/Users/jsonxu/code/ai/train/6017', # 训练结果路径
- name='result',# 训练结果名称
- exist_ok=True, #如果为 True，则允许覆盖现有的项目/名称目录。这对迭代实验非常有用，无需手动清除之前的输出。
- epochs=1,
- batch=16,
- imgsz=640,
- scale=0.5, # S:0.9; M:0.9; L:0.9; X:0.9
- mosaic=1.0,
- mixup=0.0, # S:0.05; M:0.15; L:0.15; X:0.2
- copy_paste=0.1, # S:0.15; M:0.4; L:0.5; X:0.6
- )
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