feat: 训练与评估入口及 yaml 配置
- train.py: 先过 require_cuda() 守卫再建模型/数据,支持 --resume 与 --set 覆盖 - eval.py: 允许 CPU,输出定位与分类指标并可写 json - configs: model/dataset/train/eval 四类,通过 `_base_` 组合; classes 既可直接写列表,也可指向 YOLO data.yaml 由框架读 names Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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Claude Opus 5
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_base_:
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- ./baseline.yaml
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- ../model/resnet18.yaml
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work_dir: runs/resnet18
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train:
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optimizer:
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lr: 0.0005
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