Shaun ZhouandClaude Opus 5
b0d0dfffbb
- 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>
19 lines
447 B
YAML
19 lines
447 B
YAML
# 自研轻量骨架：backbone stride 16 + 2 次上采样 => 输出 stride 4。
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model:
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name: defect_net
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backbone:
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name: tiny_conv
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in_channels: 3
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widths: [32, 64, 128, 256]
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depths: [1, 2, 2, 2]
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block: dw # dw=深度可分离(更快) / res=残差(更强)
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neck:
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name: upsample
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channels: 64
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num_upsamples: 2
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head:
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hidden_channels: 64
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with_classification: true
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classification:
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dropout: 0.1
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