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ModelTrainEval/configs/model/resnet18.yaml
T
Shaun ZhouandClaude Opus 5 b0d0dfffbb 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>
2026-09-02 17:55:20 +08:00

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# torchvision resnet18:stride 32 + 3 次上采样 => 输出 stride 4。
model:
name: defect_net
backbone:
name: torchvision
arch: resnet18
pretrained: true
in_channels: 3
neck:
name: upsample
channels: 64
num_upsamples: 3
head:
hidden_channels: 64
with_classification: true