75 lines
1.8 KiB
YAML
75 lines
1.8 KiB
YAML
training:
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learning_rate: 5.0e-5
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batch_size: 8
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num_epochs: 50
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patch_size: 256
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scale_jitter_range: [0.8, 1.2]
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model:
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fpn:
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enabled: true
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out_channels: 256
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levels: [2, 3, 4]
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norm: "bn"
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# 新增：可切换骨干网络配置（默认为 vgg16，保持与现有实现一致）
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backbone:
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name: "vgg16" # 可选：vgg16 | resnet34 | efficientnet_b0
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pretrained: false # 是否加载 ImageNet 预训练权重（如可用）
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# 新增：可选注意力机制（默认关闭，避免影响现有结果）
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attention:
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enabled: false
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type: "none" # 可选：none | cbam | se
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places: [] # 插入位置：backbone_high | det_head | desc_head（数组）
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matching:
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keypoint_threshold: 0.5
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ransac_reproj_threshold: 5.0
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min_inliers: 15
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pyramid_scales: [0.75, 1.0, 1.5]
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inference_window_size: 1024
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inference_stride: 768
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use_fpn: true
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nms:
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enabled: true
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radius: 4
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score_threshold: 0.5
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evaluation:
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iou_threshold: 0.5
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logging:
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use_tensorboard: true
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log_dir: "runs"
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experiment_name: "baseline"
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paths:
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layout_dir: "path/to/layouts"
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save_dir: "path/to/save"
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val_img_dir: "path/to/val/images"
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val_ann_dir: "path/to/val/annotations"
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template_dir: "path/to/templates"
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model_path: "path/to/save/model_final.pth"
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# 数据增强与合成数据配置（可选）
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augment:
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elastic:
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enabled: false
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alpha: 40
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sigma: 6
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alpha_affine: 6
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prob: 0.3
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photometric:
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brightness_contrast: true
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gauss_noise: true
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synthetic:
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enabled: false
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png_dir: "data/synthetic/png"
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ratio: 0.0 # 0~1，训练时混合的合成样本比例
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diffusion:
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enabled: false
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png_dir: "data/synthetic_diff/png"
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ratio: 0.0 # 0~1，训练时混合的扩散样本比例
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