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RoRD-Layout-Recognation/configs/base_config.yaml

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