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智能秤分析

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lee
2025-08-06 17:03:28 +08:00
parent 54898e30ec
commit 3392d76e38
17 changed files with 572 additions and 54 deletions
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20
configs/compare.yml
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@ -16,24 +16,24 @@ base:
# 模型配置
models:
backbone: 'resnet18'
channel_ratio: 0.75
channel_ratio: 1.0
# 训练参数
training:
epochs: 600 # 总训练轮次
epochs: 400 # 总训练轮次
batch_size: 128 # 批次大小
lr: 0.007 # 初始学习率
lr: 0.01 # 初始学习率
optimizer: "sgd" # 优化器类型
metric: 'arcface' # 损失函数类型（可选：arcface/cosface/sphereface/softmax）
loss: "cross_entropy" # 损失函数类型（可选：cross_entropy/cross_entropy_smooth/center_loss/center_loss_smooth/arcface/cosface/sphereface/softmax）
lr_step: 10 # 学习率调整间隔（epoch）
lr_step: 5 # 学习率调整间隔（epoch）
lr_decay: 0.95 # 学习率衰减率
weight_decay: 0.0005 # 权重衰减
scheduler: "cosine" # 学习率调度器（可选：cosine/cosine_warm/step/None）
scheduler: "step" # 学习率调度器（可选：cosine/cosine_warm/step/None）
num_workers: 32 # 数据加载线程数
checkpoints: "./checkpoints/resnet18_20250717_scale=0.75_nosub/" # 模型保存目录
restore: true
restore_model: "./checkpoints/resnet18_20250716_scale=0.75_nosub/best.pth" # 模型恢复路径
checkpoints: "./checkpoints/resnet18_electornic_20250806/" # 模型保存目录
restore: false
restore_model: "./checkpoints/resnet18_20250717_scale=0.75_nosub/best.pth" # 模型恢复路径
cosine_t_0: 10 # 初始周期长度
cosine_t_mult: 1 # 周期长度倍率
cosine_eta_min: 0.00001 # 最小学习率
@ -49,8 +49,8 @@ data:
train_batch_size: 128 # 训练批次大小
val_batch_size: 128 # 验证批次大小
num_workers: 32 # 数据加载线程数
data_train_dir: "../data_center/contrast_data/v2/train" # 训练数据集根目录
data_val_dir: "../data_center/contrast_data/v2/val" # 验证数据集根目录
data_train_dir: "../data_center/electornic/v1/train" # 训练数据集根目录
data_val_dir: "../data_center/electornic/v1/val" # 验证数据集根目录
transform:
img_size: 224 # 图像尺寸