54 lines
2.1 KiB
YAML
54 lines
2.1 KiB
YAML
# configs/similar_analysis.yml
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# 专为模型训练对比设计的配置文件
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# 支持对比不同训练策略（如蒸馏vs独立训练）
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# 基础配置
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base:
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experiment_name: "model_comparison" # 实验名称（用于结果保存目录）
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device: "cuda" # 训练设备（cuda/cpu）
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embedding_size: 256 # 特征维度
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pin_memory: true # 是否启用pin_memory
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distributed: true # 是否启用分布式训练
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# 模型配置
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models:
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backbone: 'resnet18'
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channel_ratio: 0.75
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model_path: "../checkpoints/resnet18_1009/best.pth"
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heatmap:
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feature_layer: "layer4"
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show_heatmap: true
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# 数据配置
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data:
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dataset: "imagenet" # 数据集名称（示例用，可替换为实际数据集）
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train_batch_size: 128 # 训练批次大小
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val_batch_size: 8 # 验证批次大小
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num_workers: 32 # 数据加载线程数
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data_dir: "/home/lc/data_center/image_analysis/error_compare_subimg"
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image_joint_pth: "/home/lc/data_center/image_analysis/error_compare_result"
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transform:
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img_size: 224 # 图像尺寸
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img_mean: 0.5 # 图像均值
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img_std: 0.5 # 图像方差
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RandomHorizontalFlip: 0.5 # 随机水平翻转概率
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RandomRotation: 180 # 随机旋转角度
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ColorJitter: 0.5 # 随机颜色抖动强度
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# 日志与监控
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logging:
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logging_dir: "./logs/resnet18_scale=0.75_nosub_log" # 日志保存目录
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tensorboard: true # 是否启用TensorBoard
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checkpoint_interval: 30 # 检查点保存间隔（epoch）
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event:
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oneToOneTxt: "/home/lc/detecttracking/oneToOne.txt"
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oneToSnTxt: "/home/lc/detecttracking/oneToSn.txt"
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oneToOne_max_th: 0.9
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oneToSn_min_th: 0.6
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event_save_dir: "/home/lc/works/realtime_yolov10s/online_yolov10s_resnetv11_20250702/yolos_tracking"
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stdlib_image_path: "/testDataAndLogs/module_test_record/comparison/标准图测试数据/pic/stlib_base"
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pickle_path: "event.pickle"
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