ai_bighw2's Introduction
程晔安 自72 2017011627 ## 使用说明 ## 1. 首先安装AdaBound 再将train.py中的import adabound解除注释就可以正常使用 2. 运行./data/data_process.py获得增强后的数据 3. 开始训练 python train.py 4. 进行模型融合 python ensemble.py 5. 结果在./submission中 实现详情见报告 ## 文件结构 ## - ensemble.py 模型融合文件 - train.py 训练文件 - report.pdf 报告文件 - ./data/: 数据文件夹, -- /original_data为题目给出的原数据, -- /aug_data为增强后的数据和切分成5折的数据 -- /data_process.py增强数据处理过程 - ./datasets 自己实现的数据集读入程序 - ./experiments 训练原模型保存处 - ./log 训练log保存处 - ./mymodels -- myDenseNet.py 自己实现的DenseNet -- myResNet.py 自己实现的ResNet -- utils.py 配合辅助文件 - ./pictures报告中的ROC图和loss图保存处 - ./results 用于之后模型融合的模型在测试集上的输出的文件 - ./submission 最后的上传kaggle文件保存处 - ./utils 其他工具程序 -- plot.py 画loss曲线程序 -- roc.py 画roc曲线程序
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