Efficientnet_pytorch_cbam_gui

上传者: 42138545 | 上传时间: 2021-09-14 14:17:37 | 文件大小: 357KB | 文件类型: ZIP
海洋生物分类 代码说明 pip-requirements.txt 需要安装的库 convert_dataset.py 整理csv文件格式的数据集 creat_map.py 生成对应的标签映射 train.py 训练主函数 test_one.py 利用训练好的模型预测一张图片 test_all.py 预测整个test文件里的图片 test_tta. py 预测时加入tta,但是实际效果不好,不知道哪里出了问题 sys_gui .py 运行时生成界面,可实现单张图片的读取,以及对单张图片的预测 训练方案 模型方面采用的是efficientnet-b5,在原始b5模型中增加了cbam注意力模块,数据增强方面使用了随机裁切、翻转、auto_augment、随机擦除以及cutmix, 损失函数采用CrossEntropyLabelSmooth,训练策略方面采用了快照集成(snapshot)思想。 第

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