DeepLabv3+水稻稻穗语义分割模型在Pytorch当中的实现

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DeepLabv3+水稻稻穗语义分割模型在Pytorch当中的实现 ### 目录 1. [性能情况 Performance](#性能情况) 2. [所需环境 Environment](#所需环境) 3. [注意事项 Attention](#注意事项) 4. [文件下载 Download](#文件下载) 5. [训练步骤 How2train](#训练步骤) 6. [预测步骤 How2predict](#预测步骤) 7. [评估步骤 miou](#评估步骤) 8. [参考资料 Reference](#Reference) ### 所需环境 torch==1.2.0 ### 注意事项 代码中的deeplab_mobilenetv2.pth和deeplab_xception.pth是基于VOC拓展数据集训练的。训练和预测时注意修改backbone。 ### 训练步骤 #### a、训练voc数据集 1、将我提供的voc数据集放入VOCdevkit中(无需运行voc_annotation.py)。 有问题请关注私聊,包此代码的答疑服务,基本秒回,不满意加球球包退款,可接受定制服务

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( 7633 个子文件 376.6MB ) DeepLabv3+水稻稻穗语义分割模型在Pytorch当中的实现
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