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基于Pytorch的弱监督边框检测

requirements

  • Python3.6
  • pytorch0.4.0-gpu(注:不支持pytorch1.1.0)

Usage

  1. 下载预训练的模型,放在demo\models路径中。

[VGG16_ImageNet]

  1. 安装 SPN

    cd SPN/spnlib
    bash make.sh
  2. 运行程序:

    cd SPN.pytorch/demo
    bash runme.sh

    注:修改demo\experiment/demo_voc2007.py的--data参数为PascalVOC数据集的路径

  3. 测试:

    step 1: 按照上述1-3的步骤训练,或者下载训练好的模型,放在demo\logs\voc2007路径下。下载链接如下:

    [Our best model]

    step 2: 运行demo/test.py文件,生成预测的框

    step 3: MAP计算: 运行pascalvoc.py文件。

  4. 结果:

    Figure

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