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deep-head-pose

该项目是头部朝向模型的训练和测试

文件结构

  • checkpoints : 模型训练过程中保存的文件
  • datasets
    • 数据处理过程中用到的一些代码
    • filenamelists: 300W_LP和AFLW2000的文件名列表文件,一般用disgard版本,里面舍弃了角度在-99~99度以外的数据(论文的做法)
  • models
    • 模型参数文件,包含了已经训练好的一些模型,hopenet*.pkl的模型是官方发布的模型,resnet50_epoch_4.pkl是我们重新训练的最好的模型, 测试结果上,也是这四个模型中最优的
  • network
    • HopeNet 网络定义
  • test
    • 不同的测试方法: 1. 在公开数据集上的测试 2. 在video上的测试 3. 调用 detector 进行多人脸测试
  • main.py : 训练的主文件,加入了分布式,训练参数可以参考代码文件
  • tester.py :测试代码,测试参数可以参考代码文件
  • train_test.sh: 训练、测试脚本,可根据需要修改该脚本的参数来进行训练测试

环境依赖

  • pytorch 1.0

运行

运行train_test.sh脚本即可

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