Question

我使用Caffe训练了一个神经网络模型：

/home/f/caffe-master/build/tools/caffe train -solver=/media/my_solver.prototxt

然后我在验证集上对学习模型进行了评分：

/home/f/caffe-master/build/tools/caffe test -model=/media/my_train_test.prototxt 
                                            -weights model.caffemodel -iterations 100

但是如何在Caffe中获得经过训练的神经网络模型预测的标签？

我知道我可以为此目的使用Python或Matlab绑定，但我很想知道我们是否可以直接通过命令行界面获取Caffe中的预测标签。

official Caffe's tutorial on interfaces似乎没有提到它，看caffe的帮助没有帮助：

> f@f-VirtualBox:~/caffe/caffe-master/build/tools$ ./caffe
caffe: command line brew
usage: caffe <command> <args>

commands:
  train           train or finetune a model
  test            score a model
  device_query    show GPU diagnostic information
  time            benchmark model execution time

  Flags from /home/f/caffe-master/tools/caffe.cpp:
    -gpu (Run in GPU mode on given device ID.) type: int32 default: -1
    -iterations (The number of iterations to run.) type: int32 default: 50
    -model (The model definition protocol buffer text file..) type: string
      default: ""
    -snapshot (Optional; the snapshot solver state to resume training.)
      type: string default: ""
    -solver (The solver definition protocol buffer text file.) type: string
      default: ""
    -weights (Optional; the pretrained weights to initialize finetuning. Cannot
      be set simultaneously with snapshot.) type: string default: ""

Answer 1

如果您不想浏览Python，可以添加HDF5_OUTPUT图层：它会将预测输出保存在HDF5文件中。

否则，如果您想加入代码，可以在https://github.com/BVLC/caffe/blob/master/src/caffe/layers/accuracy_layer.cpp#L74附近打印或保存bottom_data_vector[k].second

如何通过CLI在Caffe中生成预测标签？

1 个答案: