如何在caffe中提取图层的blob信息？

Question

我用caffe为我的机器学习C++。

作为net_->Forward();通过网络后，我喜欢提取单个图层的信息。

我所做的是

  net_->Forward(); 

      //Extract layer information 
      cout << "Num layers:" << "'" << net_->layer_names().size() << "'"<< endl; 
      for (int layer_index = 0; layer_index < net_->layer_names().size(); ++layer_index) 
      { 
       // get that layer blob and its dimension 
       const boost::shared_ptr<Blob<float> > blob = net_->blob_by_name(net_->blob_names()[layer_index]); 
       int batch_size = blob->num();     
       int dim_features = blob->count()/batch_size; 
       std::cout << "Layer name:" << "'" << net_->layer_names()[layer_index] << "'" << " Blob name:" << "'" <<net_->blob_names()[layer_index] << "'" << " batch size " << "'" << batch_size << "'" << " dim_features:" << "'" << dim_features << "'" << std::endl; 
      } 

我可以看到所有的图层名称和尺寸。

Layer name'image' Blob name'image' batch_size'1' dim_features'921600' 
Layer name'conv1/7x7_s2' Blob name'conv1/7x7_s2' batch_size'1' dim_features'4915200' 
Layer name'conv1/relu_7x7' Blob name'pool1/3x3_s2' batch_size'1' dim_features'1228800' 
Layer name'pool1/3x3_s2' Blob name'pool1/norm1' batch_size'1' dim_features'1228800' 
Layer name'pool1/norm1' Blob name'conv2/3x3_reduce' batch_size'1' dim_features'1228800' 
Layer name'conv2/3x3_reduce' Blob name'conv2/3x3' batch_size'1' dim_features'3686400' 
Layer name'conv2/relu_3x3_reduce' Blob name'conv2/norm2' batch_size'1' dim_features'3686400' 

但是在这里我仍然需要更深入的信息。

当前尺寸是921600，即组成批量大小x通道×高度×宽度=的921600.

（1）因此，我的第一查询是如何分割的信息？

（2）说我有此信息的批量大小x通道×高度×宽度= 1×3×480×640然后

如何在像1×1×480×640的blob提取每个层，这样我可以打印或者我可以绘图。

这种事情，我可以在Python做这样

for layer_name, blob in net.blobs.iteritems(): 
     print layer_name + '\t' + str(blob.data.shape) 
      mydata = net.blobs[layer_name].data[0,0,:,:] 
      #cv2.imshow("mydata",mydata); 
      #cv2.waitKey(1) 
      layer_name = layer_name.replace('/', '_') 
      np.savetxt("printdata/"+layer_name+".csv", mydata, delimiter=",") 

但现在，我想在C++做。

Answer 1

问题1：

如果你看看blob.hpp文件时，它有几个方法来获取BLOB的尺寸。您可以拨打shape()或返回const vector<int>&或者不推荐使用的方法，如num(),channels(),height(),width()返回int。因此，对于你的情况应该是这样的：

int batch_size = blob->num(); 
int channels = blob->channels(); 
int height = blob->height(); 
int width = blob->width(); 
std::cout << "Layer name:" << "'" << net_->layer_names()[layer_index] << "'" << " Blob name:" << "'" <<net_->blob_names()[layer_index] << "'" << " batch size " << "'" << batch_size << "'" << " channels:" << "'" << channels << "'" << " height:" << "'" << height << "'" << " width:" << "'" << width << "'" << std::endl; 

编辑：

问题2： 如果层有3个频道，那么你可以做到这一点，以显示为图像：

// assign channels 
std::vector<cv::Mat> ccs; 
cv::Size ss(width, height); 
float* data = blob->mutable_cpu_data(); 
for (int i = 0; i < channels; ++i) { 
    cv::Mat channel(ss, CV_32FC1, data); 
    ccs.push_back(channel); 
    data += ss.area(); 
} 
cv::Mat res,dst; 
// merge them 
cv::merge(ccs, res); 
// optional add mean if needed 
cv::normalize(res, dst, 0, 1, cv::NORM_MINMAX); 
cv::namedWindow("Display window"); 
cv::imshow("Display window", dst); 
cv::waitKey(0);