matlab列优先与高维矩阵重构 及 CNN 逐层可视化 on Matlab

由于matlab在列化a(:)以及reshape(a)等操作中是列优先的，所以要重构出新的高维度矩阵，通常要把reshape和permute结合起来使用。

先到 http://caffe.berkeleyvision.org/ 下载 训练好的model bvlc_reference_caffenet.caffemodel;

更多caffe使用也请参看上面的网址。

 clear
 close all


addpath ./matlab

model= './models/bvlc_reference_caffenet/deploy.prototxt';
weights= './models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel';

 
 net = caffe.Net(model, weights, 'test'); % create net and load weights

%% obtain params in diff layers and show
pdata = net.params('conv1',1).get_data();

vis_square(pdata,2,0.5);
 
  
net.blobs('data').reshape([227 227 3 1]);
net.reshape();

%% prepare the image
im_data = caffe.io.load_image('./examples/images/cat.jpg');
 mean = load('./matlab/+caffe/imagenet/ilsvrc_2012_mean.mat');

%% subtract mean_data (already in W x H x C, BGR)
 mean_data = mean.mean_data;
 im_data = im_data - mean_data;  

 width = 227; height = 227;
 im_data = imresize(im_data, [width, height]); % resize using Matlab's imresize
 res = net.forward({im_data});

 prob = res{1};

%% obtain features and show
 ddata = net.blobs('conv2').get_data();
 vis_square(ddata,2,0);

function vis_square(data,padsize,padval)

 data=net_data_normalize(data);

if ~ exist('padsize', 'var') 
  padsize=1;
end
if ~ exist('padval', 'var') 
  padval=0;
end
ndim=ndims(data);
% w*num*h*chanel
if ndim==4
    fprintf('visualize params
');
    data=permute(data,[1,4,2,3]);
else ndim==3
    fprintf('visualize maps
');
    data=permute(data,[1,3,2]);
end
    
    n = (ceil(sqrt(size(data,2))));
    data=padarray(data,[padsize n^2-size(data,2) padsize 0],'post');
    data=reshape(data,size(data,1),n,n,size(data,3),size(data,4));
    data=permute(data,[1,3,4,2,5]);
    data=reshape(data,[size(data,1)*n,size(data,3)*n,size(data,5)]);
   
figure
if ndim==4
    ;
else ndim==3
    data=imrotate(data,-90);
end   

imshow(imresize(data,[500,500],'nearest'))

end