googlenet运行实例.rar_googLeNet的应用_googlenet运行实例_matconvnet_图像分类_神经网

%% 自己编译成功 clear close all run matlab/vl_setupnn % download a pre-trained CNN from the web (needed once) % urlwrite(... % 'http://www.vlfeat.org/matconvnet/models/imagenet-googlenet-dag.mat', ... % 'imagenet-googlenet-dag.mat') ; % load the pre-trained CNNs net = dagnn.DagNN.loadobj(load('imagenet-googlenet-dag.mat')) ; net.mode = 'test' ; % load and preprocess an image im = imread('peppers.png') ; im_ = single(im) ; % note: 0-255 range im_ = imresize(im_, net.meta.normalization.imageSize(1:2)) ; im_ = bsxfun(@minus, im_, net.meta.normalization.averageImage) ; % run the CNN net.conserveMemory = 0; %将特征都显示出来 net.eval({'data',im_}); % % clear socres; % scores=net.vars(net.getVarIndex('icp6_reduction1')).value; % scores=squeeze(gather(scores)); % 查看每个参数的输出 for i=1:153 scores{i}=net.vars(net.getVarIndex(net.layers(i).outputs)).value; % scores{i}=squeeze(gather(scores)); end % % scores = net.vars(net.getVarIndex('prob')).value ; % % scores = squeeze(gather(scores)) ; % % % show the classification results [bestScore, best] = max(scores) ; figure(1) ; clf ; imagesc(im) ; title(sprintf('%s (%d), score %.3f',... net.meta.classes.description{best}, best, bestScore)) ;