您好，为了熟悉 CNN，我准备了二进制分类飞机（760 幅图像）或非飞机（750）的代码。
这是我的 MATLAB 代码
Npos = numel(possitive_regions);
Nneg = numel(negative_regions);
Npos_train = floor(0.25* Npos);
Npos_val = floor(0.25*Npos);
Npos_test = floor(0.50*Npos);
Nneg_train = floor(0.25*Nneg);
Nneg_val = floor(0.25*Nneg);
Nneg_test = floor(0.50*Nneg);
for i=1:Npos
im= imresize (single(possitive_regions{i,:}),[50,50]);
imdb.images.data(:,:,:, i) = im;
imdb.images.labels(i) = 1;
if i <= Npos_train
imdb.images.set(i) = 1;
elseif i <= Npos_train+Npos_val
imdb.images.set(i) = 2;
else
imdb.images.set(i) = 3;
end
end
% for negative samples
for i=1:Nneg
im= imresize (single(negative_regions{i,:}),[50,50]);
imdb.images.data(:,:,:, i+Npos) = im;
imdb.images.labels(i+Npos) = 0;
if i <= Nneg_train
imdb.images.set(Npos+i) = 1;
elseif i <= Nneg_train+Nneg_val
imdb.images.set(Npos+i) = 2;
else
imdb.images.set(Npos+i) = 3;
end
end
imdb.meta.sets = {'train', 'val', 'test'} ;
%% Network
opts.inputSize = [50 50 3] ;
opts.train.batchSize = 50;
opts.train.numEpochs = 10;
opts.train.continue = true;
% opts.train.useGpu = false;
opts.train.learningRate = 0.01;
% opts = vl_argparse(opts, []);
f = 0.01;
f=1/100 ;
net.layers = {} ;
net.layers{end+1} = struct('type', 'conv','weights', {{f*randn(5,5,3,20, 'single'), zeros(1, 20, 'single')}},'stride', 1,'pad', 0);
net.layers{end+1} = struct('type', 'pool','method', 'max', 'pool', [2 2], 'stride', 2, 'pad', 0) ;
net.layers{end+1} = struct('type', 'conv', 'weights', {{f*randn(5,5,20,50, 'single'),zeros(1,50,'single')}}, 'stride', 1, 'pad', 0) ;
net.layers{end+1} = struct('type', 'pool', 'method', 'max', 'pool', [2 2], 'stride', 2, 'pad', 0) ;
net.layers{end+1} = struct('type', 'conv', 'weights', {{f*randn(4,4,50,500, 'single'), zeros(1,500,'single')}}, 'stride', 1, 'pad', 0) ;
net.layers{end+1} = struct('type', 'relu') ;
net.layers{end+1} = struct('type', 'conv', 'weights', {{f*randn(1,1,500,10, 'single'), zeros(1,10,'single')}}, 'stride', 1, 'pad', 0) ;
net.layers{end+1} = struct('type', 'softmaxloss') ;
disp( 'Net is Ok.' );
% [net, info] = trainfn(net, imdb, getBatch(opts), 'expDir', opts.expDir, net.meta.trainOpts, opts.train, 'val', find(imdb.images.set == 3)) ;
[net, info] = cnn_train( net, imdb, @getBatch, opts.train, 'val', find( imdb.images.set == 2 ) ) ;
我从 MINST 示例中获取的网络部分。我已将此文件和 getBatch 函数保存在 MatConvNet 示例文件夹中。当我运行时，cnn_train我得到了这个输出和错误。
任何人，请帮我解决这个错误。另外，我搜索了这个错误，我发现我需要检查 mex 文件并使用 vl_compilenn('verbose', 1) 进行编译。我在编译时也遇到了错误：
使用 mex 时出错
链接：致命错误 LNK1104：无法打开文件 'C:\Users\z5085693\Downloads\matconvnet-1.0-beta23\matconvnet-1.0-beta23\matlab\mex\vl_nnconv.mexw64'
vl_compilenn>mex_link (line 547) mex(mopts{:}) 中的错误；
vl_compilenn 错误（第 498 行） mex_link(opts, objs, mex_dir, flags.mexlink) ；