The training image are the size of [32 32 32 4] but the input layer expects image size [32 32 32 3]

Question

hla hla myint 2020-11-4

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/635870-the-training-image-are-the-size-of-32-32-32-4-but-the-input-layer-expects-image-size-32-32-32-3

回答： Walter Roberson 2020-11-5

I train the network the following :

imageDir=fullfile(tempdir,'PP');
if ~exist(imageDir,'dir')
    mkdir(imageDir);
end
sourceDatalaoc=[imageDir filesep 'Brain'];
volc=fullfile (sourceDatalaoc, 'AA')
if~ exist(volc,'dir')
    mkdir(volc);
end
loc=fullfile (sourceDatalaoc, 'BB')
if~ exist(loc,'dir')
    mkdir(loc);
end
 
imds = imageDatastore(volc,'FileExtensions','.nii','ReadFcn',@sampleReadeFcn);
classNames = ["edema","nonEnhancingTumor","enhancingTumour"];
pixelLabelID = [1 2 3];
pxds = pixelLabelDatastore(loc,classNames,pixelLabelID,'FileExtensions','.nii','ReadFcn',@sampleReadeFcn);
V = read(imds);
L = read(pxds);
%h = labelvolshow(L,V(:,:,:,1));
pximds = pixelLabelImageDatastore(imds,pxds);
inputPatchSize = [32 32 32 4];
numClasses = 2;
patchSize = [32 32 32];
patchPerImage = 8;
miniBatchSize = 16;
patchds = randomPatchExtractionDatastore(imds,pxds,patchSize, ...
    'PatchesPerImage',patchPerImage);
patchds.MiniBatchSize = miniBatchSize;
layers = [
         image3dInputLayer([32 32 32 3)
         convolution3dLayer(3,12,'Stride',1,'Padding','Same')
         batchNormalizationLayer
         reluLayer
         transposedConv3dLayer(3,6,'Stride',1,'Cropping',1)
         batchNormalizationLayer
         reluLayer
         convolution3dLayer(1,2)
         softmaxLayer
         pixelClassificationLayer
      ]
opts = trainingOptions('sgdm', ...
    'InitialLearnRate',1e-3, ...
            'ExecutionEnvironment','CPU',...
    'MaxEpochs',100);
 [net2,info] = trainNetwork(patchds,layers,opts);