Error using trainNetwork (line 154) augmentedImageSource cannot form MiniBatches of data because input image sizes differ in 3rd dimension. Consider using 'ColorPreprocessing'

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Rida Shariff
Rida Shariff 2022-6-30
回答： Sanyam 2022-7-13
i am using MATLAB r2018a and i have this problem.my coding is;
net = alexnet;
analyzeNetwork(net)
inputSize = net.Layers(1).InputSize
layersTransfer = net.Layers(1:end-3);
numClasses = numel(categories(imdsTrain.Labels))
layers = [
layersTransfer
fullyConnectedLayer(numClasses,'WeightLearnRateFactor',20,'BiasLearnRateFactor',20)
softmaxLayer
classificationLayer];
pixelRange = [-30 30];
imageAugmenter = imageDataAugmenter( ...
'RandXReflection',true, ...
'RandXTranslation',pixelRange, ...
'RandYTranslation',pixelRange);
augimdsTrain = augmentedImageDatastore(inputSize(1:2),imdsTrain, ...
'DataAugmentation',imageAugmenter);
augimdsValidation = augmentedImageDatastore(inputSize(1:2),imdsValidation);
options = trainingOptions('sgdm', ...
'MiniBatchSize',10, ...
'MaxEpochs',6, ...
'InitialLearnRate',1e-4, ...
'Shuffle','every-epoch', ...
'ValidationData',augimdsValidation, ...
'ValidationFrequency',3, ...
'Verbose',false, ...
'Plots','training-progress');
netTransfer = trainNetwork(augimdsTrain,layers,options);
[YPred,scores] = classify(netTransfer,augimdsValidation);
idx = randperm(numel(imdsValidation.Files),4);
figure
for i = 1:4
subplot(2,2,i)
I = readimage(imdsValidation,idx(i));
imshow(I)
label = YPred(idx(i));
title(string(label));
end
YValidation = imdsValidation.Labels;
accuracy = mean(YPred == YValidation)

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回答（1 个）

Sanyam
Sanyam 2022-7-13
It looks like your data set contains images of different color channels like grayscale, rgb etc. matlab does not allow 2 images of different dimensions in a mini-batch. One of the ways would be to convert all your images in grayscale, this can be done by defining augmented datastore like this:
augmentedImageDatastore(inputSize(1:2),yourData,'ColorPreprocessing','rgb2gray');
It converts all the rgb images to grayscale.
Hope that helps! Thanks!

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