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Training a Convolutional Autoencoder

12 vues (au cours des 30 derniers jours)
Aghata
Aghata le 23 Mai 2024
Commenté : Aghata le 27 Mai 2024
I'm trying to train this simple convolutional autoencoder but I'm getting error on the training part. The error says the size of predictions and tragets are not the same. But When I check the network structure using the analyseNetwork function it seems that my input has the same size as my output. I can't find where is the error. Can someone help me?
Follows the code
datastore_MP = datastore("Tiles_MP1_100ov50\", "IncludeSubfolders",true, "LabelSource","foldernames");
images_MP = cell(numel(datastore_MP.Files), 1);
for i = 1:numel(datastore_MP.Files)
img_MP = readimage(datastore_MP, i);
[rows, cols] = size(img_MP);
images_MP{i} = img_MP;
end
encoderBlock = @(block) [
convolution2dLayer(3,2^(3+block), "Padding",'same')
reluLayer
maxPooling2dLayer(2,"Stride",2)
convolution2dLayer(3,2^(5+block), "Padding",'same')
reluLayer
maxPooling2dLayer(2,"Stride",2)];
net_E = blockedNetwork(encoderBlock,1,"NamePrefix","encoder_");
decoderBlock = @(block) [
transposedConv2dLayer(3,2^(5-block),"Stride",2)
reluLayer
transposedConv2dLayer(3,2^(1-block), "Stride",2)
reluLayer];
net_D = blockedNetwork(decoderBlock,1,"NamePrefix","decoder_");
inputSize = [100 100 1];
CAE = encoderDecoderNetwork(inputSize,net_E,net_D);
analyzeNetwork(CAE)
options = trainingOptions( "adam",...
"Plots","training-progress",...
"MaxEpochs", 100,...
"L2Regularization",0.001);
trainedCAE = trainnet(datastore_MP, CAE, "mse", options);

Réponses (1)

fatma zahra
fatma zahra le 23 Mai 2024
Hey, try changing 'trainnet' to 'trainNetwork'.
trainedCAE = trainNetwork(datastore_MP, CAE, "mse", options);
  1 commentaire
Aghata
Aghata le 27 Mai 2024
Hello, Fatma.
I tried but this doesn't fix the problem. I've been trying to find a way to set the target size to be the same as the input or output, but without success.

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