image resize deep learning

Question

amjad hammad 2022-10-30

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1839333-image-resize-deep-learning

评论： amjad hammad 2022-11-6

在 MATLAB Online 中打开

i have problem in image size in matlab

Error using trainNetwork (line 183)

Unexpected image size: All images must have the same size.

Error in neuralkadoplnenienulami (line 58)

net = trainNetwork(imgsTrain,layers,options);

%Trenovacie data pre siet
trainingDataPath = fullfile('C:\Users\amjad\Desktop\COVID-19-master\doplnenie nulami (1)\Triedenie');
trainingImages = imageDatastore(trainingDataPath,'IncludeSubfolders',true,'LabelSource','foldernames');
% Zobrazenie nahodnych trenovacich dat
figure;
perm = randperm(169,16);
for i = 1:16
    subplot(4,4,i);
    imshow(trainingImages.Files{perm(i)});
end
% Pocet fotografii v jednotlivych triedach
labelCount = countEachLabel(trainingImages);
% Velkost trenovacich fotiek
img = readimage(trainingImages,1);
[sizeR, SizeC] = size(img);
%specifikovanie poctu trenovacich a validacnych dat
numTrainData = 75;
[imgsTrain,imgsValidation] = splitEachLabel(trainingImages,numTrainData,'randomize');
%Definovanie architektury siete
layers = [
    imageInputLayer([sizeR SizeC 1])
    
    convolution2dLayer(3,8,'Padding','same')
    batchNormalizationLayer
    reluLayer
    
    maxPooling2dLayer(1,'Stride',2)
    
    convolution2dLayer(3,16,'Padding','same')
    batchNormalizationLayer
    reluLayer
    
    maxPooling2dLayer(2,'Stride',2)
   
    convolution2dLayer(3,32,'Padding','same')
    batchNormalizationLayer
    reluLayer  
    
    fullyConnectedLayer(2)
    softmaxLayer
    classificationLayer];
options = trainingOptions('sgdm', ...
    'InitialLearnRate',0.01, ...
    'MaxEpochs',20, ...
    'Shuffle','every-epoch', ...
    'ValidationData',imgsValidation, ...
    'Verbose',false, ...
    'Plots','training-progress');
net = trainNetwork(imgsTrain,layers,options);
%Klasifikacia dat s vyhodnotenim
clasifydataPath = fullfile('C:\Users\amjad\Desktop\COVID-19-master\doplnenie nulami (1)\Klasifikacia');
clasifyingImages = imageDatastore(clasifydataPath,'IncludeSubfolders',true,'LabelSource','foldernames');
YPred = classify(net,clasifyingImages);
YValidation = clasifyingImages.Labels;
accuracy = sum(YPred == YValidation)/numel(YValidation);
missclassifaction  = find(YPred ~= YValidation);
missclassifaction = transpose(missclassifaction);
FP = sum(missclassifaction (:)>8);
FN = sum(missclassifaction (:)<9);
TN = 8-FP;
TP = 8-FN;

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KALYAN ACHARJYA 2022-10-30

Dear Amjad, before train the model, why do not perfoem just 2 line code to make all images in same size.

amjad hammad 2022-11-6

i have chabged all images to same sizes using resize program

Please if you have code to resize images can you provide me

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Answer 1

Walter Roberson 2022-10-30

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1839333-image-resize-deep-learning#answer_1087488

https://www.mathworks.com/help/deeplearning/ref/augmentedimagedatastore.html

You use an augmented image data store. That allows you to specify an output size. It also allows you to set rgb or grayscale and will automatically convert images as needed.