Hello, i have a problem with the size of the training data. i've done the augmentedImageDatastore function to fix it but when i do the trainNetwork function they say that the size of the training images is not the same as the size that the input layer expects. How can i fix this error? Here is my code
Flowers ='C:\Users\hind';'deeplearning_course_files';'Flowers';
flowerds = imageDatastore(Flowers,"IncludeSubfolders",true,"LabelSource","foldernames");
[trainImgs,testImgs] = splitEachLabel(flowerds,0.6);
numClasses = numel(categories(flowerds.Labels));
net = googlenet;
lgraph = layerGraph(net);
newFc = fullyConnectedLayer(12,"Name","new_fc");
lgraph = replaceLayer(lgraph,"loss3-classifier",newFc);
newOut = classificationLayer("Name","new_out");
lgraph = replaceLayer(lgraph,"output",newOut);
options = trainingOptions("sgdm","InitialLearnRate", 0.001);
auds = augmentedImageDatastore([224 224],flowerds,"ColorPreprocessing","gray2rgb");
[flowernet,info] = trainNetwork(trainImgs, lgraph, options);

4 commentaires

Jan
Jan le 18 Mar 2021
"they say that the size of the training images is not the same as the size that the input layer expects" - please post a copy of the error message.
What do you expect this line to do:
Flowers ='C:\Users\hind';'deeplearning_course_files';'Flowers';
You create the char vectors 'deeplearning_course_files' and 'Flowers' and assign it to nothing.
Hind Haboubi
Hind Haboubi le 18 Mar 2021
Thank you for your response.
Flowers ='C:\Users\hind';'deeplearning_course_files';'Flowers';
is for imagedatastore, I couldn't do it without this ligne.
Can you correct me please
Jan
Jan le 19 Mar 2021
The line
Flowers ='C:\Users\hind';'deeplearning_course_files';'Flowers';
does exactly the same as:
Flowers ='C:\Users\hind';
Do you mean:
Flowers = 'C:\Users\hind\deeplearning_course_files\Flowers';
Hind Haboubi
Hind Haboubi le 19 Mar 2021
thank you, I'll try it

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Srivardhan Gadila
Srivardhan Gadila le 22 Mar 2021

0 votes

Even though you are creating a "auds" augmentedImageDatastore object, you are not using it to train your network. Change the line
[flowernet,info] = trainNetwork(trainImgs, lgraph, options);
to
[flowernet,info] = trainNetwork(auds, lgraph, options);

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