Where is the problem with this code?
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I will receive this message after entering the information(dsnew) into the deep learning application
invalid training data for classification network response must be categorical
location1 = fullfile(matlabroot,'bin','F18','test9','noise');
location2 = fullfile(matlabroot,'bin','F18','test9','1','main');
location3 = fullfile(matlabroot,'bin','F18','test9','1','validation');
noise = imageDatastore({location1},'FileExtensions',{'.jpg','.png','.jpeg'},'IncludeSubfolders',true,'LabelSource','foldernames');
nonnoise = imageDatastore({location2},'FileExtensions',{'.jpg','.png','.jpeg'},'IncludeSubfolders',true,'LabelSource','foldernames');
validation = imageDatastore({location3},'FileExtensions',{'.jpg','.png','.jpeg'},'IncludeSubfolders',true,'LabelSource','foldernames');
aug1 = imageDataAugmenter('RandRotation',[0 90],'RandScale',[1.1 1.3]);
auimds1 = augmentedImageDatastore([224 224 1],nonnoise,'ColorPreprocessing','rgb2gray','DataAugmentation',aug1);
auimds2 = augmentedImageDatastore([224 224 1],noise,'ColorPreprocessing','rgb2gray');
validation1 = augmentedImageDatastore([224 224 1],validation,'ColorPreprocessing','rgb2gray');
dsnew = combine(noise,nonnoise);
2 Commenti
Jan
il 15 Apr 2021
It is a bad idea to store data in Matlab bin directory.
Please post the complete error message. This is better than letting the readers guess, which lines causes the problem.
Risposte (1)
Cris LaPierre
il 15 Apr 2021
Inspect your response variable. It apparently has the wrong data type.
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