Where is the problem with this code?
이전 댓글 표시
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);
답변 (1개)
Cris LaPierre
2021년 4월 15일
0 개 추천
Inspect your response variable. It apparently has the wrong data type.
카테고리
도움말 센터 및 File Exchange에서 Deep Learning Toolbox에 대해 자세히 알아보기
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