Invalid training data. The output size (5) of the last layer doesn't match the number of classes (5). How to match output size??

net=vgg16();
imds = imageDatastore(fullfile('E:\','data','labels'),...
  'IncludeSubfolders',true,'FileExtensions','.dcm','LabelSource','foldernames');  
labelCount = countEachLabel(imds);
trainingNumFiles = 105;
rng(1) % For reproducibility
[trainData,testData] = splitEachLabel(imds,...
    trainingNumFiles,'randomize');
imageSize = [512 512 1];
numClasses = 5;
encoderDepth = 9;
lgraph = segnetLayers(imageSize,numClasses,encoderDepth);
plot(lgraph)
options = trainingOptions('sgdm','InitialLearnRate',1e-3, ...
      'MaxEpochs',50,'VerboseFrequency',10);
seg = trainNetwork(imds,lgraph,options)

Answer 1

[nima aalizade]

hello,

for using SegNet, you most have pixel labeled data with image labeler. you can use this and this example to understand better.

Answer 2

[abdulkader helwan]

Hello.. i am having the same problem here. could u please tell me how u solved it if u did so. thanks

[Evan Koester]

Same issue here as well. Any answers?

[Imene Mech]

Same issue here !

[nima aalizade]

hello

 for using SegNet, you most have pixel labeled data with image labeler. you can use this and this example to understand better.

[Mihai Mihaela]

Same issue here. The attached link doesn't work.