VGG19 GOT ERROR

Dear all,

Need your help.

I want to run VGG19. But I got an error. (all data in ezyzip folder as attached, and matlab.m is workspace)

Below is my coding

clc
clear all
close all

%testDataimages
DATASetDir = fullfile('C:\Users\USER\Downloads\NEW 3D U NET 128X128\vgg');
IMAGEDir = fullfile(DATASetDir,'ImagesTr');
volReader = @(x) matRead(x);
volds = imageDatastore(IMAGEDir, ...
    'FileExtensions','.mat','ReadFcn',volReader);

% labelReader = @(x) matread(x);
matFileDir = fullfile('C:\Users\USER\Downloads\NEW 3D U NET 128X128\LabelsTr');
classNames = ["background", "tumor"];
pixelLabelID = [0 1];

% pxds = (LabelDirr,classNames,pixelLabelID, ...
%     'FileExtensions','.mat','ReadFcn',labelReader);

pxds = pixelLabelDatastore(matFileDir,classNames,pixelLabelID, ...
    'FileExtensions','.mat','ReadFcn',@matRead);

volume = preview(volds);
label = preview(pxds);

patchSize = [128 128 64];
patchPerImage = 16;
miniBatchSize = 2;

patchds = randomPatchExtractionDatastore(volds,pxds,patchSize, ...
    'PatchesPerImage',patchPerImage);
patchds.MiniBatchSize = miniBatchSize;
dsTrain = transform(patchds,@augment3dPatch);

volLocVal = fullfile('C:\Users\USER\Downloads\NEW 3D U NET 128X128\imagesVal');
voldsVal = imageDatastore(volLocVal, ...
    'FileExtensions','.mat','ReadFcn',volReader);

lblLocVal = fullfile('C:\Users\USER\Downloads\NEW 3D U NET 128X128\labelsVal');
pxdsVal = pixelLabelDatastore(lblLocVal,classNames,pixelLabelID, ...
    'FileExtensions','.mat','ReadFcn',volReader);

dsVal = randomPatchExtractionDatastore(voldsVal,pxdsVal,patchSize, ...
    'PatchesPerImage',patchPerImage);
dsVal.MiniBatchSize = miniBatchSize;

layers = [
    image3dInputLayer([128 128 64],"Name","image3dinput")
    convolution3dLayer([3 3 3],32,"Name","conv3d_1","Padding","same")
    batchNormalizationLayer("Name","batchnorm_1")
    reluLayer("Name","relu_1")
    convolution3dLayer([3 3 3],32,"Name","conv3d_2","Padding","same")
    batchNormalizationLayer("Name","batchnorm_2")
    reluLayer("Name","relu_2")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_1","Padding","same")
    convolution3dLayer([3 3 3],32,"Name","conv3d_3","Padding","same")
    batchNormalizationLayer("Name","batchnorm_3")
    reluLayer("Name","relu_3")
    convolution3dLayer([3 3 3],32,"Name","conv3d_4","Padding","same")
    batchNormalizationLayer("Name","batchnorm_4")
    reluLayer("Name","relu_4")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_2","Padding","same")
    convolution3dLayer([3 3 3],32,"Name","conv3d_5","Padding","same")
    batchNormalizationLayer("Name","batchnorm_5")
    reluLayer("Name","relu_5")
    convolution3dLayer([3 3 3],32,"Name","conv3d_6","Padding","same")
    batchNormalizationLayer("Name","batchnorm_6")
    reluLayer("Name","relu_6")
    convolution3dLayer([3 3 3],32,"Name","conv3d_7","Padding","same")
    batchNormalizationLayer("Name","batchnorm_7")
    reluLayer("Name","relu_7")
    convolution3dLayer([3 3 3],32,"Name","conv3d_8","Padding","same")
    batchNormalizationLayer("Name","batchnorm_8")
    reluLayer("Name","relu_8")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_3","Padding","same")
    convolution3dLayer([3 3 3],32,"Name","conv3d_9","Padding","same")
    batchNormalizationLayer("Name","batchnorm_9")
    reluLayer("Name","relu_9")
    convolution3dLayer([3 3 3],32,"Name","conv3d_10","Padding","same")
    batchNormalizationLayer("Name","batchnorm_10")
    reluLayer("Name","relu_10")
    convolution3dLayer([3 3 3],32,"Name","conv3d_11","Padding","same")
    batchNormalizationLayer("Name","batchnorm_11")
    reluLayer("Name","relu_11")
    convolution3dLayer([3 3 3],32,"Name","conv3d_12","Padding","same")
    batchNormalizationLayer("Name","batchnorm_12")
    reluLayer("Name","relu_12")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_4","Padding","same")
    convolution3dLayer([3 3 3],32,"Name","conv3d_13","Padding","same")
    batchNormalizationLayer("Name","batchnorm_13")
    reluLayer("Name","relu_13")
    convolution3dLayer([3 3 3],32,"Name","conv3d_14","Padding","same")
    batchNormalizationLayer("Name","batchnorm_14")
    reluLayer("Name","relu_14")
    convolution3dLayer([3 3 3],32,"Name","conv3d_15","Padding","same")
    batchNormalizationLayer("Name","batchnorm_15")
    reluLayer("Name","relu_15")
    convolution3dLayer([3 3 3],32,"Name","conv3d_16","Padding","same")
    batchNormalizationLayer("Name","batchnorm_16")
    reluLayer("Name","relu_16")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_5","Padding","same")
    fullyConnectedLayer(2,"Name","fc_1")
    reluLayer("Name","relu_17")
    dropoutLayer(0.5,"Name","dropout_1")
    fullyConnectedLayer(2,"Name","fc_2")
    reluLayer("Name","relu_18")
    dropoutLayer(0.5,"Name","dropout_2")
    fullyConnectedLayer(2,"Name","fc_3")
    softmaxLayer("Name","softmax")
    pixelClassificationLayer("Name","pixel-class")];

plot(layerGraph(layers));


maxEpochs = 150;
options = trainingOptions('adam', ...
    'MaxEpochs',maxEpochs, ...
    'InitialLearnRate',1e-3, ...
    'LearnRateSchedule','piecewise', ...
    'LearnRateDropPeriod',5, ...
    'LearnRateDropFactor',0.97, ...
    'ValidationData',dsVal, ...
    'ValidationFrequency',200, ...
    'Plots','training-progress', ...
    'Verbose',false, ...
    'MiniBatchSize',miniBatchSize);

doTraining = true;
if doTraining
    modelDateTime = datestr(now,'dd-mmm-yyyy-HH-MM-SS');
    [net,info] = trainNetwork(dsTrain,layers,options);
    save(['trained3DUNet-' modelDateTime '-Epoch-' num2str(maxEpochs) '.mat'],'net');
else
    load('trained3DVNet-07-Jun-2022-13-45-30-Epoch-250.mat');
end

Error using trainNetwork

Invalid training data. The output size ([1 1 1 2]) of the last layer does not match the response size ([128 128 64 2]).