VGG19 net Error

Question

mohd akmal masud 2022-7-13

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1758785-vgg19-net-error

评论： mohd akmal masud 2022-7-13

采纳的回答： Walter Roberson

matlab.mat

在 MATLAB Online 中打开

Dear all, I was run the VGG19 using apps designer. But I got error.

**The workspace of data as attached. (matlab.mat)

Anyone can help me?

Because actually I dont understand what fullyconnected function

clc
clear all
close all
%testDataimages
DATASetDir = fullfile('C:\Users\Akmal\Desktop\NEW 3D U NET');
IMAGEDir = fullfile(DATASetDir,'ImagesTr');
volReader = @(x) matRead(x);
volds = imageDatastore(IMAGEDir, ...
    'FileExtensions','.mat','ReadFcn',volReader);
% labelReader = @(x) matread(x);
matFileDir = fullfile('C:\Users\Akmal\Desktop\NEW 3D U NET\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);
up1 = uipanel;
h = labelvolshow(label, volume, 'Parent', up1);
h.CameraPosition = [4 2 -3.5];
h.LabelVisibility(1) = 0;
h.VolumeThreshold = 0.5;
volumeViewer(volume, label)
patchSize = [128 128 64];
patchPerImage = 16;
miniBatchSize = 8;
patchds = randomPatchExtractionDatastore(volds,pxds,patchSize, ...
    'PatchesPerImage',patchPerImage);
patchds.MiniBatchSize = miniBatchSize;
dsTrain = transform(patchds,@augment3dPatch);
volLocVal = fullfile('C:\Users\Akmal\Desktop\NEW 3D U NET\imagesVal');
voldsVal = imageDatastore(volLocVal, ...
    'FileExtensions','.mat','ReadFcn',volReader);
lblLocVal = fullfile('C:\Users\Akmal\Desktop\NEW 3D U NET\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 1],"Name","image3dinput")
    convolution3dLayer([3 3 3],32,"Name","conv3d_1","Padding","same")
    reluLayer("Name","relu_1")
    convolution3dLayer([3 3 3],32,"Name","conv3d_2","Padding","same")
    reluLayer("Name","relu_2")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_1","Padding","same")
    convolution3dLayer([3 3 3],32,"Name","conv3d_3","Padding","same")
    reluLayer("Name","relu_3")
    convolution3dLayer([3 3 3],32,"Name","conv3d_4","Padding","same")
    reluLayer("Name","relu_4")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_2","Padding","same")
    convolution3dLayer([3 3 3],32,"Name","conv3d_5","Padding","same")
    reluLayer("Name","relu_5")
    convolution3dLayer([3 3 3],32,"Name","conv3d_6","Padding","same")
    reluLayer("Name","relu_6")
    convolution3dLayer([3 3 3],32,"Name","conv3d_7","Padding","same")
    reluLayer("Name","relu_7")
    convolution3dLayer([3 3 3],32,"Name","conv3d_8","Padding","same")
    reluLayer("Name","relu_8")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_3","Padding","same")
    convolution3dLayer([3 3 3],32,"Name","conv3d_9","Padding","same")
    reluLayer("Name","relu_9")
    convolution3dLayer([3 3 3],32,"Name","conv3d_10","Padding","same")
    reluLayer("Name","relu_10")
    convolution3dLayer([3 3 3],32,"Name","conv3d_11","Padding","same")
    reluLayer("Name","relu_11")
    convolution3dLayer([3 3 3],32,"Name","conv3d_12","Padding","same")
    reluLayer("Name","relu_12")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_4","Padding","same")
    convolution3dLayer([3 3 3],32,"Name","conv3d_13","Padding","same")
    reluLayer("Name","relu_13")
    convolution3dLayer([3 3 3],32,"Name","conv3d_14","Padding","same")
    reluLayer("Name","relu_14")
    convolution3dLayer([3 3 3],32,"Name","conv3d_15","Padding","same")
    reluLayer("Name","relu_15")
    convolution3dLayer([3 3 3],32,"Name","conv3d_16","Padding","same")
    reluLayer("Name","relu_16")
    maxPooling3dLayer([5 5 5],"Name","maxpool3d_5","Padding","same")
    fullyConnectedLayer(10,"Name","fc_3")
    reluLayer("Name","relu_18")
    dropoutLayer(0.5,"Name","dropout_1")
    fullyConnectedLayer(10,"Name","fc_2")
    reluLayer("Name","relu_17")
    dropoutLayer(0.5,"Name","dropout_2")
    fullyConnectedLayer(10,"Name","fc_1")
    softmaxLayer("Name","softmax")
    pixelClassificationLayer("Name","pixel-class")];
plot(layerGraph(layers));

ERROR

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Answer 1

Walter Roberson 2022-7-13

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1758785-vgg19-net-error#answer_1006065

在 MATLAB Online 中打开

classNames = ["background", "tumor"];

That is only two classes

fullyConnectedLayer(10,"Name","fc_1")

You are asking for 10 connections on the output layer, but 10 connections would be what you would use for training 10 classes. The number of connections on the output layer should be the same as the number of classes.