How to monitor Deep learning training

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Mustafa Yildiz 2020-4-13

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/517433-how-to-monitor-deep-learning-training

评论： Mohammad Sami 2020-4-13

Hello i wanna monitor the training when its happening , how should i change the code for that ?

outputFolder = fullfile('faceset'); 
rootFolder = fullfile(outputFolder,'faces'); 
categories = {'Ali','amanda','Betul','Clarisse','Elizabet','Erica','Firdevs','Furkan','Gabia','Gabriela','Irem','Justa','Kadir','Laura','Mehmet','Merve','Mustafa','Oguz','Ruta','Vika','Yigit'}; %choosing the categories which is gonna go to training
imds = imageDatastore(fullfile(rootFolder,categories),'LabelSource','foldernames'); 
tbl = countEachLabel(imds); 
minSetCount = min(tbl{:,2});
imds = splitEachLabel(imds, minSetCount,'randomize'); 
countEachLabel(imds); 
Ali = find(imds.Labels == 'Ali',1); 
amanda = find(imds.Labels == 'amanda',1);
net = resnet101();
net.Layers(1); 
net.Layers(end); 
[trainingSet,testSet] = splitEachLabel(imds,0.3,'randomize');
imageSize = net.Layers(1).InputSize; 
augmentedTrainingSet = augmentedImageDatastore(imageSize,...
    trainingSet,'ColorPreprocessing','gray2rgb'); 
augmentedTestSet = augmentedImageDatastore(imageSize,...
    testSet,'ColorPreprocessing','gray2rgb');
w1 = net.Layers(2).Weights;
w1 = mat2gray(w1); 
featureLayer = 'fc1000'; 
trainingFeatures = activations(net,augmentedTrainingSet,...
    featureLayer,'MiniBatchSize',32,'OutputAs','columns');
trainingLables = trainingSet.Labels;
classifier=fitcecoc(trainingFeatures,...
    trainingLables,'Learner','Linear','Coding','onevsall','ObservationsIn','columns');
testFeature = activations(net,augmentedTestSet,...
    featureLayer,'MiniBatchSize',32,'OutputAs','columns');
predictLabels = predict(classifier, testFeature,'ObservationsIn','columns');
testLables = testSet.Labels; 
confMat = confusionmat(testLables , predictLabels);
confMat = bsxfun(@rdivide , confMat , sum(confMat,2));
mean(diag(confMat));