how can I extract predicted label and testlabel from already trained deep learning model. the code below gives error while running
5 次查看(过去 30 天)
显示 更早的评论
load('MyVGG19Model.mat');
imdsTest = imageDatastore("C:\Users\Bashir\Desktop\Training dataset\Test set", ...
'IncludeSubfolders',true, ...
'LabelSource','foldernames');
imageAugmenter = imageDataAugmenter( ...
'RandRotation',[-90,90], ...
'RandScale',[1 1.1], ...
'RandXTranslation',[-3 3], ...
'RandYTranslation',[-3 3]);
imageSize = myvgg16.Layers(1).InputSize;
augmentedTestSet = augmentedImageDatastore(imageSize, imdsTest, 'DataAugmentation',imageAugmenter);
predictedLabels = predict(myvgg16, augmentedTestSet);
testLabels = imdsTest.Labels
% Tabulate the results using a confusion matrix.
confMat = confusionmat(testLabels, predictedLabels);
% Convert confusion matrix into percentage form
confMat = bsxfun(@rdivide,confMat,sum(confMat,2))
7 个评论
Walter Roberson
2021-12-4
You could try
categorical(string(round(predictedLabels)))
but I would recommend looking more carefully at the values in predictedLabels. The values of the predictedLabels might possibly be class numbers, in which case you would want to use them to index the categories that were used in TestLabels .
回答(1 个)
yanqi liu
2021-12-4
load('MyVGG19Model.mat');
imdsTest = imageDatastore("C:\Users\Bashir\Desktop\Training dataset\Test set", ...
'IncludeSubfolders',true, ...
'LabelSource','foldernames');
imageAugmenter = imageDataAugmenter( ...
'RandRotation',[-90,90], ...
'RandScale',[1 1.1], ...
'RandXTranslation',[-3 3], ...
'RandYTranslation',[-3 3]);
imageSize = myvgg16.Layers(1).InputSize;
augmentedTestSet = augmentedImageDatastore(imageSize, imdsTest, 'DataAugmentation',imageAugmenter);
predictedLabels = predict(myvgg16, augmentedTestSet);
testLabels = imdsTest.Labels
% Tabulate the results using a confusion matrix.
confMat = confusionmat(double(testLabels), double(predictedLabels));
% Convert confusion matrix into percentage form
confMat = bsxfun(@rdivide,confMat,sum(confMat,2))
0 个评论
另请参阅
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!