%this file is used to test the model in the unseen data to this model by
%loading the trained model into the workking space

load skin-cancer-model-alexnet.mat trainedNet
digitDatasetPath = fullfile('C:\Users\UTStudent\Desktop\salari\salari-project\skin-cancer-dataset-test');
imds = imageDatastore(digitDatasetPath, ...
    'IncludeSubfolders',true,'LabelSource','foldernames');

%finding number of images in the directorty of test
numberofImages = length(imds.Files);
idx = randperm(numel(imds.Files),numberofImages);
%this loop here will clasify the unseen images to the model
for i = 1:numberofImages
    subplot(2,2,i)
    I = readimage(imds,idx(i));
    actualLabel = imds.Labels(idx(i));
    predictedLabel = netTransfer.classify(I);
    imshow(I)
    title(['Predicted: ' char(predictedLabel) ', Actual: ' char(actualLabel)])
end