ples expline this codes

and write to me what is the classification

expline the using of agumented image datastore

and why using this

Zocreate ImageDatastore for CNN . inds i imageDatastore(fullfile(dataFolder, categories), 'Labelsource', 'follernames'); tbl countEachlabel (imds) 3 devide data to the troin and test [indsTrain,imdstest] = spliteachLabel (inds, 0.90, 'randomized'); numtraintmages = nume1 (imdstrain.Labels); 8 Extract the class labels from the training and test data. counteachLabel (imds Train) 6. numitrages Train = numel (imdsTrain.Labels); Qi idx inandperm(numtralnImages, 16); . I Iatile( inds, "Frames', Idx); i figure Binchow (I) iscal1 Alextlet Network. net = alexnet; analyzenetwork (net); 6 export the features from layer 7 netway ers: * figure \% imshow(I) Wcall AlexNet Network. net = alexnet; analyzeNetwork(net); % export the features from layer 7 net.Layers; layer = "fc7"; \% format each image to 227227.3 because its the size that can be deal with Alexket outputsize=[ [2272273]; auimdstrain = augmentedimageDatastore (outputsize, imds Train, 'Colorpreprocessaing', 'gray2rgb'); auimdstest = augmentedImageDatastore(outputSize, imdsTest, 'Colorpreprocessing', 'gray2ggb') i \% feature extraction from layer 7 featurestrain = activations(net, auindstrain, layer, 'Outputas', "rons'); features Test = activations(net, Guindstest, layer, 'OutputAs', 'rons.'); % calculate number of examples for train and test YTrain = imdsTrain. Labels; \% Extract the class labels from the training and test data. VTest = inds Test, Labels; numClasses = numel (categonies) \% format each image to 2272273 because its the size that can be deal with AlexNet outputsize =[2272273]; auimdstrain = augmentedimageDatastore (outputSize, imds Train, 'Colorpreprocessing ', 'gray2rgb'); auindstest = augmentedimageDatastore(outputsize, indstest, 'Colorpreprocessing", "gray2rgb'); 9 feature extraction from layer 7 featurestrain = activations (net, auindstrain, layer, 'outputAs', ' rows'); featurestest - activations (net, auimdstest, layer, outputAs, , rows'); ine 7 calculate number of examples for troin and test Yrrain - imdsTrain. Labels; Y Extract the class lobels from the training and test data. YTest indstest. Labels: numclasses = numel (categories) fingure) tic Svirid = fitcecocfeatunesTrain, yTrain)