partial face recognition using CNN-alexnet

an arror occured while implementing face recognition using CNN -alexnet.please help me to move the project.

 clc
clear
n=1;
im = imageDatastore('images','IncludeSubfolders',true,'LabelSource','foldernames');

% Resize the images to the input size of the net
 im.ReadFcn = @(loc)imresize(imread(loc),[227,227]);
 [Train ,Test] = splitEachLabel(im,0.8,'randomized');
 fc = fullyConnectedLayer(n);
 net = alexnet;
 ly = net.Layers;
 ly(23) = fc;
 cl = classificationLayer;
 ly(25) = cl; 
 % options for training the net if your newnet performance is low decrease
 % the learning_rate
 learning_rate = 0.00001;
 opts = trainingOptions("rmsprop","InitialLearnRate",learning_rate,'MaxEpochs',5,'MiniBatchSize',64,'Plots','training-progress');
 [newnet,info] = trainNetwork(Train, ly, opts);
 [predict,scores] = classify(newnet,Test);
 names = Test.Labels;
 pred  = (predict==names);
 s = size(pred);
 acc = sum(pred)/s(1);
 fprintf('The accuracy of the test set is %f %% \n',acc*100);

 
 
 
 
 
 %%%%ERROR%%%%
 
 
 
 Training on single CPU.
Initializing input data normalization.
Error using trainNetwork (line 170)
Unexpected image size: All images must have the same size.

Error in work2 (line 21)
 [newnet,info] = trainNetwork(Train, ly, opts);
 
>> 

Answer 1

[Srivardhan Gadila]

Make sure that all the images have the same number of channels.

Make use of the following:

im = imageDatastore('images','IncludeSubfolders',true,'LabelSource','foldernames');
im.ReadFcn = @customReadDatstoreImage;
function data = customReadDatastoreImage(filename)
% code from default function: 
onState = warning('off', 'backtrace'); 
c = onCleanup(@() warning(onState)); 
data = imread(filename); % added lines: 
data = data(:,:,min(1:3, end)); 
data = imresize(data,[227 227]);
end

Refer to the following: How can i resize image stored in imageDatastore

Alternatively you can load the images using imageDatastore and then use the augmentedImageDatastore for resizing the images.

[Munshida P]

okey sir....Thank you. I will implement and will be back with the results...