write a video processing code using cnn to detect epilepsy in matlab

main.m
% Load the pre-trained CNN
net = alexnet;

% Specify the layers to be replaced
layers = net.Layers;
layers(end-2) = fullyConnectedLayer(2);
layers(end) = classificationLayer;

% Load the training data
imds = imageDatastore('epilepsyImages','IncludeSubfolders',true,'LabelSource','foldernames');
[imdsTrain, imdsValidation] = splitEachLabel(imds,0.7,'randomize');

% Specify the training options
options = trainingOptions('sgdm', ...
    'MiniBatchSize',10, ...
    'MaxEpochs',10, ...
    'InitialLearnRate',1e-4, ...
    'ValidationData',imdsValidation, ...
    'ValidationFrequency',3, ...
    'Verbose',false, ...
    'Plots','training-progress');

% Train the network
net = trainNetwork(imdsTrain,layers,options);

% Load the test video
video = VideoReader('epilepsyVideo.avi');
numFrames = video.Framerate * video.Duration;

% Specify the output file
outputVideo = VideoWriter('epilepsyDetection.avi');
outputVideo.FrameRate = video.Framerate;
open(outputVideo);

% Process each frame of the video
for i = 1:numFrames
    frame = readFrame(video);
    
    % Resize and pre-process the frame
    inputSize = net.Layers(1).InputSize;
    newFrame = imresize(frame,inputSize(1:2));
    newFrame = augmentedImageDatastore(inputSize,newFrame);
    newFrame = read(newFrame);
    newFrame = im2double(newFrame);
    
    % Make a prediction using the CNN
    [pred,scores] = classify(net,newFrame);
    
    % Overlay the prediction on the video frame
    if pred == 'epilepsy'
        frame = insertText(frame,[10 10],char(pred),'FontSize',18,'BoxColor','red','TextColor','white');
    end
    
    % Write the frame to the output file
    writeVideo(outputVideo,frame);
end

% Close the output file
close(outputVideo);
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