neural network for predicting the percentage of blurring in an image in matlab

main.m
% Load the image dataset
imds = imageDatastore('path/to/images','IncludeSubfolders',true,'FileExtensions','.jpg');

% Define the layers of the neural network
layers = [
    imageInputLayer([256 256 3])
    convolution2dLayer(3,16,'Padding','same')
    reluLayer
    maxPooling2dLayer(2,'stride',2)
    convolution2dLayer(3,32,'Padding','same')
    reluLayer
    maxPooling2dLayer(2,'stride',2)
    fullyConnectedLayer(1)
    regressionLayer
    ];

% Divide the dataset into training and testing sets
[trainSet,testSet] = splitEachLabel(imds,0.8);

% Train the neural network
options = trainingOptions('adam', ...
    'InitialLearnRate',0.0001, ...
    'MaxEpochs',10, ...
    'MiniBatchSize',32, ...
    'Shuffle','every-epoch', ...
    'ValidationData',testSet, ...
    'ValidationFrequency',30, ...
    'Verbose',false, ...
    'Plots','training-progress');
net = trainNetwork(trainSet,layers,options);

% Predict the percentage of blurring in a test image
testImage = imread('path/to/test/image.jpg');
blurringPercentage = predict(net,testImage);

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