create a semantic segmentation algorithm using net = inceptionresnetv2; in matlab

main.m
% Load the CamVid dataset
imds = imageDatastore('CamVid', 'IncludeSubfolders', true, 'LabelSource', 'foldernames');

% Define the network
net = inceptionresnetv2;

% Specify the input size of the network to match the size of the images in the dataset
inputSize = net.Layers(1).InputSize;
imds.ReadFcn = @(loc)imresize(imread(loc), inputSize(1:2));

% Specify training options
options = trainingOptions('adam', ...
    'LearnRateSchedule', 'piecewise', ...
    'LearnRateDropPeriod', 8, ...
    'LearnRateDropFactor', 0.1, ...
    'InitialLearnRate', 0.0001, ...
    'L2Regularization', 0.001, ...
    'MaxEpochs', 50, ...
    'MiniBatchSize', 16);

% Train the network on the dataset
trainedNet = trainNetwork(imds, net, options);

% Test the trained network on a new image
testImage = imread('testImage.png');
testImageResized = imresize(testImage, inputSize(1:2));
predictedLabels = classify(trainedNet, testImageResized);
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