Invalid training or validation response data

Hello, I am training a neural network with semantic segmentation data and I have the following error:

Error using trainNetwork (line 184)

Maximum variable size allowed on the device is exceeded.

Error in index (line 48)

net = trainNetwork(trainingData,layers,opts);

Caused by:

Error using gpuArray

Maximum variable size allowed on the device is exceeded.

I believe this is because the input sizes of my images are quite high: imageInputLayer([8000 6000 3])

I used a @customreader function to resize the images in my imageDatastore and pixelLabelDatastore as follows: imds.ReadFcn = @customreader; and pxds.ReadFcn = @customreader;

However, it is returning the following error:

Error using trainNetwork (line 184)

Invalid training or validation response data. Categorical responses must

either be a vector or a single-channel 2-D or 3-D image.

Error in index (line 48)

net = trainNetwork(trainingData,layers,opts);

I'll leave the code I'm using:

clear, clc, close all;

%% Upload a set of images for training
imds = imageDatastore('Imagens');
imds.ReadFcn = @customreader;
 
I = readimage(imds,1);

%% Load pixel label images using pixelLabelDatastore
pxDir = fullfile('PixelLabelData');
classNames = ["Escala" "Fundo"];
pixelLabelID = [1 2];

pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
pxds.ReadFcn = @customreader;
C = readimage(pxds,1);

%% Create a binary mask
buildingMask = C == 'Escala';
%figure
%imshowpair(I, buildingMask,'montage')

%% Create a semantic segmentation network

numFilters = 64;
filterSize = 3;
numClasses = 2;
layers = [
    imageInputLayer([8000 6000 3])
    convolution2dLayer(filterSize,numFilters,'Padding',1)
    reluLayer()
    maxPooling2dLayer(2,'Stride',2)
    convolution2dLayer(filterSize,numFilters,'Padding',1)
    reluLayer()
    transposedConv2dLayer(4,numFilters,'Stride',2,'Cropping',1);
    convolution2dLayer(1,numClasses);
    softmaxLayer()
    pixelClassificationLayer()
    ];

opts = trainingOptions('sgdm', ...
    'InitialLearnRate',1e-3, ...
    'MaxEpochs',100, ...
    'MiniBatchSize',64);

trainingData = combine(imds,pxds);

net = trainNetwork(trainingData,layers,opts);

The function to resize imageDatastore and pixelLabelDatastore:

function data = customreader(filename)
onState = warning('off', 'backtrace');
c = onCleanup(@() warning(onState));
data = imread(filename);
data = data(:,:,min(1:3, end)); 
data = imresize(data, [100 75]);
end

I'll also leave a folder on the drive with all the files I'm using:

https://drive.google.com/drive/folders/14cmvfO5yrexLScG1_KyI9hFfgCIuZhHH?usp=share_link

If you can help me, I will be very grateful.