<?PHP
ini_set('memory_limit', '20480M'); // Increase the memory limit to 20480MB (20GB)
include_once("../../CLASSES/Headers.php");
use NameSpaceNumpyLight\NumpyLight;
use NameSpaceRandomGenerator\RandomGenerator;
use NameSpaceActivationRelu\Activation_Relu;
use NameSpaceOptimizerSGD\Optimizer_SGD;
use NameSpaceOptimizerAdagrad\Optimizer_Adagrad;
use NameSpaceOptimizerRMSprop\Optimizer_RMSprop;
function load_mnist_dataset($dataset, $path) {
$labels = [];
$dir = $path . '/' . $dataset;
// Check if the main directory exists and is readable
if (is_readable($dir) && ($dir_content = scandir($dir))) {
foreach ($dir_content as $item) {
if ($item !== '.' && $item !== '..' && is_dir($dir . '/' . $item)) {
$labels[] = $item;
}
}
}
$X = [];
$y = [];
foreach ($labels as $label) {
$label_path = $dir . '/' . $label;
if (is_readable($label_path) && ($files = scandir($label_path))) {
foreach ($files as $file) {
if ($file !== '.' && $file !== '..') {
$filePath = $label_path . '/' . $file;
if (is_readable($filePath) && !is_dir($filePath)) {
$imageProcessor = new ImageProcessor($filePath);
$imageData = $imageProcessor->getImageGrayscaleArray(["rows" => 28, "cols" => 28]);
$X[] = $imageData;
$y[] = $label;
}
}
}
}
}
return ["X" => $X, "y" => $y];
}
function create_data_mnist($path) {
// Load both sets separately
$trainData = load_mnist_dataset('train', $path);
$X = $trainData['X'];
$y = $trainData['y'];
$testData = load_mnist_dataset('test', $path);
$X_test = $testData['X'];
$y_test = $testData['y'];
// And return all the data
return [$X,$y,$X_test,$y_test];
}
$mnist_data = create_data_mnist("fashion_mnist_images");
list($X, $y, $X_test, $y_test) = $mnist_data;
$imageProcessor = new ImageProcessor("");
for ($i=0; $i < 10; $i++) {
$imageProcessor->printGrayscaleArray($X[$i]);
echo "\n\n\n\n\n\n";
}
?>
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