public void ReadTrainMNIST()
{
try
{
FileStream ifsLabels =
new FileStream(@"C:\Users\cleist\BA\MNIST\train-labels.idx1-ubyte", FileMode.Open); // train labels
FileStream ifsImages =
new FileStream(@"C:\Users\cleist\BA\MNIST\train-images.idx3-ubyte", FileMode.Open); // train images
BinaryReader brLabels = new BinaryReader(ifsLabels);
BinaryReader brImages = new BinaryReader(ifsImages);
int magic1 = BigEndianConverter.ReadBigInt32(brImages); // discard
int numImages = BigEndianConverter.ReadBigInt32(brImages);
int numRows = BigEndianConverter.ReadBigInt32(brImages);
int numCols = BigEndianConverter.ReadBigInt32(brImages);
int magic2 = BigEndianConverter.ReadBigInt32(brLabels);
int numLabels = BigEndianConverter.ReadBigInt32(brLabels);
byte[][] pixels = new byte[numRows][];
for (int i = 0; i < pixels.Length; ++i)
{
pixels[i] = new byte[numCols];
}
// each image
for (int di = 0; di < 1000; ++di)
{
for (int i = 0; i < numRows; ++i)
{
for (int j = 0; j < numCols; ++j)
{
byte b = brImages.ReadByte();
pixels[i][j] = b;
}
}
byte lbl = brLabels.ReadByte();
TrainingImgs.Add(new DigitImage(pixels, lbl, numRows, numCols));
}
ifsImages.Close();
brImages.Close();
ifsLabels.Close();
brLabels.Close();
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
Console.ReadLine();
}
}
public void ShuffleTrainingImgs()
{
var rnd = new Random();
TrainingImgs = TrainingImgs.OrderBy(x => rnd.Next()).ToList();
}
