public void TestNetwork(MNistImage[] images, CancellationToken cancellation)
{
Debug.AssertNotNull(images);
Debug.AssertNotNull(cancellation);
if (_statRefresher != null && _statRefresher.Started) return;
_cancelTrainToken = cancellation;
var normalImages = new NormalizedImage[images.Length];
for (var i = 0; i < images.Length; i++)
{
normalImages[i] = new NormalizedImage(images[i]);
normalImages[i].PadCanvas(Network.InputImageWidth, Network.InputImageHeight);
}
_testInfoBuffer.Clear();
_imageProcessed = 0;
_errors.Clear();
_totalMSE = 0.0;
_statRefresher = new ActionRepeater(PrintTestingInfo, 1000.0);
_statRefresher.Start(false);
TestProcess(normalImages);
_statRefresher.Stop(true);
History = txtStatistics.Text;
}
public static MNistImage[] GetImageSet(string labelsPath, string imagesPath)
{
Debug.Assert(labelsPath != null && imagesPath != null);
var imagesBytes = File.ReadAllBytes(imagesPath);
if (ConvertFromBigEndian(imagesBytes, 0) != Idx3MagicNumber)
throw new FormatException("Неверный формат файла изображений");
var imagesCount = ConvertFromBigEndian(imagesBytes, sizeof (int));
var imageHeight = ConvertFromBigEndian(imagesBytes, sizeof (int)*2);
var imageWidth = ConvertFromBigEndian(imagesBytes, sizeof (int)*3);
var imageLength = imageWidth*imageHeight;
if (imagesCount != (imagesBytes.Length - Idx3DataOffset)/imageLength)
throw new FormatException("Файл изображений поврежден");
var labelsBytes = File.ReadAllBytes(labelsPath);
if (ConvertFromBigEndian(labelsBytes, 0) != Idx1MagicNumber)
throw new FormatException("Неверный формат файла подписей");
var labelsCount = ConvertFromBigEndian(labelsBytes, sizeof (int));
if (labelsCount != labelsBytes.Length - Idx1DataOffset)
throw new FormatException("Файл подписей поврежден");
if (imagesCount != labelsCount)
throw new Exception("Количество изображений не совпадает с количеством подписей");
// получаем все изображения
var images = new MNistImage[imagesCount];
for (var i = 0; i < images.Length; i++)
{
var label = (int) labelsBytes[Idx1DataOffset + i];
Debug.Assert(label < 10, label.ToString());
var imageBytes = new byte[imageWidth][];
for (var r = 0; r < imageHeight; r++)
{
imageBytes[r] = new byte[imageHeight];
Buffer.BlockCopy(imagesBytes, Idx3DataOffset + i*imageLength + r*imageWidth,
imageBytes[r], 0, imageWidth);
}
images[i] = new MNistImage(label, imageBytes);
}
return images;
}
public void TrainNetwork(MNistImage[] images, CancellationToken cancellation)
{
Debug.AssertNotNull(images);
Debug.Assert(cancellation != null);
if (_statRefresher != null && _statRefresher.Started) return;
_cancelTrainToken = cancellation;
var normalImages = new NormalizedImage[images.Length];
for (var i = 0; i < images.Length; i++)
normalImages[i] = new NormalizedImage(images[i]);
_statRefresher = new ActionRepeater(PrintTrainingInfo, 1000.0);
_statRefresher.Start(false);
TrainProcess(normalImages);
_statRefresher.Stop(true);
History = txtStatistics.Text;
}
