private void Window_Loaded_1(object sender, RoutedEventArgs e)
{
const string baseUri = @"C:\Users\Dmitry\Pictures\DPSI\";
_knowledgeImages[0] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "A")));
_width = _knowledgeImages[0].PixelWidth;
_height = _knowledgeImages[0].PixelHeight;
_pixelsNumber = _width * _height;
_knowledgeImages[1] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "C")));
_knowledgeImages[2] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "K")));
_knowledgeImages[3] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "A2")));
_knowledgeImages[4] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "C2")));
_knowledgeImages[5] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "K2")));
_knowledgeImages[6] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "A3")));
_knowledgeImages[7] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "C3")));
_knowledgeImages[8] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "K3")));
for (int i = 0; i < NumberOfImages; i++)
{
_knowledgeMatrix[i] = GetImageVector(BitmapConverter.BitmapImage2Bitmap(_knowledgeImages[i]));
}
W = new double[_pixelsNumber, NumberOfClasses];
for (int i = 0; i < _pixelsNumber; i++)
{
for (int j = 0; j < NumberOfClasses; j++)
{
W[i, j] = 1;
}
}
InitFrequency();
Y = new double[NumberOfClasses];
StartLearning();
var learningResults = new List <LearningResult>();
for (int i = 0; i < _knowledgeImages.Length; i++)
{
learningResults.Add(new LearningResult
{
Image = _knowledgeImages[i],
ClassNumnber = RecognizeClass(_knowledgeImages[i])
});
}
var learningResultsWindow = new LearningResultsWindow(learningResults);
learningResultsWindow.Show();
}
private void Window_Loaded_1(object sender, RoutedEventArgs e)
{
const string baseUri = @"C:\Users\Dmitry\Pictures\DPSI\";
_knowledgeImages[0] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "A")));
_width = _knowledgeImages[0].PixelWidth;
_height = _knowledgeImages[0].PixelHeight;
_pixelsNumber = _width * _height;
_knowledgeImages[1] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "C")));
_knowledgeImages[2] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "K")));
_knowledgeImages[3] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "A2")));
_knowledgeImages[4] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "C2")));
_knowledgeImages[5] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "K2")));
_knowledgeImages[6] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "A3")));
_knowledgeImages[7] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "C3")));
_knowledgeImages[8] = new BitmapImage(new Uri(string.Format("{0}{1}.png", baseUri, "K3")));
for (int i = 0; i < NumberOfImages; i++)
{
_knowledgeMatrix[i] = GetImageVector(BitmapConverter.BitmapImage2Bitmap(_knowledgeImages[i]));
}
W = new double[_pixelsNumber, NumberOfClasses];
for (int i = 0; i < _pixelsNumber; i++)
{
for (int j = 0; j < NumberOfClasses; j++)
{
W[i, j] = 1;
}
}
InitFrequency();
Y = new double[NumberOfClasses];
StartLearning();
var learningResults = new List<LearningResult>();
for(int i = 0; i < _knowledgeImages.Length; i++)
{
learningResults.Add(new LearningResult
{
Image = _knowledgeImages[i],
ClassNumnber = RecognizeClass(_knowledgeImages[i])
});
}
var learningResultsWindow = new LearningResultsWindow(learningResults);
learningResultsWindow.Show();
}
