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(); }