private void OpenDialog_Click(object sender, RoutedEventArgs e) { var dialog = new FolderBrowserDialog { SelectedPath = Environment.GetFolderPath(Environment.SpecialFolder.MyPictures) }; var result = dialog.ShowDialog(this.GetIWin32Window()); var viewModel = new ImageViewModel(); if (result == System.Windows.Forms.DialogResult.OK) { foreach (var model in Directory.EnumerateFiles(dialog.SelectedPath, "*.*") .Where(file => _imageFileExtensions.Any(x => file.EndsWith(x, StringComparison.OrdinalIgnoreCase))) .Select(filePath => new ImageModel(new BitmapImage(new Uri(filePath))))) { viewModel.Images.Add(model); } ImagesGrid.DataContext = viewModel; } }
private void PerformClassification(List<Bitmap> circles, List<Bitmap> triangles, List<Bitmap> rectangles, ImageViewModel viewModel) { var signData = new Dictionary<Bitmap, Sign>(); foreach (var circle in circles) { var colorInfo = ColorInfo.Extract(circle); signData.Add(circle, new Sign(100, colorInfo[0], colorInfo[1], colorInfo[2], colorInfo[3])); } foreach (var triangle in triangles) { var colorInfo = ColorInfo.Extract(triangle); signData.Add(triangle, new Sign(50, colorInfo[0], colorInfo[1], colorInfo[2], colorInfo[3])); } foreach (var rectangle in rectangles) { var colorInfo = ColorInfo.Extract(rectangle); signData.Add(rectangle, new Sign(150, colorInfo[0], colorInfo[1], colorInfo[2], colorInfo[3])); } var containers = new[] { null, viewModel.WarningSigns, viewModel.ProhibitingSigns, viewModel.RegulatorySigns, viewModel.InformationSigns, viewModel.TemporarySigns }; var tc = new PrebuildSignsClassifier(); tc.Teach(); foreach (var sign in signData) { var classIndex = tc.FindClass(sign.Value); var resizedImage = BilinearInterpolation.Resize(sign.Key, 150, 150); containers[classIndex].Add(new ImageModel(BitmapConverter.GetBitmapSource(resizedImage))); } }
private void PerformClassification(List<Bitmap>[] circles, List<Bitmap>[] triangles, List<Bitmap>[] rectangles, ImageViewModel viewModel) { var signData = new Dictionary<Bitmap[], Sign>(); for (int i = 0; i < circles[1].Count; i++) { var circle = circles[1][i]; var colorInfo = ColorInfo.Extract(circle); signData.Add(new[] { circles[0][i] , circles[1][i] }, new Sign(100, colorInfo[0], colorInfo[1], colorInfo[2], colorInfo[3])); } for (int i = 0; i < triangles[1].Count; i++) { var triangle = triangles[1][i]; var colorInfo = ColorInfo.Extract(triangle); signData.Add(new[] { triangles[0][i], triangles[1][i] }, new Sign(50, colorInfo[0], colorInfo[1], colorInfo[2], colorInfo[3])); } for (int i = 0; i < rectangles[1].Count; i++) { var rectangle = rectangles[1][i]; var colorInfo = ColorInfo.Extract(rectangle); signData.Add(new[] { rectangles[0][i], rectangles[1][i] }, new Sign(150, colorInfo[0], colorInfo[1], colorInfo[2], colorInfo[3])); } var containers = new[] { viewModel.WarningSigns, viewModel.ProhibitingSigns, viewModel.RegulatorySigns, viewModel.InformationSigns, viewModel.TemporarySigns }; var formatter = new BinaryFormatter(); Stream stream = new FileStream("..\\..\\..\\perceptrons.bin", FileMode.Open, FileAccess.Read, FileShare.None); var perceptrons = (List<Perceptron>)formatter.Deserialize(stream); stream.Close(); var tc = new PrebuildSignsClassifier(); tc.Teach(); var signsViewModel = (SignsGrid.DataContext) as SignViewModel; signsViewModel.Signs.Clear(); foreach (var sign in signData) { var groupIndex = tc.FindClass(sign.Value) - 1; var signsImageSource = BitmapConverter.GetBitmapSource(sign.Key[1]); containers[groupIndex].Add(new ImageModel(signsImageSource)); var perceptron = perceptrons[groupIndex]; var histogram = HistogramExtracter.Process(BilinearInterpolation.Resize(sign.Key[0], ResizeWidth, ResizeHeight)); var classificationResult = perceptron.Classify(histogram).ToList(); var classIndex = classificationResult.IndexOf(classificationResult.Max()); var description = SignDescription.Get(groupIndex, classIndex); signsViewModel.Signs.Add(new SignModel(signsImageSource, description)); } }