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));
}
}
private async void ProcessFolder_Click(object sender, RoutedEventArgs e)
{
var dialog = new FolderBrowserDialog
{
SelectedPath = Environment.GetFolderPath(Environment.SpecialFolder.MyPictures)
};
var result = dialog.ShowDialog(this.GetIWin32Window());
var storage = new Dictionary <string, Bitmap>();
if (result == System.Windows.Forms.DialogResult.OK)
{
foreach (var path in Directory.EnumerateFiles(dialog.SelectedPath, "*.*", SearchOption.AllDirectories)
.Where(file => _imageFileExtensions.Any(x => file.EndsWith(x, StringComparison.OrdinalIgnoreCase))))
{
var bitmap = BitmapConverter.GetBitmap(new BitmapImage(new Uri(path)));
bitmap = (from object filterObject in FiltersMenu.ItemsSource
select(filterObject as FilterModel) into filterModel
where filterModel.Enabled
select filterModel.Filter)
.Aggregate(bitmap, (current, filter) => filter.Process(current));
var binarizedImage = BitmapBinarizer.Process(bitmap);
var linesTask = HoughTransform.GetLines(binarizedImage);
var circlesTask = HoughTransform.GetCircles(binarizedImage);
var rectanglesBitmaps = await RectanglesExtractor.Extract(bitmap, bitmap, binarizedImage, await linesTask, true);
var trianglesBitmaps = await TrianglesExtractor.Extract(bitmap, bitmap, binarizedImage, await linesTask, true);
var circleBitmaps = await CirclesExtractor.Extract(bitmap, bitmap, await circlesTask, true);
bitmap =
rectanglesBitmaps[0].Concat(trianglesBitmaps[0])
.Concat(circleBitmaps[0])
.OrderBy(b => b.Width * b.Height).Last();
storage.Add(path, bitmap);
}
}
foreach (var element in storage)
{
BilinearInterpolation.Resize(element.Value, ResizeWidth, ResizeHeight)
.Save(element.Key + ".processed.bmp", ImageFormat.Bmp);
}
}
public Bitmap Resize1920x1080Frame() => _scaling.Resize(_frame1920x1080, _scaleX, _scaleY);
