private async void GenerateMosaic(object sender, RoutedEventArgs e)
{
var availableSources = sources.ToList();
var sourcePixels = sampledBitmap.Pixels.Select(p => ColorSpaces.CieLab.ConvertFromStandardRgb(p)).ToArray();
ColorClusteredBitmap[] targetPixelImages = new ColorClusteredBitmap[sourcePixels.Length];
int progressIndex = 0;
var timer = InitializeProgress(targetPixelImages.Length * 2, () => progressIndex);
await Task.Run(() =>
{
for (; progressIndex < sampledBitmap.Pixels.Length; progressIndex++)
{
targetPixelImages[progressIndex] = FindBestMatchAndRemove(sourcePixels[progressIndex], ColorSpaces.CieLab, availableSources);
}
});
FinishProgress(timer);
const double maxSize = 23000;
double scaleXFit = Math.Min(1, maxSize / (sampledBitmap.Width * averageWidth));
double scaleYFit = Math.Min(1, maxSize / (sampledBitmap.Height * averageHeight));
double scaleFit = Math.Min(scaleXFit, scaleYFit);
int cellWidth = (int)(averageWidth * scaleFit);
int cellHeight = (int)(averageHeight * scaleFit);
var output = await CreateOutputBitmap(targetPixelImages, sampledBitmap.Width, sampledBitmap.Height, (int)(averageWidth *scaleFit), (int)(averageHeight *scaleFit));
SimplifiedBitmap.Source = output;
SimplifiedBitmap.Width = output.PixelWidth;
SimplifiedBitmap.Height = output.PixelHeight;
}
private float DistanceTo(ColorClusteredBitmap other, IReadOnlyList <int> indexLookup)
{
float distance = 0;
for (int i = 0; i < this.Histogram.Colors.Count; i++)
{
float thisWeight = (float)this.Histogram.Colors[i].PixelCount / this.Histogram.PixelCount;
float otherWeight = (float)other.Histogram.Colors[indexLookup[i]].PixelCount / other.Histogram.PixelCount;
float distanceSquared = Vector3.DistanceSquared((Vector3)this.Histogram.Colors[i].Color.ToCieLab(), (Vector3)other.Histogram.Colors[indexLookup[i]].Color.ToCieLab());
distance += distanceSquared * (thisWeight + otherWeight) / 2;
}
return(distance);
}
private async void PopulateImagesAsync(string originalImages, string computedImages)
{
string[] originalFilePaths = Directory.GetFiles(originalImages, "*.png").Concat(Directory.GetFiles(originalImages, "*.jpg")).ToArray();
string[] computedFilesPaths = Directory.GetFiles(computedImages, "*.png");
Tuple <string, string>[] joinedPaths = originalFilePaths.Join(computedFilesPaths, o => Path.GetFileNameWithoutExtension(o), i => GetPrefix(i), (o, i) => Tuple.Create(o, i)).ToArray();
ColorClusteredBitmap[] bitmaps = new ColorClusteredBitmap[originalFilePaths.Length];
int progress = 0;
var timer = InitializeProgress(joinedPaths.Length, () => progress);
long totalWidths = 0;
long totalHeights = 0;
await Task.Run(() =>
{
Parallel.For(0, joinedPaths.Length, i =>
{
string histogramFile = Path.Combine(Path.GetDirectoryName(joinedPaths[i].Item2), "colorHistograms", $"{Path.GetFileNameWithoutExtension(joinedPaths[i].Item2)}.json");
if (File.Exists(histogramFile))
{
WeightedColorSet set = JsonConvert.DeserializeObject <WeightedColorSet>(File.ReadAllText(histogramFile));
bitmaps[i] = new ColorClusteredBitmap(joinedPaths[i].Item1, joinedPaths[i].Item2, set);
Interlocked.Add(ref totalWidths, bitmaps[i].Histogram.PixelWidth);
Interlocked.Add(ref totalHeights, bitmaps[i].Histogram.PixelHeight);
}
Interlocked.Increment(ref progress);
});
});
FinishProgress(timer);
foreach (ColorClusteredBitmap result in bitmaps.Where(b => b != null))
{
sources.Add(result);
}
averageWidth = (int)(totalWidths / sources.Count);
averageHeight = (int)(totalHeights / sources.Count);
averageAspectRatio = (float)totalWidths / totalHeights;
}
public float DistanceTo(ColorClusteredBitmap other, bool usePermutations)
{
float distance = float.MaxValue;
if (usePermutations)
{
foreach (var permutation in Permutation.GetPermutations(this.Histogram.Colors.Count))
{
float newDistance = DistanceTo(other, permutation);
if (newDistance < distance)
{
distance = newDistance;
}
}
}
else
{
distance = DistanceTo(other, Permutation.GetPermutations(this.Histogram.Colors.Count).First());
}
return(distance);
}