public ColorClusteredBitmap(string originalImagePath, string convertedImagePath, WeightedColorSet histogram)
{
OriginalImagePath = originalImagePath;
ConvertedImagePath = convertedImagePath;
Histogram = histogram;
Colors = histogram.Colors.Select(c => c.Color.ToWindowsColor()).ToArray();
ColorWeights = histogram.Colors.Select(c => c.PixelCount).ToArray();
}
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;
}