private Task InitCells(IImageFeatureExtractor featureExtractor)
{
return(Task.Run(() =>
{
_completedCells = new Image[GridSize.Height, GridSize.Width];
_targetCellFeatures = new IImageFeatureSet[GridSize.Height, GridSize.Width];
// subdivide the target image into grid of (rows x cols) cells and extract features for each
var resizedTarget = ImageUtils.MakeGrayscale(new Bitmap(2, 2, PixelFormat.Format24bppRgb), TargetImageSize);
using (var g = Graphics.FromImage(resizedTarget))
{
g.DrawImage(TargetImage, 0, 0, TargetImageSize.Width, TargetImageSize.Height);
}
for (int r = 0; r < GridSize.Height; r++)
{
for (int c = 0; c < GridSize.Width; c++)
{
var imageRect = new Rectangle(new Point(CellSize.Width * c, CellSize.Height * r), CellSize);
var cellImage = resizedTarget.Clone(imageRect, PixelFormat.Format24bppRgb);
_targetCellFeatures[r, c] = featureExtractor.ExtractFeatures(cellImage);
}
}
resizedTarget.Dispose();
}));
}
public Task <Image> Build(IImageSource imageSource, IImageFeatureExtractor featureExtractor, CancellationToken cancelToken)
{
return(Task.Run(async() =>
{
await InitCells(featureExtractor);
await AssignImagesToCells(imageSource, featureExtractor, cancelToken);
return await CreateCompletedImage();
}));
}
private Task AssignImagesToCells(IImageSource imageSource, IImageFeatureExtractor featureExtractor, CancellationToken cancelToken)
{
var remainingCells = (from R in Enumerable.Range(0, GridSize.Height)
from C in Enumerable.Range(0, GridSize.Width)
select new { R, C, Target = GetTargetCell(R, C) }).ToArray();
return(Task.Run(async() =>
{
while (!cancelToken.IsCancellationRequested)
{
if (IsComplete)
{
System.Console.WriteLine("Mosaic is complete!");
break;
}
var nextImage = await imageSource.GetNextImage(cancelToken);
if (nextImage != null)
{
System.Console.WriteLine($"Attempting to match image {nextImage.Id} with remaining {remainingCells.Count()} cells...");
var nextImageReduced = ImageUtils.MakeGrayscale(nextImage.RawImage, CellSize);
var features = featureExtractor.ExtractFeatures(nextImageReduced);
remainingCells = remainingCells.Where(c => GetCompletedCell(c.R, c.C) == null).ToArray();
foreach (var cell in remainingCells.Where(c => features.IsMatch(c.Target)))
{
SetCompletedCell(cell.R, cell.C, nextImageReduced);
System.Console.WriteLine($" MATCH: '{nextImage.Id}' --> cell r:{cell.R}, c:{cell.C}");
}
nextImage.RawImage.Dispose();
}
else
{
// hacky, fix this up
System.Console.WriteLine("ERROR: Failed to retreive any images, quitting...");
break;
}
}
}));
}
Create <TExtractor, TClustering>(IImageFeatureExtractor <FeatureDescriptor> detector, TClustering clustering)
where TClustering : IUnsupervisedLearning <IClassifier <double[], int>, double[], int>
{
return(new BagOfVisualWords <FeatureDescriptor, double[], TClustering, IImageFeatureExtractor <FeatureDescriptor> >(detector, clustering));
}
/// <summary>
/// Constructs a new <see cref="BagOfVisualWords"/>.
/// </summary>
///
/// <param name="extractor">The feature extractor to use.</param>
/// <param name="algorithm">The clustering algorithm to use.</param>
///
public BagOfVisualWords(IImageFeatureExtractor <TPoint> extractor, //IClusteringAlgorithm<double[]>
IUnsupervisedLearning <IClassifier <double[], int>, double[], int> algorithm)
{
base.Init(extractor, algorithm);
}
/// <summary>
/// Constructs a new <see cref="BagOfVisualWords"/>.
/// </summary>
///
/// <param name="extractor">The feature extractor to use.</param>
/// <param name="numberOfWords">The number of codewords.</param>
///
public BagOfVisualWords(IImageFeatureExtractor <TPoint> extractor, int numberOfWords)
{
base.Init(extractor, BagOfWords.GetDefaultClusteringAlgorithm(numberOfWords));
}
/// <summary>
/// Constructs a new <see cref="BagOfVisualWords"/>.
/// </summary>
///
/// <param name="extractor">The feature extractor to use.</param>
/// <param name="algorithm">The clustering algorithm to use.</param>
///
public BagOfVisualWords(IImageFeatureExtractor <TPoint> extractor,
IUnsupervisedLearning <IClassifier <TFeature, int>, TFeature, int> algorithm)
{
Init(extractor, algorithm);
}
