public IEnumerable <Match> FindMatches(IPattern Template, double Similarity)
{
using var result = new DisposableMat();
// max is used for tmccoeff
Imgproc.MatchTemplate(Mat, (Template as DroidCvPattern)?.Mat, result.Mat, Imgproc.TmCcoeffNormed);
Imgproc.Threshold(result.Mat, result.Mat, 0.1, 1, Imgproc.ThreshTozero);
while (true)
{
using var minMaxLocResult = Core.MinMaxLoc(result.Mat);
var score = minMaxLocResult.MaxVal;
if (score >= Similarity)
{
var loc = minMaxLocResult.MaxLoc;
var region = new Region((int)loc.X, (int)loc.Y, Template.Width, Template.Height);
yield return(new Match(region, score));
using var mask = new DisposableMat();
// Flood fill eliminates the problem of nearby points to a high similarity point also having high similarity
const double floodFillDiff = 0.05;
Imgproc.FloodFill(result.Mat, mask.Mat, loc, new Scalar(0),
new Rect(),
new Scalar(floodFillDiff), new Scalar(floodFillDiff),
0);
}
else
{
break;
}
}
}
public IPattern Crop(Region Region)
{
Region = new Region(0, 0, Width, Height)
.Clip(Region);
var rect = new Rect(Region.X, Region.Y, Region.W, Region.H);
var result = new Mat(Mat, rect);
return(new DroidCvPattern(result));
}
public IPattern Crop(Region Region)
{
var rect = new Rect(Region.X, Region.Y, Region.W, Region.H);
if (rect.X + rect.Width > Width)
{
rect.X = Width - rect.Width;
}
if (rect.Y + rect.Height > Height)
{
rect.Y = Height - rect.Height;
}
var result = new Mat(Mat, rect);
return(new DroidCvPattern(result));
}