public ImageData(string path, string correspondingValue, Emgu.CV.Features2D.ORBDetector orbDetector, KAZE featureDetector)
{
this.path = path;
this.image = new Image <Bgr, byte>(path);
orbDetector.DetectAndCompute(image, null, keyPointsOrb, descriptorOrb, false);
UMat uObservedImage = image.Mat.GetUMat(AccessType.Read);
//featureDetector.DetectAndCompute(image, null, keyPointsSurf, descriptorSurf, false);
featureDetector.DetectAndCompute(uObservedImage, null, keyPointsSurf, descriptorSurf, false);
this.correspondingValue = correspondingValue;
}
private double DetectTemplate(Mat observedImage, TemplateContainer.ImageData template)
{
orbDetector.DetectAndCompute(observedImage, null, observedKeyPoints, observedDescriptor, false);
if (template.keyPointsOrb.Size > 0 && observedKeyPoints.Size > 0)
{
BFMatcher matcher = new BFMatcher(DistanceType.L2);
matcher.Add(template.descriptorOrb);
VectorOfVectorOfDMatch matches = new VectorOfVectorOfDMatch();
matcher.KnnMatch(observedDescriptor, matches, 2, null);
//Copied
Mat mask = new Mat(matches.Size, 1, DepthType.Cv8U, 1);
mask.SetTo(new MCvScalar(255));
Features2DToolbox.VoteForUniqueness(matches, 0.8, mask);
if (matches.Size == 0)
{
return(0.0);
}
else
{
int nonZeroCount = CvInvoke.CountNonZero(mask);
double nonZeroCountNormalized = 1.0 * nonZeroCount / template.keyPointsOrb.Size;
if (nonZeroCount > 3)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(template.keyPointsOrb, observedKeyPoints, matches, mask, 1.8, 18);
nonZeroCountNormalized = 1.0 * nonZeroCount / template.keyPointsOrb.Size;
return(nonZeroCount);
}
return(0.0);
}
}
else
{
return(0.0);
}
}