public void FindMatch(Image <Gray, byte> modelImage, Image <Gray, byte> observedImage, double hessianThresh, int k,
double uniquenessThreshold, VectorOfVectorOfDMatch matches, out VectorOfKeyPoint modelKeyPoints,
out VectorOfKeyPoint observedKeyPoints, out Mat mask, out Mat homography)
{
homography = null;
modelKeyPoints = new VectorOfKeyPoint();
observedKeyPoints = new VectorOfKeyPoint();
CudaSURFDetector surfCuda = new CudaSURFDetector((float)hessianThresh);
using (GpuMat gpuModelImage = new GpuMat(modelImage))
//extract features from the object image
using (GpuMat gpuModelKeyPoints = surfCuda.DetectKeyPointsRaw(gpuModelImage, null))
using (
GpuMat gpuModelDescriptors = surfCuda.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
using (CudaBFMatcher matcher = new CudaBFMatcher(DistanceType.L2))
{
surfCuda.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
// extract features from the observed image
using (GpuMat gpuObservedImage = new GpuMat(observedImage))
using (GpuMat gpuObservedKeyPoints = surfCuda.DetectKeyPointsRaw(gpuObservedImage, null))
using (
GpuMat gpuObservedDescriptors = surfCuda.ComputeDescriptorsRaw(gpuObservedImage, null,
gpuObservedKeyPoints))
{
matcher.KnnMatch(gpuObservedDescriptors, gpuModelDescriptors, matches, k);
surfCuda.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);
mask = new Mat(matches.Size, 1, DepthType.Cv8U, 1);
mask.SetTo(new MCvScalar(255));
Features2DToolbox.VoteForUniqueness(matches, uniquenessThreshold, mask);
int nonZeroCount = CvInvoke.CountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints,
matches, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints,
observedKeyPoints, matches, mask, 2);
}
}
}
}
}
public void TestCudaSURFKeypointDetection()
{
if (CudaInvoke.HasCuda)
{
Image <Gray, byte> image = new Image <Gray, byte>(200, 100);
image.SetRandUniform(new MCvScalar(), new MCvScalar(255));
GpuMat gpuMat = new GpuMat(image);
EmguAssert.IsTrue(gpuMat.ToMat().Equals(image.Mat));
CudaSURFDetector cudaSurf = new CudaSURFDetector(100.0f, 2, 4, false, 0.01f, false);
GpuMat cudaKpts = cudaSurf.DetectKeyPointsRaw(gpuMat, null);
VectorOfKeyPoint kpts = new VectorOfKeyPoint();
cudaSurf.DownloadKeypoints(cudaKpts, kpts);
}
}
public static void FindMatch(Image <Gray, Byte> modelImage, Image <Gray, byte> observedImage, out long matchTime, out VectorOfKeyPoint modelKeyPoints, out VectorOfKeyPoint observedKeyPoints, VectorOfVectorOfDMatch matches, out Matrix <byte> mask, out HomographyMatrix homography)
{
int k = 2;
double uniquenessThreshold = 0.8;
double hessianThresh = 300;
Stopwatch watch;
homography = null;
modelKeyPoints = new VectorOfKeyPoint();
observedKeyPoints = new VectorOfKeyPoint();
#if !IOS
if (CudaInvoke.HasCuda)
{
CudaSURFDetector surfCuda = new CudaSURFDetector((float)hessianThresh);
using (GpuMat gpuModelImage = new GpuMat(modelImage))
//extract features from the object image
using (GpuMat gpuModelKeyPoints = surfCuda.DetectKeyPointsRaw(gpuModelImage, null))
using (GpuMat gpuModelDescriptors = surfCuda.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
using (CudaBruteForceMatcher matcher = new CudaBruteForceMatcher(DistanceType.L2))
{
surfCuda.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
watch = Stopwatch.StartNew();
// extract features from the observed image
using (GpuMat gpuObservedImage = new GpuMat(observedImage))
using (GpuMat gpuObservedKeyPoints = surfCuda.DetectKeyPointsRaw(gpuObservedImage, null))
using (GpuMat gpuObservedDescriptors = surfCuda.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
//using (GpuMat tmp = new GpuMat())
//using (Stream stream = new Stream())
{
matcher.KnnMatch(gpuObservedDescriptors, gpuModelDescriptors, matches, k);
surfCuda.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);
mask = new Matrix <byte>(matches.Size, 1);
mask.SetValue(255);
Features2DToolbox.VoteForUniqueness(matches, uniquenessThreshold, mask);
int nonZeroCount = CvInvoke.CountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints,
matches, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints,
observedKeyPoints, matches, mask, 2);
}
}
}
watch.Stop();
}
}
else
#endif
{
using (UMat uModelImage = modelImage.Mat.ToUMat(AccessType.Read))
using (UMat uObservedImage = observedImage.Mat.ToUMat(AccessType.Read))
{
SURFDetector surfCPU = new SURFDetector(hessianThresh);
//extract features from the object image
UMat modelDescriptors = new UMat();
surfCPU.DetectAndCompute(uModelImage, null, modelKeyPoints, modelDescriptors, false);
watch = Stopwatch.StartNew();
// extract features from the observed image
UMat observedDescriptors = new UMat();
surfCPU.DetectAndCompute(uObservedImage, null, observedKeyPoints, observedDescriptors, false);
BruteForceMatcher matcher = new BruteForceMatcher(DistanceType.L2);
matcher.Add(modelDescriptors);
matcher.KnnMatch(observedDescriptors, matches, k, null);
mask = new Matrix <byte>(matches.Size, 1);
mask.SetValue(255);
Features2DToolbox.VoteForUniqueness(matches, uniquenessThreshold, mask);
int nonZeroCount = CvInvoke.CountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints,
matches, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints,
observedKeyPoints, matches, mask, 2);
}
}
watch.Stop();
}
}
matchTime = watch.ElapsedMilliseconds;
}
