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;
}
internal static extern IntPtr cveCudaORBCreate(
int numberOfFeatures,
float scaleFactor,
int nLevels,
int edgeThreshold,
int firstLevel,
int WTA_K,
ORBDetector.ScoreType scoreType,
int patchSize,
int fastThreshold,
[MarshalAs(CvInvoke.BoolMarshalType)]
bool blurForDescriptor,
ref IntPtr feature2D,
ref IntPtr feature2DAsync);
/// <summary>
/// Create a ORBDetector using the specific values
/// </summary>
/// <param name="numberOfFeatures">The number of desired features.</param>
/// <param name="scaleFactor">Coefficient by which we divide the dimensions from one scale pyramid level to the next.</param>
/// <param name="nLevels">The number of levels in the scale pyramid.</param>
/// <param name="firstLevel">The level at which the image is given. If 1, that means we will also look at the image.<paramref name="scaleFactor"/> times bigger</param>
/// <param name="edgeThreshold">How far from the boundary the points should be.</param>
/// <param name="WTK_A">How many random points are used to produce each cell of the descriptor (2, 3, 4 ...).</param>
/// <param name="scoreType">Type of the score to use.</param>
/// <param name="patchSize">Patch size.</param>
/// <param name="blurForDescriptor">Blur for descriptor</param>
/// <param name="fastThreshold">Fast threshold</param>
public CudaORBDetector(
int numberOfFeatures = 500,
float scaleFactor = 1.2f,
int nLevels = 8,
int edgeThreshold = 31,
int firstLevel = 0,
int WTK_A = 2,
ORBDetector.ScoreType scoreType = ORBDetector.ScoreType.Harris,
int patchSize = 31,
int fastThreshold = 20,
bool blurForDescriptor = false)
{
_ptr = CudaInvoke.cveCudaORBCreate(
numberOfFeatures, scaleFactor, nLevels, edgeThreshold, firstLevel, WTK_A, scoreType, patchSize, fastThreshold, blurForDescriptor,
ref _feature2D, ref _feature2DAsyncPtr);
}
static void Main(string[] args)
{
var image = new Image <Bgr, byte>("RGB.jpg").Resize(0.4, Inter.Area);
var image_gray = image.Convert <Gray, byte>();
//CvInvoke.CvtColor(image, image_gray, ColorConversion.Bgr2Gray);
var orbDetector = new Emgu.CV.Features2D.ORBDetector(200, 1.1f, 2, 31, 0, 2, Emgu.CV.Features2D.ORBDetector.ScoreType.Harris, 31);
//var keyPoints = new VectorOfKeyPoint();
var descriptors = new UMat();
//fastDetector.DetectAndCompute(image_gray, null, keyPoints, descriptors, false);
//Features2DToolbox.DrawKeypoints(image, keyPoints, image, new Bgr(255, 255, 0), Features2DToolbox.KeypointDrawType.DrawRichKeypoints);
var keyPoints = orbDetector.Detect(image_gray);
foreach (var point in keyPoints)
{
CvInvoke.Circle(image, new Point((int)point.Point.X, (int)point.Point.Y), 1, new MCvScalar(0, 0, 255, 255), 2);
}
CvInvoke.Imshow("result", image);
CvInvoke.WaitKey();
}
public void TestORB()
{
ORBDetector orb = new ORBDetector(700);
//String[] parameters = orb.GetParamNames();
EmguAssert.IsTrue(TestFeature2DTracker(orb, orb), "Unable to find homography matrix");
}
