private extern static void CvLDetectorDetectKeyPoints(
ref LDetector detector,
IntPtr image,
IntPtr keypoints,
int maxCount,
[MarshalAs(UnmanagedType.I1)]
bool scaleCoords);
internal extern static void CvPlanarObjectDetectorTrain(
IntPtr objectDetector,
IntPtr image,
int npoints,
int patchSize,
int nstructs,
int structSize,
int nviews,
ref LDetector keyPointDetector,
ref PatchGenerator patchGenerator);
/// <summary>
/// Train the planar object detector using the specific image
/// </summary>
/// <param name="image">The training image</param>
/// <param name="npoints">Use 300 for default</param>
/// <param name="patchSize">Use 31 for default</param>
/// <param name="nstructs">Use 50 for default</param>
/// <param name="structSize">Use 9 for default</param>
/// <param name="nviews">Use 5000 for default</param>
/// <param name="keyPointDetector">The keypoint detector to be used</param>
/// <param name="patchGenerator">The patch generator to be used</param>
public void Train(Image<Gray, byte> image,
int npoints,
int patchSize,
int nstructs,
int structSize,
int nviews,
ref LDetector keyPointDetector,
ref PatchGenerator patchGenerator)
{
CvPlanarObjectDetectorTrain(Ptr, image, npoints, patchSize, nstructs, structSize, nviews, ref keyPointDetector, ref patchGenerator);
}
/// <summary>
/// Train the planar object detector using the specific image
/// </summary>
/// <param name="image">The training image</param>
/// <param name="npoints">Use 300 for default</param>
/// <param name="patchSize">Use 31 for default</param>
/// <param name="nstructs">Use 50 for default</param>
/// <param name="structSize">Use 9 for default</param>
/// <param name="nviews">Use 5000 for default</param>
/// <param name="keyPointDetector">The keypoint detector to be used</param>
/// <param name="patchGenerator">The patch generator to be used</param>
public void Train(Image <Gray, byte> image,
int npoints,
int patchSize,
int nstructs,
int structSize,
int nviews,
ref LDetector keyPointDetector,
ref PatchGenerator patchGenerator)
{
CvPlanarObjectDetectorTrain(Ptr, image, npoints, patchSize, nstructs, structSize, nviews, ref keyPointDetector, ref patchGenerator);
}
private static extern void CvLDetectorDetectKeyPoints(
ref LDetector detector,
IntPtr image,
IntPtr keypoints,
int maxCount,
[MarshalAs(UnmanagedType.I1)]
bool scaleCoords);
private static extern void CvPlanarObjectDetectorTrain(
IntPtr objectDetector,
IntPtr image,
int npoints,
int patchSize,
int nstructs,
int structSize,
int nviews,
ref LDetector keyPointDetector,
ref PatchGenerator patchGenerator);
public void TestPlanarObjectDetector()
{
Image<Gray, byte> box = new Image<Gray, byte>("box.png");
Image<Gray, byte> scene = new Image<Gray,byte>("box_in_scene.png");
//Image<Gray, Byte> scene = box.Rotate(1, new Gray(), false);
using (PlanarObjectDetector detector = new PlanarObjectDetector())
{
Stopwatch watch = Stopwatch.StartNew();
LDetector keypointDetector = new LDetector();
keypointDetector.SetDefaultParameters();
PatchGenerator pGen = new PatchGenerator();
pGen.SetDefaultParameters();
detector.Train(box, 300, 31, 50, 9, 5000, ref keypointDetector, ref pGen);
watch.Stop();
Trace.WriteLine(String.Format("Training time: {0} milliseconds.", watch.ElapsedMilliseconds));
MKeyPoint[] modelPoints = detector.GetModelPoints();
int i = modelPoints.Length;
HomographyMatrix h = new HomographyMatrix();
watch = Stopwatch.StartNew();
PointF[] corners = detector.Detect(scene, h);
watch.Stop();
Trace.WriteLine(String.Format("Detection time: {0} milliseconds.", watch.ElapsedMilliseconds));
foreach (PointF c in corners)
{
scene.Draw(new CircleF(c, 2), new Gray(255), 1);
}
scene.DrawPolyline(Array.ConvertAll<PointF, Point>(corners, Point.Round), true, new Gray(255), 2);
}
}
public void TestLDetectorAndSelfSimDescriptor()
{
Image<Gray, byte> box = new Image<Gray, byte>("box.png");
LDetector detector = new LDetector();
detector.SetDefaultParameters();
MKeyPoint[] keypoints = detector.DetectKeyPoints(box, 200, true);
Point[] pts = Array.ConvertAll<MKeyPoint, Point>(keypoints, delegate(MKeyPoint k) { return Point.Round(k.Point); });
SelfSimDescriptor descriptor = new SelfSimDescriptor(5, 41, 3, 7, 20);
int descriptorSize = descriptor.DescriptorSize;
float[] descriptors = descriptor.Compute(box, new Size(20, 20), pts);
float absSum = 0;
foreach (float f in descriptors)
absSum += Math.Abs(f);
//TODO: Find out why selfsimilarity always return descriptors of all zeros. Probaboly a bug in the opencv C++ code
//Assert.AreNotEqual(0, absSum, "The sum of the descriptor should not be zero");
Assert.AreEqual(descriptors.Length / descriptor.DescriptorSize, pts.Length);
foreach (MKeyPoint kp in keypoints)
{
box.Draw(new CircleF(kp.Point, kp.Size), new Gray(255), 1);
}
}