private void Btn_findCorner_Click(object sender, EventArgs e)
{
var bitmap = this.picSrc.GetFirstRegionRect();
var image = new Image <Bgr, byte>(bitmap);
//Mat mat_threshold = new Mat();
//int myThreshold = 200;
//CvInvoke.Threshold(image, mat_threshold, myThreshold, 255, Emgu.CV.CvEnum.ThresholdType.BinaryInv);
//new CommonUse().SaveMat(mat_threshold, "角检测的二值化前期");
//LineSegment2D
BriefDescriptorExtractor extractor = new BriefDescriptorExtractor();
FastDetector detector = new FastDetector((int)this.numericUpDown1.Value);
var points = detector.Detect(image);
//detector.
//CvInvoke.DrawChessboardCorners(image, new Size(1, 1), points, true);
for (int i = 0; i < points.Length; i++)
{
//if (points[i].Angle < 60)
//{
// continue;
//}
var tmpPoint = new Point((int)points[i].Point.X, (int)points[i].Point.Y);
CvInvoke.Circle(image, tmpPoint, 1, new MCvScalar(0, 0, 255));
}
this.picTarget.LoadImage(image.ToBitmap());
}
public MKeyPoint[] DetectKeyPoints(IInputArray image)
{
MKeyPoint[] result;
result = _fast.Detect(image);
return(result);
}
private void opticalFlow()
{
var a = new MCvTermCriteria(100);
byte[] status2;
float[] errors2;
PointF[] corners2;
var vectors2 = vector2Point(vectors);
var keypoints = fastDetector.Detect(inputGrayImage, null);
var corners = new VectorOfKeyPoint(keypoints);
corners2 = vector2Point(corners);
CvInvoke.CalcOpticalFlowPyrLK(inputGrayImagePrevious, inputGrayImage, vectors2, new Size(10, 10), 3, a, out corners2, out status2, out errors2);
var matches = countNonZero(status2);
labelStatus.Text = "Found =" + Convert.ToString(matches);
labelTotal.Text = "Total =" + Convert.ToString(errors2.Count());
}
static void Main(string[] args)
{
VectorOfKeyPoint modelKeyPoints, observedKeyPoints = new VectorOfKeyPoint();
Mat img0 = new Mat(@"D:\Desktop\SI4\testImg0.jpg");
Mat img1 = new Mat(@"D:\Desktop\SI4\testImg1.jpg");
VectorOfVectorOfDMatch vectorOfDMatch = new VectorOfVectorOfDMatch();
FastDetector fd = new FastDetector();
MKeyPoint[] points0 = fd.Detect(img0);
MKeyPoint[] points1 = fd.Detect(img1);
Console.WriteLine(points0.Length);
Console.WriteLine(points1.Length);
MKeyPoint[] points2 = fd.Detect(img1, img0);
Console.WriteLine(points2.Length);
SIFT sift = new SIFT();
GpuMat outputArray = new GpuMat();
sift.DetectAndCompute(img0, img1, new VectorOfKeyPoint(points2), outputArray, false);
}
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 fastDetector = new FastDetector(80);
//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 = fastDetector.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();
}
