private async Task LoadProfiles()
{
var topFileName = CurrentMVProfile.Id == "default" ? "TopCameraVision.json" : $"Top.{CurrentMVProfile.Id}.mv.json";
var bottomFileName = CurrentMVProfile.Id == "default" ? "BottomCameraVision.json" : $"Bottom.{CurrentMVProfile.Id}.mv.json";
_topCameraProfile = await Storage.GetAsync <Models.VisionProfile>(topFileName);
_bottomCameraProfile = await Storage.GetAsync <Models.VisionProfile>(bottomFileName);
if (_topCameraProfile == null)
{
_topCameraProfile = await Storage.GetAsync <Models.VisionProfile>("TopCameraVision.json");
if (_topCameraProfile == null)
{
_topCameraProfile = new VisionProfile();
}
}
if (_bottomCameraProfile == null)
{
_bottomCameraProfile = await Storage.GetAsync <Models.VisionProfile>("BottomCameraVision.json");
if (_bottomCameraProfile == null)
{
_bottomCameraProfile = new VisionProfile();
}
}
SaveProfile();
if (ShowTopCamera)
{
Profile = _topCameraProfile;
}
if (ShowBottomCamera)
{
Profile = _bottomCameraProfile;
}
}
public void CornerDetection(VisionProfile profile, Mat img)
{
var output = new Mat();
var outputNormalized = new Mat();
var outputNormalizedScaled = new Mat();
CvInvoke.CornerHarris(img, output, profile.HarrisCornerBlockSize, profile.HarrisCornerAperture, profile.HarrisCornerK, BorderType.Default);
CvInvoke.Normalize(output, outputNormalized, 0, 255, NormType.MinMax, DepthType.Cv32F, null);
CvInvoke.ConvertScaleAbs(outputNormalized, outputNormalizedScaled, 5, 5);
for (int j = 0; j < outputNormalized.Rows; j++)
{
for (int i = 0; i < outputNormalized.Cols; i++)
{
// if ((int)outputNormalized.GetData(j,i) > profile.HarrisCornerThreshold)
{
// circle(outputNormalizedScaled, Point(i, j), 5, Scalar(0), 2, 8, 0);
}
}
}
}
public Result PerformShapeDetection(VisionProfile profile, Mat img)
{
using (var gray = new Image <Gray, byte>(img.Bitmap))
using (var blurredGray = new Mat())
using (var finalOutput = new Mat())
{
//K Must always be odd.
CvInvoke.GaussianBlur(gray, blurredGray, System.Drawing.Size.Empty, profile.GaussianSigmaX);
//Convert the image to grayscale and filter out the noise
//UMat uimage = new UMat();
//CvInvoke.CvtColor(img, uimage, ColorConversion.Bgr2Gray);
//use image pyr to remove noise
UMat pyrDown = new UMat();
CvInvoke.PyrDown(img, pyrDown);
CvInvoke.PyrUp(pyrDown, img);
//Image<Gray, Byte> gray = img.Convert<Gray, Byte>().PyrDown().PyrUp();
var circles = CvInvoke.HoughCircles(img, HoughType.Gradient, profile.HoughCirclesDP, profile.HoughCirclesMinDistance, profile.HoughCirclesParam1, profile.HoughCirclesParam2, profile.HoughCirclesMinRadius, profile.HoughCirclesMaxRadius);
UMat cannyEdges = new UMat();
CvInvoke.Canny(img, cannyEdges, profile.CannyLowThreshold, profile.CannyHighThreshold, profile.CannyApetureSize, profile.CannyGradient);
var lines = CvInvoke.HoughLinesP(cannyEdges, profile.HoughLinesRHO, profile.HoughLinesTheta, profile.HoughLinesThreshold, profile.HoughLinesMinLineLength, profile.HoughLinesMaxLineGap);
List <Triangle2DF> triangleList = new List <Triangle2DF>();
List <RotatedRect> boxList = new List <RotatedRect>(); //a box is a rotated rectangle
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
CvInvoke.FindContours(cannyEdges, contours, null, RetrType.List, ChainApproxMethod.ChainApproxSimple);
int count = contours.Size;
for (int i = 0; i < count; i++)
{
using (VectorOfPoint contour = contours[i])
using (VectorOfPoint approxContour = new VectorOfPoint())
{
CvInvoke.ApproxPolyDP(contour, approxContour, CvInvoke.ArcLength(contour, true) * 0.05, true);
if (CvInvoke.ContourArea(approxContour, false) > 250) //only consider contours with area greater than 250
{
if (approxContour.Size == 3) //The contour has 3 vertices, it is a triangle
{
var pts = approxContour.ToArray();
triangleList.Add(new Triangle2DF(
pts[0],
pts[1],
pts[2]
));
}
else if (approxContour.Size == 4) //The contour has 4 vertices.
{
#region determine if all the angles in the contour are within [80, 100] degree
bool isRectangle = true;
var pts = approxContour.ToArray();
LineSegment2D[] edges = PointCollection.PolyLine(pts, true);
for (int j = 0; j < edges.Length; j++)
{
double angle = Math.Abs(
edges[(j + 1) % edges.Length].GetExteriorAngleDegree(edges[j]));
if (angle < 80 || angle > 100)
{
isRectangle = false;
break;
}
}
#endregion
if (isRectangle)
{
boxList.Add(CvInvoke.MinAreaRect(approxContour));
}
}
}
}
}
}
var results = new Result();
results.Triangles = triangleList;
results.Rects = boxList;
results.Circles = circles.ToList();
results.Lines = lines.ToList();
return(results);
}
}