private static void drawHsv(Mat flow, out Mat bgr)
{
Mat[] xy = new Mat[2];
Cv2.Split(flow, out xy);
Mat magnitude = new Mat();
Mat angle = new Mat();
Cv2.CartToPolar(xy[0], xy[1], magnitude, angle, true);
//translate magnitude to range [0;1]
double mag_max, mag_min;
Cv2.MinMaxLoc(magnitude, out mag_min, out mag_max);
magnitude.ConvertTo(
magnitude, // output matrix
-1, // type of the ouput matrix, if negative same type as input matrix
1.0 / mag_max // scaling factor
);
//build hsv image
Mat[] _hsv = new Mat[3];
Mat hsv = new Mat();
bgr = new Mat();
_hsv[0] = angle;
_hsv[1] = magnitude;
_hsv[2] = Mat.Ones(angle.Size(), MatType.CV_32F);
Cv2.Merge(_hsv, hsv);
Cv2.CvtColor(hsv, bgr, ColorConversionCodes.HSV2BGR);
}
/// <summary>
/// Create a template
/// </summary>
private void TrainTemplate()
{
try
{
results.Clear();
using (Mat src = new Mat())
using (Mat output = new Mat())
using (Mat gx = new Mat())
using (Mat gy = new Mat())
using (Mat magnitude = new Mat())
using (Mat direction = new Mat())
{
/// convert to gray image
Cv2.CvtColor(template, src, ColorConversionCodes.RGB2GRAY);
/// using the canny algorithm to get edges
Cv2.Canny(src, output, TrainParame.Threshold1, TrainParame.Threshold2, TrainParame.ApertureSize, TrainParame.L2gradient);
Cv2.FindContours(output, out var contours, out var hierarchy, TrainParame.Mode, TrainParame.Method);
/// use the sobel filter on the template image which returns the gradients in the X (Gx) and Y (Gy) direction.
Cv2.Sobel(src, gx, MatType.CV_64F, 1, 0, 3);
Cv2.Sobel(src, gy, MatType.CV_64F, 0, 1, 3);
/// compute the magnitude and direction(radians)
Cv2.CartToPolar(gx, gy, magnitude, direction);
/// save edge info
var sum = new Point2d(0, 0);
for (int i = 0, m = contours.Length; i < m; i++)
{
for (int j = 0, n = contours[i].Length; j < n; j++)
{
var cur = contours[i][j];
var fdx = gx.At <double>(cur.Y, cur.X, 0); // dx
var fdy = gy.At <double>(cur.Y, cur.X, 0); // dy
var der = new Point2d(fdx, fdy); // (dx,dy)
var mag = magnitude.At <double>(cur.Y, cur.X, 0); // √(dx²+dy²)
var dir = direction.At <double>(cur.Y, cur.X, 0); // atan2(dy,dx)
results.Add(new PointInfo
{
Point = cur,
Derivative = der,
Direction = dir,
Magnitude = mag == 0 ? 0 : 1 / mag,
});
sum += cur;
}
}
/// update Center and Offset in PointInfo
var center = new Point2d(sum.X / results.Count, sum.Y / results.Count);
foreach (var item in results)
{
item.Update(center);
}
/// overlay display origin image, edge(green) and center point(red)
Cv2.DrawContours(template, new[] { results.Select(_ => _.Point) }, -1, Scalar.LightGreen, 2);
//Cv2.DrawContours(template, contours, -1, Scalar.LightGreen, 2);
Cv2.Circle(template, center.ToPoint(), 2, Scalar.Red, -1);
}
/// update UI
RaisePropertyChanged(nameof(Template));
}
catch (Exception ex)
{
Trace.TraceError(ex.Message);
Trace.TraceError(ex.StackTrace);
}
}
/// <summary>
/// NCC to find template
/// </summary>
private void MatchSearch()
{
Stopwatch stopwatch = new Stopwatch();
try
{
Trace.TraceInformation("NCC matching start");
stopwatch.Start();
/// convert to gray image
using (Mat src = new Mat())
using (Mat gx = new Mat())
using (Mat gy = new Mat())
using (Mat direction = new Mat())
using (Mat magnitude = new Mat())
{
Cv2.CvtColor(destination, src, ColorConversionCodes.RGB2GRAY);
/// use the sobel filter on the source image which returns the gradients in the X (Gx) and Y (Gy) direction.
Cv2.Sobel(src, gx, MatType.CV_64F, 1, 0, 3);
Cv2.Sobel(src, gy, MatType.CV_64F, 0, 1, 3);
/// compute the magnitude and direction
Cv2.CartToPolar(gx, gy, magnitude, direction);
var minScore = SearchParame.MinScore;
var greediness = SearchParame.Greediness;
/// ncc match search
long noOfCordinates = results.Count;
double normMinScore = minScore / noOfCordinates; // normalized min score
double normGreediness = (1 - greediness * minScore) / (1 - greediness) / noOfCordinates;
double partialScore = 0;
double resultScore = 0;
Point center = new Point();
for (int i = 0, h = src.Height; i < h; i++)
{
for (int j = 0, w = src.Width; j < w; j++)
{
double partialSum = 0;
for (var m = 0; m < noOfCordinates; m++)
{
var item = results[m];
var curX = (int)(j + item.Offset.X);
var curY = (int)(i + item.Offset.Y);
var iTx = item.Derivative.X;
var iTy = item.Derivative.Y;
if (curX < 0 || curY < 0 || curY > src.Height - 1 || curX > src.Width - 1)
{
continue;
}
var iSx = gx.At <double>(curY, curX, 0);
var iSy = gy.At <double>(curY, curX, 0);
if ((iSx != 0 || iSy != 0) && (iTx != 0 || iTy != 0))
{
var mag = magnitude.At <double>(curY, curX, 0);
var matGradMag = mag == 0 ? 0 : 1 / mag; // 1/√(dx²+dy²)
partialSum += ((iSx * iTx) + (iSy * iTy)) * (item.Magnitude * matGradMag);
}
var sumOfCoords = m + 1;
partialScore = partialSum / sumOfCoords;
/// check termination criteria
/// if partial score score is less than the score than needed to make the required score at that position
/// break serching at that coordinate.
if (partialScore < Math.Min((minScore - 1) + normGreediness * sumOfCoords, normMinScore * sumOfCoords))
{
break;
}
}
if (partialScore > resultScore)
{
resultScore = partialScore;
center.X = j;
center.Y = i;
}
}
}
/// overlay display origin image, edge(green) and center point(red)
Cv2.DrawContours(destination, new[] { results.Select(_ => _.Offset.ToPoint()) }, -1, Scalar.LightGreen, 2, offset: center);
Cv2.Circle(destination, center, 5, Scalar.Red, -1);
Trace.TraceInformation($"NCC matching score {resultScore}. time: {stopwatch.Elapsed.TotalMilliseconds} ms");
}
RaisePropertyChanged(nameof(Destination));
}
catch (Exception ex)
{
Trace.TraceError(ex.Message);
Trace.TraceError(ex.StackTrace);
}
finally
{
stopwatch.Stop();
}
}
private void Cardboardize(ref Mat src, ref Mat dst)
{
// Calculate Center Point of input image
int n = src.Cols;
int c = n / 2;
// create a cartesian coordinate mesh of pixels.
// generates 2 matrices xi and yi, each of size n*n
Mat xi = new Mat(n, n, MatType.CV_32FC1);
Mat yi = new Mat(n, n, MatType.CV_32FC1);
meshgrid(ref xi, ref yi);
// normalizing indices between -n and n
Mat xt = xi - c;
Mat yt = yi - c;
// Transposing
xt = xt.T();
yt = yt.T();
if (!xt.IsContinuous())
{
xt = xt.Clone();
}
if (!yt.IsContinuous())
{
yt = yt.Clone();
}
xt = xt.Reshape(0, xt.Rows * xt.Cols);
yt = yt.Reshape(0, yt.Rows * yt.Cols);
Mat r = new Mat();
Mat theta = new Mat();
Cv2.CartToPolar(xt, yt, r, theta);
//Cv2.CreateSuperResolution_BTVL1();
Mat s = r + 0.00001f * r.Mul(r.Mul(r));
Mat ut = new Mat();
Mat vt = new Mat();
Cv2.PolarToCart(s, theta, ut, vt);
Mat u = new Mat();
Mat v = new Mat();
if (!ut.IsContinuous())
{
ut = ut.Clone();
}
if (!vt.IsContinuous())
{
vt = vt.Clone();
}
u = ut.Reshape(0, n) + c;
v = vt.Reshape(0, n) + c;
u = u.T();
v = v.T();
Mat dist = new Mat();
Cv2.Remap(src, dist, u, v, InterpolationFlags.Linear, BorderTypes.Constant);
string devicenames = "";
for (int i = 0; i < WebCamTexture.devices.Length; ++i)
{
//if (!WebCamTexture.devices[i].isFrontFacing)
//{
// devicenames = devicenames + WebCamTexture.devices[i].name;
// devicenames = devicenames + " , ";
//}
devicenames = devicenames + WebCamTexture.devices[i].name;
devicenames = devicenames + " , ";
}
Scalar color = new Scalar(0, 0, 255);
Point p = new Point(50, c);
Debug.Log("Number of Cameras Found: " + WebCamTexture.devices.Length);
//Cv2.PutText(dist, devicenames, p, HersheyFonts.HersheyPlain, 1, color, 2);
Cv2.HConcat(dist, dist, dst);
}
