public Image <Bgr, byte> GetPalm(Mat mask)
{
int width = mask.Width;
int height = mask.Height;
var temp = new Mat();
var result = mask.ToImage <Bgr, byte>();
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
VectorOfPoint biggestContour = new VectorOfPoint();
CvInvoke.FindContours(mask, contours, null, RetrType.List, ChainApproxMethod.ChainApproxSimple);
if (contours.Size > 0)
{
biggestContour = contours[0];
for (int i = 0; i < contours.Size; i++)
{
if (contours[i].Size > biggestContour.Size)
{
biggestContour = contours[i];
}
}
}
if (biggestContour.Size != 0)
{
//Gaunam rankos konturus
CvInvoke.ApproxPolyDP(biggestContour, biggestContour, 0.00000001, false);
var points = biggestContour.ToArray();
VectorOfInt hull = new VectorOfInt();
//find the palm hand area using convexitydefect
CvInvoke.ConvexHull(biggestContour, hull, true);
var box = CvInvoke.MinAreaRect(biggestContour);
Mat defects = new Mat();
CvInvoke.ConvexityDefects(biggestContour, hull, defects);
if (!defects.IsEmpty)
{
//Data from Mat are not directly readable so we convert it to Matrix<>
Matrix <int> m = new Matrix <int>(defects.Rows, defects.Cols, defects.NumberOfChannels);
defects.CopyTo(m);
for (int i = 0; i < m.Rows; i++)
{
int startIdx = m.Data[i, 0];
int endIdx = m.Data[i, 1];
Point startPoint = points[startIdx];
Point endPoint = points[endIdx];
//draw a line connecting the convexity defect start point and end point in thin red line
CvInvoke.Line(result, startPoint, endPoint, new MCvScalar(0, 0, 255));
}
}
}
return(result);
}
Image <Bgr, byte> ProcessFrame(Mat colorPicture, MCvScalar skinHsv)
{//, Mat binPicture) {
Mat picture = colorPicture.Clone();
picture = BackgroundSubtraction(picture, skinHsv);
//picture = binPicture;
//return new Image<Bgr, byte>(picture.Bitmap);
//contour stuff
VectorOfVectorOfPoint contoursss = new VectorOfVectorOfPoint();
CvInvoke.FindContours(picture, contoursss, null, RetrType.List, ChainApproxMethod.ChainApproxNone);
VectorOfPoint handContour = FindLargestContour(contoursss);
if ((handContour == null || CvInvoke.ContourArea(handContour) < 100 || CvInvoke.ContourArea(handContour) > 200000))
{
return(new Image <Bgr, byte>(colorPicture.Bitmap));
}
VectorOfVectorOfPoint hulls = new VectorOfVectorOfPoint(1);
//VectorOfVectorOfPoint hullDefects = new VectorOfVectorOfPoint(1);
VectorOfInt hullI = new VectorOfInt();
CvInvoke.ConvexHull(handContour, hullI, false, false);
CvInvoke.ConvexHull(handContour, hulls[0], false, true);
//convexity defects
Mat defects = new Mat();
CvInvoke.ConvexityDefects(handContour, hullI, defects);
try
{
Matrix <int> m = new Matrix <int>(defects.Rows, defects.Cols, defects.NumberOfChannels); // copy Mat to a matrix...
defects.CopyTo(m);
CvInvoke.DrawContours(colorPicture, hulls, -1, new MCvScalar(0, 0, 255), 1);
Image <Bgr, byte> image = new Image <Bgr, byte>(colorPicture.Bitmap);
return(DrawPoints(image, m, handContour));
}
catch (Exception)
{
return(new Image <Bgr, byte>(colorPicture.Bitmap));
}
//CvInvoke.Imshow("picture", colorPicture);
//CvInvoke.WaitKey(); // Render image and keep window opened until any key is pressed
}
/// Calculate convex hull and convexity defects for accurate finger calculation
private Matrix <int> CalculateConvexityDefects(Image <Gray, Byte> img, VectorOfPoint biggestContour, VectorOfVectorOfPoint contours)
{
VectorOfPoint currentContour = new VectorOfPoint();
VectorOfInt hullIndices = new VectorOfInt();
CvInvoke.ApproxPolyDP(biggestContour, currentContour, CvInvoke.ArcLength(biggestContour, true) * .005, true);
biggestContour = currentContour;
CvInvoke.ConvexHull(biggestContour, hullIndices, false, false);
/// Calcualate convexity defects
/// Defects is a 4-element integer vector
/// (start_index, end_index, farthest_pt_index, fixpt_depth)
/// stored in a matrix where each row is a defect
Matrix <int> defects = null;
Mat mat = new Mat();
CvInvoke.ConvexityDefects(biggestContour, hullIndices, mat);
if (mat.Rows > 0)
{
defects = new Matrix <int>(mat.Rows, mat.Cols, mat.NumberOfChannels);
mat.CopyTo(defects);
/// For debugging and training purposes
/// Draws finger points using convexity defects
Matrix <int>[] channels = defects.Split();
/// channel[0] = start_point, channel[1] = end_point, channel[2] = fixpt_depth
for (int j = 0; j < defects.Rows; ++j)
{
if (j < 5)
{
CvInvoke.Circle(img, System.Drawing.Point.Round(new System.Drawing.PointF(biggestContour[channels[0][j, 0]].X, biggestContour[channels[0][j, 0]].Y)), 10, new MCvScalar(255, 255, 255), 10);
}
}
}
/// For debugging and training purposes
/// Draws convex hull of biggest contour
VectorOfPoint hullPoints = new VectorOfPoint();
CvInvoke.ConvexHull(biggestContour, hullPoints, false);
CvInvoke.Polylines(img, hullPoints.ToArray(), true, new MCvScalar(255, 255, 255), 10);
return(defects);
}
private void ExtractContourAndHull(Image <Gray, byte> skin) // kiem vien va lop ngoai
{
using (MemStorage storage = new MemStorage())
{
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
CvInvoke.FindContours(skin, contours, new Mat(), Emgu.CV.CvEnum.RetrType.External, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);
VectorOfPoint biggestContour = new VectorOfPoint(); // mang point[] chua vien` lon nhat
Double Result1 = 0; // area dang xet
Result = 0;
for (int i = 0; i < contours.Size; i++)
{
VectorOfPoint contour = contours[i]; // chuyen sang Point[][]
double area = CvInvoke.ContourArea(contour, false); // tinh area
Result1 = area;
if (Result1 > Result)
{
Result = Result1;
biggestContour = contour;
}
}
label8.Text = "Size Rect :" + Result.ToString();
if (biggestContour != null)
{
CvInvoke.ApproxPolyDP(biggestContour, biggestContour, 0.00025, false);
points = biggestContour.ToArray();
currentFrame.Draw(points, new Bgr(255, 0, 255), 4);
VectorOfPoint hull = new VectorOfPoint();
VectorOfInt convexHull = new VectorOfInt();
CvInvoke.ConvexHull(biggestContour, hull, false); //~ Hull
box = CvInvoke.MinAreaRect(hull);
currentFrame.Draw(new CircleF(box.Center, 5), new Bgr(Color.Black), 4);
CvInvoke.ConvexHull(biggestContour, convexHull);
//PointF[] Vertices = box.GetVertices();
// handRect = box.MinAreaRect();
currentFrame.Draw(box, new Bgr(200, 0, 0), 1);
// ve khung ban tay khung bao quanh tay
currentFrame.DrawPolyline(hull.ToArray(), true, new Bgr(200, 125, 75), 4);
currentFrame.Draw(new CircleF(new PointF(box.Center.X, box.Center.Y), 3), new Bgr(200, 125, 75));
// tim convex defect
CvInvoke.ConvexityDefects(biggestContour, convexHull, defect);
// chuyen sang Matrix
if (!defect.IsEmpty)
{
mDefect = new Matrix <int>(defect.Rows, defect.Cols, defect.NumberOfChannels);
defect.CopyTo(mDefect);
}
}
}
}
/// <summary>
/// Count number of fingers on skinMask and draw debug information
/// </summary>
/// <param name="skinMask">Skin mask to count fingers on</param>
/// <returns>Mat with detection debug information</returns>
public Mat FindFingersCount(Mat skinMask)
{
Mat contoursImage = Mat.Ones(skinMask.Height, skinMask.Width, DepthType.Cv8U, 3);
if (skinMask.IsEmpty || skinMask.NumberOfChannels != 1)
{
return(contoursImage);
}
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
Mat hierarchy = new Mat();
CvInvoke.FindContours(skinMask, contours, hierarchy, RetrType.External, ChainApproxMethod.ChainApproxNone);
if (contours.Size <= 0)
{
return(contoursImage);
}
int biggestContourIndex = -1;
double biggestArea = 0;
for (int i = 0; i < contours.Size; i++)
{
double area = CvInvoke.ContourArea(contours[i], false);
if (area > biggestArea)
{
biggestArea = area;
biggestContourIndex = i;
}
}
if (biggestContourIndex < 0)
{
return(contoursImage);
}
VectorOfPoint hullPoints = new VectorOfPoint();
VectorOfInt hullInts = new VectorOfInt();
CvInvoke.ConvexHull(contours[biggestContourIndex], hullPoints, true);
CvInvoke.ConvexHull(contours[biggestContourIndex], hullInts, false);
Mat defects = new Mat();
if (hullInts.Size > 3)
{
CvInvoke.ConvexityDefects(contours[biggestContourIndex], hullInts, defects);
}
else
{
return(contoursImage);
}
Rectangle boundingRectangle = CvInvoke.BoundingRectangle(hullPoints);
Point centerBoundingRectangle = new Point((boundingRectangle.X + boundingRectangle.Right) / 2, (boundingRectangle.Y + boundingRectangle.Bottom) / 2);
VectorOfPoint startPoints = new VectorOfPoint();
VectorOfPoint farPoints = new VectorOfPoint();
int[,,] defectsData = (int[, , ])defects.GetData();
for (int i = 0; i < defectsData.Length / 4; i++)
{
Point startPoint = contours[biggestContourIndex][defectsData[i, 0, 0]];
if (!startPoints.ToArray().ToList().Any(p => Math.Abs(p.X - startPoint.X) < 30 && Math.Abs(p.Y - startPoint.Y) < 30))
{
VectorOfPoint startPointVector = new VectorOfPoint(new Point[] { startPoint });
startPoints.Push(startPointVector);
}
Point farPoint = contours[biggestContourIndex][defectsData[i, 0, 2]];
if (findPointsDistance(farPoint, centerBoundingRectangle) < boundingRectangle.Height * BOUNDING_RECT_FINGER_SIZE_SCALING)
{
VectorOfPoint farPointVector = new VectorOfPoint(new Point[] { farPoint });
farPoints.Push(farPointVector);
}
}
VectorOfPoint filteredStartPoints = CompactOnNeighborhoodMedian(startPoints, boundingRectangle.Height * BOUNDING_RECT_NEIGHBOR_DISTANCE_SCALING);
VectorOfPoint filteredFarPoints = CompactOnNeighborhoodMedian(farPoints, boundingRectangle.Height * BOUNDING_RECT_NEIGHBOR_DISTANCE_SCALING);
VectorOfPoint filteredFingerPoints = new VectorOfPoint();
if (filteredFarPoints.Size > 1)
{
VectorOfPoint fingerPoints = new VectorOfPoint();
for (int i = 0; i < filteredStartPoints.Size; i++)
{
VectorOfPoint closestPoints = findClosestOnX(filteredFarPoints, filteredStartPoints[i]);
if (isFinger(closestPoints[0], filteredStartPoints[i], closestPoints[1], LIMIT_ANGLE_INF, LIMIT_ANGLE_SUP, centerBoundingRectangle, boundingRectangle.Height * BOUNDING_RECT_FINGER_SIZE_SCALING))
{
fingerPoints.Push(new Point[] { filteredStartPoints[i] });
}
}
if (fingerPoints.Size > 0)
{
while (fingerPoints.Size > 5)
{
//Remove extra fingers
//Convert to list and remove last item
List <Point> points = new List <Point>(fingerPoints.ToArray());
points.Remove(points.Last());
fingerPoints = new VectorOfPoint(points.ToArray());
}
for (int i = 0; i < fingerPoints.Size - 1; i++)
{
}
filteredFingerPoints = fingerPoints;
this.NumberOfFingersRaised = filteredFingerPoints.Size;
}
}
Bgr colorRed = new Bgr(Color.Red);
Bgr colorGreen = new Bgr(Color.Green);
Bgr colorBlue = new Bgr(Color.Blue);
Bgr colorYellow = new Bgr(Color.Yellow);
Bgr colorPurple = new Bgr(Color.Purple);
Bgr colorWhite = new Bgr(Color.White);
//Debug, draw defects
defectsData = (int[, , ])defects.GetData();
for (int i = 0; i < defectsData.Length / 4; i++)
{
Point start = contours[biggestContourIndex][defectsData[i, 0, 0]];
Point far = contours[biggestContourIndex][defectsData[i, 0, 2]];
Point end = contours[biggestContourIndex][defectsData[i, 0, 1]];
CvInvoke.Polylines(contoursImage, new Point[] { start, far, end }, true, colorPurple.MCvScalar, DRAW_THICKNESS / 2);
CvInvoke.Circle(contoursImage, start, 5, colorWhite.MCvScalar);
CvInvoke.Circle(contoursImage, far, 5, colorRed.MCvScalar, 10);
CvInvoke.Circle(contoursImage, end, 5, colorBlue.MCvScalar);
}
//Draw information about what was detected (Contours, key points, fingers / how many fingers)
CvInvoke.DrawContours(contoursImage, contours, 0, colorGreen.MCvScalar, DRAW_THICKNESS, LineType.AntiAlias);
CvInvoke.Polylines(contoursImage, hullPoints, true, colorBlue.MCvScalar, DRAW_THICKNESS);
CvInvoke.Rectangle(contoursImage, boundingRectangle, colorRed.MCvScalar, DRAW_THICKNESS);
CvInvoke.Circle(contoursImage, centerBoundingRectangle, 5, colorYellow.MCvScalar, DRAW_THICKNESS);
drawVectorPoints(contoursImage, filteredStartPoints, colorRed.MCvScalar, true, 3);
drawVectorPoints(contoursImage, filteredFarPoints, colorWhite.MCvScalar, true, 3);
drawVectorPoints(contoursImage, filteredFingerPoints, colorYellow.MCvScalar, false, 3);
CvInvoke.PutText(contoursImage, filteredFingerPoints.Size.ToString(), centerBoundingRectangle, FontFace.HersheyComplex, 2, colorYellow.MCvScalar);
return(contoursImage);
}
private void ProcessFrame(object sender, EventArgs args)
{
//Get frame
Mat frame = camera.QueryFrame();
//Process frame
Image <Bgr, Byte> img = frame.ToImage <Bgr, Byte>();
img.ROI = new Rectangle(100, 100, 300, 300);
Image <Hsv, Byte> HSVimg = img.Convert <Hsv, Byte>();
Image <Gray, Byte> binary = HSVimg.InRange(new Hsv(minH, minS, minV), new Hsv(maxH, maxS, maxV));
Image <Gray, Byte> eroded = binary.Erode(erosions);
Image <Gray, Byte> dilated = eroded.Dilate(dilations);
//Detect largest blob
CvBlobDetector blobDetector = new CvBlobDetector();
CvBlobs blobs = new CvBlobs();
blobDetector.Detect(dilated, blobs);
int maxBlobArea = 0;
CvBlob largestBlob = null;
foreach (CvBlob blob in blobs.Values)
{
if (blob.Area > maxBlobArea)
{
maxBlobArea = blob.Area;
largestBlob = blob;
}
}
if (largestBlob != null && largestBlob.Area >= 10000)
{
handContour = largestBlob.GetContour();
VectorOfInt convexHullIndices = new VectorOfInt();
VectorOfPoint convexHull = new VectorOfPoint();
CvInvoke.ConvexHull(new VectorOfPoint(handContour), convexHull);
CvInvoke.ConvexHull(new VectorOfPoint(handContour), convexHullIndices);
Mat defects = new Mat();
//img.Draw(handContour, new Bgr(0, 0, 255),3);
img.Draw(convexHull.ToArray(), new Bgr(255, 0, 0), 3);
try
{
CvInvoke.ConvexityDefects(new VectorOfPoint(handContour), convexHullIndices, defects);
}
catch (CvException exc)
{
MessageBox.Show(exc.Message);
}
if (!defects.IsEmpty)
{
Matrix <int> defectsInt = new Matrix <int>(defects.Rows, defects.Cols, defects.NumberOfChannels);
defects.CopyTo(defectsInt);
int countFingers = 0;
for (int i = 0; i < defectsInt.Rows; i++)
{
int startIdx = defectsInt.Data[i, 0];
int endIdx = defectsInt.Data[i, 1];
int farthestIdx = defectsInt.Data[i, 2];
float distance = defectsInt.Data[i, 3];
if (distance >= 15000)
{
//distances.Add(distance);
Point startPoint = handContour[startIdx];
Point endPoint = handContour[endIdx];
Point farthestPoint = handContour[farthestIdx];
img.Draw(new CircleF(startPoint, 2.0f), new Bgr(0, 255, 0), 2);
img.Draw(new CircleF(endPoint, 2.0f), new Bgr(255, 0, 0), 2);
img.Draw(new CircleF(farthestPoint, 2.0f), new Bgr(0, 0, 255), 2);
CvInvoke.Line(img, startPoint, farthestPoint, new MCvScalar(255, 255, 0));
countFingers++;
}
}
//Approssimo conteggio dita, e classifico : 1 dito = play, 5 dita = pausa
if (Math.Abs(countFingers - 1) < Math.Abs(countFingers - 5)
&&
Math.Abs(countFingers - 1) < Math.Abs(countFingers - 2))
{
label10.Text = "Play";
axWindowsMediaPlayer1.Ctlcontrols.play();
}
else if (Math.Abs(countFingers - 5) < Math.Abs(countFingers - 1)
&&
Math.Abs(countFingers - 5) < Math.Abs(countFingers - 2))
{
label10.Text = "Pause";
axWindowsMediaPlayer1.Ctlcontrols.pause();
}
else if (Math.Abs(countFingers - 2) < Math.Abs(countFingers - 1)
&&
Math.Abs(countFingers - 2) < Math.Abs(countFingers - 5))
{
label10.Text = "Volume Up";
axWindowsMediaPlayer1.Ctlcontrols.pause();
axWindowsMediaPlayer1.settings.volume++;
}
}
}
pictureBox1.Image = binary.Bitmap;
}
private Rectangle LocateROI()
{
int prediction = -1;
VectorOfPoint contourOfInterest = new VectorOfPoint();
int index = 0;
index = ImgProc.LargestContourIndex(_contour);
contourOfInterest = _contour[index];
MCvMoments moment = CvInvoke.Moments(contourOfInterest);
double[] huMoment = moment.GetHuMoment();
prediction = _svm.Compute(huMoment);
//foreach (VectorOfPoint vp in _listOfContours.GetRange(0, 5))
//{
// MCvMoments moment = CvInvoke.Moments(vp);
// double[] huMoment = moment.GetHuMoment();
// prediction = _svm.Compute(huMoment);
// if (prediction == CLASSIFICATION_ARM || prediction == CLASSIFICATION_HAND)
// {
// contourOfInterest = vp;
// break;
// }
//}
if (prediction == CLASSIFICATION_REJECT)
{
return(Rectangle.Empty);
}
else if (prediction == CLASSIFICATION_HAND)
{
//Rectangle rectRotRect = rectRot.MinAreaRect();
//Rectangle init = CvInvoke.MinAreaRect(contoursEval1[largestContourIndexEval1]).MinAreaRect();
//Point final = new Point(rectRotRect.X + init.X, rectRotRect.Y + init.Y);
//return new Rectangle(final, init.Size);
return(CvInvoke.MinAreaRect(contourOfInterest).MinAreaRect());
}
else if (prediction == CLASSIFICATION_ARM)
{
Mat convexityDefect = new Mat();
VectorOfInt hull = new VectorOfInt();
CvInvoke.ConvexHull(contourOfInterest, hull, false, false);
CvInvoke.ConvexityDefects(contourOfInterest, hull, convexityDefect);
RotatedRect rectRot = CvInvoke.MinAreaRect(contourOfInterest);
ModifiedRotatedRect rotRectMod = new ModifiedRotatedRect(rectRot);
int yDel = 0;
double ptLftToRight = Geometry.Distance(rotRectMod.Pul, rotRectMod.Pur);
double ptUpToDown = Geometry.Distance(rotRectMod.Pul, rotRectMod.Pll);
if (!convexityDefect.IsEmpty)
{
Matrix <int> convex = new Matrix <int>(convexityDefect.Rows, convexityDefect.Cols, convexityDefect.NumberOfChannels);
convexityDefect.CopyTo(convex);
List <Point> contourTmp = new List <Point>();
for (int i = 0; i < contourOfInterest.Size; i++)
{
contourTmp.Add(contourOfInterest[i]);
}
List <ConvexDefects> convexDefectList = new List <ConvexDefects>();
for (int i = 0; i < convex.Rows; i++)
{
// do not touch
int startIdx = convex.Data[i, 0];
int endIdx = convex.Data[i, 1];
int pointIdx = convex.Data[i, 2];
Point startPt = contourOfInterest[startIdx];
Point endPt = contourOfInterest[endIdx];
Point defectPt = contourOfInterest[pointIdx];
// do not touch
convexDefectList.Add(new ConvexDefects(startPt, endPt, defectPt));
}
if (ptLftToRight <= ptUpToDown)
{
Point pc1Tmp = convexDefectList[0].DefectPt;
Point pc2Tmp = convexDefectList[1].DefectPt;
Point pc = pc1Tmp.Y > pc2Tmp.Y ? pc1Tmp : pc2Tmp;
Point ptUpLeft = rotRectMod.Pul;
Point ptUpRight = rotRectMod.Pur;
Point ptLowLeft = rotRectMod.Pll;
Point ptLowRight = rotRectMod.Plr;
ModifiedRotatedRect rotRectEval1 = ModifiedRotatedRect.Cut(ptUpLeft, ptUpRight, ptLowLeft, ptLowRight, pc);
ModifiedRotatedRect rotRectEval2 = ModifiedRotatedRect.Cut(ptUpLeft, ptUpRight, ptLowLeft, ptLowRight, pc, true);
Size sizeFrame = ImageInput.Size;
Rectangle rectROIEval1 = rotRectEval1.ToRect(sizeFrame);
Rectangle rectROIEval2 = rotRectEval2.ToRect(sizeFrame);
Mat cloneMat1 = ImageInput.Clone().Mat;
Mat matToBeEval1 = new Mat(cloneMat1, rectROIEval1);
VectorOfVectorOfPoint contoursEval1 = new VectorOfVectorOfPoint();
Mat matHierachyEval1 = new Mat();
CvInvoke.FindContours(matToBeEval1, contoursEval1, matHierachyEval1, Emgu.CV.CvEnum.RetrType.External,
Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxTc89L1);
int largestContourIndexEval1 = ImgProc.LargestContourIndex(contoursEval1);
MCvMoments momentEval1 = CvInvoke.Moments(contoursEval1[largestContourIndexEval1]);
double[] huMomentsEval1 = momentEval1.GetHuMoment();
double[] featureVectorSearch = ScaleValues(huMomentsEval1, 5000.0);
int predictionEval1 = _svm.Compute(featureVectorSearch, MulticlassComputeMethod.Elimination);
//double[] featureVectorHand = ScaleValues(huMomentsEval1.
// .GetRange(0, _svmMachineHand.Inputs).ToArray(), 1000.0);
if (predictionEval1 == CLASSIFICATION_HAND)
{
Rectangle rectRotRect = rectRot.MinAreaRect();
Rectangle init = CvInvoke.MinAreaRect(contoursEval1[largestContourIndexEval1]).MinAreaRect();
Point final = new Point(rectRotRect.X + init.X, rectRotRect.Y + init.Y);
return(new Rectangle(final, init.Size));
}
else
{
return(Rectangle.Empty);
}
}
else
{
return(Rectangle.Empty);
}
}
else
{
return(Rectangle.Empty);
}
}
else
{
return(Rectangle.Empty);
}
}
void timer_Tick(object sender, EventArgs e)
{
sw.Start();
currentFrame = capture.QueryFrame().ToImage<Hsv, byte>();
currentFrame = currentFrame.AbsDiff(backgroundFrame);
smoothedFrame = currentFrame.PyrDown().PyrUp();
smoothedFrame._SmoothGaussian(3);
filteredFrame = smoothedFrame.InRange(new Hsv(hueLower, saturationLower, valueLower), new Hsv(hueHigher, saturationHigher, valueHigher));
outFrame = filteredFrame;//.Canny((cannyThresh), (cannyThreshLink));
CvInvoke.FindContours(outFrame, contours, hierarchy, Emgu.CV.CvEnum.RetrType.List, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);
for (int i = 0; i < contours.Size; i++)
{
double area = CvInvoke.ContourArea(contours[i], false);
if (area > maxArea)
{
maxArea = area;
idx = i;
}
}
image.SetValue(new MCvScalar(180, 0, 255));
CvInvoke.DrawContours(image, contours, idx, new MCvScalar(255, 255, 255), 3);
ContourArea.Text = maxArea.ToString();
if (maxArea != 0)
{
CvInvoke.ConvexHull(contours[idx], cvh, false);
CvInvoke.ConvexityDefects(contours[idx], cvh, cvd);
moments = CvInvoke.Moments(contours[idx], true);
centroid = new System.Drawing.Point((int) moments.GravityCenter.X, (int) moments.GravityCenter.Y);
CvInvoke.Circle(image, centroid, 5, new MCvScalar(100,50,25), 1);
if (contours.Size != 0)
{
polyline = contours[idx].ToArray();
if (!cvd.IsEmpty && contours[idx].Size > 10)
{
Matrix<int> m = new Matrix<int>(cvd.Rows, cvd.Cols,
cvd.NumberOfChannels);
cvd.CopyTo(m);
for (int i = 0; i < m.Rows; i++)
{
int startIdx = m.Data[i, 0];
int endIdx = m.Data[i, 1];
int fpIdx = m.Data[i, 2];
int depth = m.Data[i, 3];
startPoint = polyline[startIdx];
endPoint = polyline[endIdx];
midPoint = new System.Drawing.Point(
(startPoint.X + endPoint.X) / 2, (startPoint.Y + endPoint.Y) / 2);
farthestPoint = polyline[fpIdx];
CvInvoke.Line(image, midPoint, farthestPoint, new MCvScalar(180, 255, 0));
CvInvoke.Line(image, startPoint, endPoint, new MCvScalar(180, 255, 255));
}
}
if(trained.Size!=0)
{
double match=1000000;
int d = 0;
for (int i = 0; i < trained.Size; i++)
{
double curr = CvInvoke.MatchShapes(contours[idx], trained[i], ContoursMatchType.I3);
if(curr < match)
{
d = i;
match = curr;
}
}
if(match<0.25)
{
ContourArea.Text = words[d];
image.Draw(words[d], centroid, FontFace.HersheyTriplex, 1, new Hsv(90,100, 100));
}
}
}
}
if (currentFrame != null)
{
sw.Stop();
imgPros.Source = ToBitmapSource(outFrame);
imgOrig.Source = ToBitmapSource(currentFrame);
imgSmooth.Source = ToBitmapSource(image);
sw.Reset();
}
maxArea = 0;
idx = 0;
}
void ProcessFramAndUpdateGUI(object Sender, EventArgs agr)
{
int Finger_num = 0;
Double Result1 = 0;
Double Result2 = 0;
//querying image
currentFrame = capture.QueryFrame().ToImage <Bgr, byte>();
int widthROI = currentFrame.Size.Width / 4;
int heightROI = currentFrame.Size.Height / 4;
// currentFrame = currentFrame.Copy(new Rectangle(widthROI, heightROI, widthROI * 2, heightROI * 2));
if (currentFrame == null)
{
return;
}
//Cach 1***************************
//Applying YCrCb filter
//Image<Ycc, Byte> currentYCrCbFrame = currentFrame.Convert<Ycc, byte>();
//Image<Gray, byte> skin = new Image<Gray, byte>(currentFrame.Width, currentFrame.Height);
//skin = currentYCrCbFrame.InRange(new Ycc(0, minCr, minCb), new Ycc(255, maxCr, maxCb));
////Erode
//Mat rect_12 = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(10, 10), new Point(5, 5));
//CvInvoke.Erode(skin, skin, rect_12, new Point(-1, -1), 1, BorderType.Default, new MCvScalar());
////Dilate
//Mat rect_6 = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(6, 6), new Point(3, 3));
//CvInvoke.Dilate(skin, skin, rect_6, new Point(-1, -1), 1, BorderType.Default, new MCvScalar());
//**********************************
//Cach 2**************************** Phong
IColorSkinDetector skinDetector = new YCrCbSkinDetector();
Image <Gray, byte> skin = skinDetector.DetectSkin(currentFrame, new Ycc(0, minCr, minCb), new Ycc(255, maxCr, maxCb));
//**********************************
skin = skin.Flip(FlipType.Horizontal);
//smoothing the filterd , eroded and dilated image.
skin = skin.SmoothGaussian(9);
picSkinCam.Image = skin.ToBitmap();
currentFrame = currentFrame.Flip(FlipType.Horizontal);
#region Extract contours and hull
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
CvInvoke.FindContours(skin, contours, new Mat(), Emgu.CV.CvEnum.RetrType.External,
Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);
VectorOfPoint biggestContour = new VectorOfPoint();// mang point[] chua vien` lon nhat
//Tim area contours lon nhat
for (int i = 0; i < contours.Size; i++)
{
VectorOfPoint contour = contours[i]; // chuyen sang Point[][]
Result1 = CvInvoke.ContourArea(contour, false); // tinh area
if (Result1 > Result2)
{
Result2 = Result1;
biggestContour = contour;
}
}
//Gi do
try
{
lblNote.Text = "";
if (biggestContour != null)
{
CvInvoke.ApproxPolyDP(biggestContour, biggestContour, 0.00025, false);
contourPoints = biggestContour.ToArray();
currentFrame.Draw(contourPoints, new Bgr(255, 0, 255), 4);
VectorOfPoint hull = new VectorOfPoint();
VectorOfInt convexHull = new VectorOfInt();
CvInvoke.ConvexHull(biggestContour, hull, true); //~ Hull //Chinh clockwise thanh true
RotatedRect minAreaBox = CvInvoke.MinAreaRect(hull);
currentFrame.Draw(new CircleF(minAreaBox.Center, 5), new Bgr(Color.Black), 4);
CvInvoke.ConvexHull(biggestContour, convexHull, true); //Chinh clockwise thanh true
currentFrame.Draw(minAreaBox, new Bgr(200, 0, 0), 1);
// ve khung ban tay khung bao quanh tay
currentFrame.DrawPolyline(hull.ToArray(), true, new Bgr(200, 125, 75), 4);
currentFrame.Draw(new CircleF(new PointF(minAreaBox.Center.X, minAreaBox.Center.Y), 3), new Bgr(200, 125, 75));
// tim convex defect
Mat defect = new Mat();
CvInvoke.ConvexityDefects(biggestContour, convexHull, defect);
// chuyen sang Matrix
if (!defect.IsEmpty)
{
mDefect = new Matrix <int>(defect.Rows, defect.Cols, defect.NumberOfChannels);
defect.CopyTo(mDefect);
}
#region Counting finger
if (mDefect.Rows == 0)
{
return;
}
PointF[] start = new PointF[mDefect.Rows];
int num = 0;
start[0] = new PointF(0, 0);
try
{
for (int i = 0; i < mDefect.Rows; i++)
{
int startIdx = mDefect.Data[i, 0];
int depthIdx = mDefect.Data[i, 1];
int endIdx = mDefect.Data[i, 2];
Point startPoint = contourPoints[startIdx];
Point endPoint = contourPoints[endIdx];
Point depthPoint = contourPoints[depthIdx];
CircleF startCircle = new CircleF(startPoint, 5f);
CircleF endCircle = new CircleF(endPoint, 5f);
CircleF depthCircle = new CircleF(depthPoint, 5f);
LineSegment2D Line = new LineSegment2D(startPoint, new Point((int)minAreaBox.Center.X, (int)minAreaBox.Center.Y));
//Cach 1
//if ((startCircle.Center.Y < minAreaBox.Center.Y || depthCircle.Center.Y < minAreaBox.Center.Y) &&
// (startCircle.Center.Y < depthCircle.Center.Y) &&
// (Math.Sqrt(Math.Pow(startCircle.Center.X - depthCircle.Center.X, 2) +
// Math.Pow(startCircle.Center.Y - depthCircle.Center.Y, 2)) >
// minAreaBox.Size.Height / 6.5))
//{
// Finger_num++;
//}
//Cach 2
if ((startPoint.Y < minAreaBox.Center.Y && endPoint.Y < minAreaBox.Center.Y) && (startPoint.Y < endPoint.Y) &&
(Math.Sqrt(Math.Pow(startPoint.X - endPoint.X, 2) + Math.Pow(startPoint.Y - endPoint.Y, 2)) > minAreaBox.Size.Height / 7))
{
if (getAngle(startPoint, minAreaBox.Center, start[num]) > 10)
{
Finger_num++;
start[num] = startPoint;
num++;
currentFrame.Draw(Line, new Bgr(Color.Violet), 2);
currentFrame.Draw(startCircle, new Bgr(Color.OrangeRed), 5);
//currentFrame.Draw(endCircle, new Bgr(Color.Black), 5);
//currentFrame.Draw(Finger_num.ToString(), new Point(startPoint.X - 10, startPoint.Y), FontFace.HersheyPlain, 2, new Bgr(Color.Orange), 3);
//currentFrame.Draw(Finger_num.ToString(), new Point(endPoint.X - 10, endPoint.Y), FontFace.HersheyPlain, 2, new Bgr(Color.Orange), 3);
}
}
}
}
catch
{
return;
}
#endregion
}
#region Tracking
MCvMoments moment = new MCvMoments(); // a new MCvMoments object
try
{
moment = CvInvoke.Moments(biggestContour, false); // Moments of biggestContour
}
catch (NullReferenceException except)
{
//label3.Text = except.Message;
return;
}
//CvInvoke.cvMoments(biggestContour, ref moment, 0);
double m_00 = CvInvoke.cvGetSpatialMoment(ref moment, 0, 0);
double m_10 = CvInvoke.cvGetSpatialMoment(ref moment, 1, 0);
double m_01 = CvInvoke.cvGetSpatialMoment(ref moment, 0, 1);
int current_X = Convert.ToInt32(m_10 / m_00) / 10; // X location of centre of contour
int current_Y = Convert.ToInt32(m_01 / m_00) / 10; // Y location of center of contour
#endregion
if (useVirtualMouse)
{
// move cursor to center of contour only if Finger count is 1 or 0
// i.e. palm is closed
if (Finger_num == 0 || Finger_num == 1)
{
Cursor.Position = new Point(current_X * 20, current_Y * 20);
}
// Leave the cursor where it was and Do mouse click, if finger count >= 4
if (Finger_num >= 3)
{
if (!isDrag)
{
DoMouseDown();
isDrag = true;
}
else
{
DoMouseUp();
isDrag = false;
}
//Cursor.Position = new Point(current_X * 20, current_Y * 20);
//Cursor.Position = new Point(300, 300);
}
}
}
catch
{
Finger_num = 0;
lblNote.Text = "Opps! Make sure to have a 'white space'";
return;
}
#endregion
//Display image from camera
picInputCam.Image = currentFrame.ToBitmap();
lblNumFinger.Text = Finger_num.ToString();
}
private Mat DetectObject(Mat detectionFrame, Mat displayFrame)
{
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
detectGesture = false;
VectorOfPoint biggestContour = null;
IOutputArray hirarchy = null;
// Crear lista de contornos
CvInvoke.FindContours(detectionFrame, contours, hirarchy, RetrType.List, ChainApproxMethod.ChainApproxSimple);
// Selecciona el contour mas grande
if (contours.Size > 0)
{
double maxArea = 0;
int chosen = 0;
VectorOfPoint contour = null;
for (int i = 0; i < contours.Size; i++)
{
contour = contours[i];
double area = CvInvoke.ContourArea(contour);
if (area > maxArea)
{
maxArea = area;
chosen = i;
}
}
// Dibuja un frame
MarkDetectedObject(displayFrame, contours[chosen], maxArea);
VectorOfPoint hullPoints = new VectorOfPoint();
VectorOfInt hullInt = new VectorOfInt();
CvInvoke.ConvexHull(contours[chosen], hullPoints, true);
CvInvoke.ConvexHull(contours[chosen], hullInt, false);
Mat defects = new Mat();
if (hullInt.Size > 3)
{
detectGesture = true;
}
CvInvoke.ConvexityDefects(contours[chosen], hullInt, defects);
Rectangle box = CvInvoke.BoundingRectangle(hullPoints);
CvInvoke.Rectangle(displayFrame, box, drawingColor);
Point center = new Point(box.X + box.Width / 2, box.Y + box.Height / 2);
VectorOfPoint start_points = new VectorOfPoint();
VectorOfPoint far_points = new VectorOfPoint();
if (!defects.IsEmpty)
{
//Los datos del Mat no se pueden leer directamente, por lo que los convertimos a Matrix<>
Matrix <int> m = new Matrix <int>(defects.Rows, defects.Cols,
defects.NumberOfChannels);
defects.CopyTo(m);
gestualNum = 0;
int x = int.MaxValue, y = int.MaxValue;
for (int i = 0; i < m.Rows; i++)
{
int startIdx = m.Data[i, 0];
int endIdx = m.Data[i, 1];
int farIdx = m.Data[i, 2];
Point startPoint = contours[chosen][startIdx];
Point endPoint = contours[chosen][endIdx];
Point farPoint = contours[chosen][farIdx];
CvInvoke.Circle(displayFrame, endPoint, 3, new MCvScalar(0, 255, 255));
CvInvoke.Circle(displayFrame, startPoint, 3, new MCvScalar(255, 255, 0));
//if (true)
//{
if (endPoint.Y < y)
{
x = endPoint.X;
y = endPoint.Y;
}
//}
double distance = Math.Round(Math.Sqrt(Math.Pow((center.X - farPoint.X), 2) + Math.Pow((center.Y - farPoint.Y), 2)), 1);
if (distance < box.Height * 0.3)
{
CvInvoke.Circle(displayFrame, farPoint, 10, new MCvScalar(255, 0, 0), 4);
gestualNum++;
}
//dibuja una línea que conecta el punto de inicio del defecto de convexidad y el punto final en una línea roja
CvInvoke.Line(displayFrame, startPoint, endPoint, new MCvScalar(0, 255, 255));
}
if (gestualNum >= 4)
{
//Console.WriteLine("numero gestual 4");
gestualNumRepite++;
}
else
{
gestualNumRepite = 0;
}
if (gestualNumRepite == 3)
{
Console.WriteLine("numero gestual 5 Click");
gestualNumRepite = 0;
if (detectClick == true)
{
detectClick = false;
}
else
{
detectClick = true;
}
}
Console.WriteLine("numero gestual " + gestualNum);
//var info = new string[] { $"Puntero", $"Posicion: {x}, {y}" };
//WriteMultilineText(displayFrame, info, new Point(x + 30, y));
centerSensor.X = x;
centerSensor.Y = y;
CvInvoke.Circle(displayFrame, new Point(x, y), 20, new MCvScalar(255, 0, 255), 2);
//CvInvoke.Circle(picture, new Point(x * 2, y * 4), 20, new MCvScalar(255, 0, 255), 2);
return(displayFrame);
}
// detectGesture = false;
// return displayFrame;
}
return(displayFrame);
}
}
private void ImageRecognition_Click(object sender, RoutedEventArgs e)
{
try
{
Image <Gray, byte> OutputImage = InputImage.Convert <Gray, byte>().ThresholdBinary(new Gray(100), new Gray(255));
int i;
//Применение фильтрации при необходимости
if (FilterBox.IsChecked == true)
{
CvInvoke.Erode(OutputImage, OutputImage, new Mat(), new System.Drawing.Point(-1, -1), 5, Emgu.CV.CvEnum.BorderType.Default, new MCvScalar());
CvInvoke.Dilate(OutputImage, OutputImage, new Mat(), new System.Drawing.Point(-1, -1), 5, Emgu.CV.CvEnum.BorderType.Default, new MCvScalar());
}
//Поиск контура
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
Mat hierarchy = new Mat();
CvInvoke.FindContours(OutputImage,
contours,
hierarchy,
Emgu.CV.CvEnum.RetrType.Tree,
Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);
//ResultImage для фильтров
Image <Bgr, byte> ResultImage = OutputImage.Convert <Bgr, byte>();
//Отрисовка контура
CvInvoke.DrawContours(ResultImage, contours, -1, new MCvScalar(255, 10, 10), 3);
//Опорные точки
VectorOfPoint contour = new VectorOfPoint();
VectorOfInt hull = new VectorOfInt();
contour = contours[0];
CvInvoke.ConvexHull(contour, hull, false, false);
//Дефекты выпуклости
Mat convexityDefects = new Mat();
CvInvoke.ConvexityDefects(contour, hull, convexityDefects);
//Преобразование в матрицу для удобства
Matrix <int> matrixOfDefects = new Matrix <int>(convexityDefects.Rows, convexityDefects.Cols, convexityDefects.NumberOfChannels);
convexityDefects.CopyTo(matrixOfDefects);
Matrix <int>[] channels = matrixOfDefects.Split();
CircleF circle = CvInvoke.MinEnclosingCircle(contour);
//
List <System.Drawing.PointF> PointsMemory = new List <System.Drawing.PointF>();
//Для поиска центра
RotatedRect minAreaRect = CvInvoke.MinAreaRect(contour);
//Отбор точек
for (i = 0; i < matrixOfDefects.Rows; ++i)
{
if (PropertyBox.IsChecked == true)
{
#region Через Описывающий прямоугольник
//C - Center S - Start[0] E - End[1] D - Depth[2]
//Start - Center
float LengthXSC = contour[channels[0][i, 0]].X - minAreaRect.Center.X;
float LengthYSC = contour[channels[0][i, 0]].Y - minAreaRect.Center.Y;
float LengthSC = (float)Math.Sqrt(Math.Pow(LengthXSC, 2) + Math.Pow(LengthYSC, 2));
//Расстояние от начальной точки до дефекта
float LengthXSD = contour[channels[0][i, 0]].X - contour[channels[2][i, 0]].X;
float LengthYSD = contour[channels[0][i, 0]].Y - contour[channels[2][i, 0]].X;
float LengthSD = (float)Math.Sqrt(Math.Pow(LengthXSD, 2) + Math.Pow(LengthYSD, 2));
//Расстояние от начала до конца вектора
float LengthXSE = contour[channels[0][i, 0]].X - contour[channels[1][i, 0]].X;
float LengthYSE = contour[channels[0][i, 0]].Y - contour[channels[1][i, 0]].X;
float LengthSE = (float)Math.Sqrt(Math.Pow(LengthXSE, 2) + Math.Pow(LengthYSE, 2));
//Расстояние от дефекта до центра
float LengthXDC = contour[channels[2][i, 0]].X - minAreaRect.Center.X;
float LengthYDC = contour[channels[2][i, 0]].Y - minAreaRect.Center.Y;
float LengthDC = (float)Math.Sqrt(Math.Pow(LengthXDC, 2) + Math.Pow(LengthYDC, 2));
//Расстояние от центра до грани под 90
float MinRadius = minAreaRect.Size.Width / 2;
//Отбор точек по условиям
if (LengthSC >= MinRadius * 0.85 &&
(LengthSE <= MinRadius || LengthSE >= MinRadius * 0.95) &&
(LengthSD > MinRadius * 0.3 && LengthDC <= MinRadius * 0.9))
{
PointsMemory.Add(new System.Drawing.PointF(contour[channels[0][i, 0]].X, contour[channels[0][i, 0]].Y));
ResultImage.Draw(new System.Drawing.Point[] { contour[channels[0][i, 0]], contour[channels[2][i, 0]] }, new Bgr(0, 255, 0), 2);
}
ResultImage.Draw(new RotatedRect(minAreaRect.Center, minAreaRect.Size, minAreaRect.Angle), new Bgr(125, 125, 125), 2);
#endregion
}
else
{
#region Через описывающую окружность
//C - Center S - Start[0] E - End[1] D - Depth[2]
//Start - Center
float LengthXSC = contour[channels[0][i, 0]].X - circle.Center.X;
float LengthYSC = contour[channels[0][i, 0]].Y - circle.Center.Y;
float LengthSC = (float)Math.Sqrt(Math.Pow(LengthXSC, 2) + Math.Pow(LengthYSC, 2));
//Расстояние от начальной точки до дефекта
float LengthXSD = contour[channels[0][i, 0]].X - contour[channels[2][i, 0]].X;
float LengthYSD = contour[channels[0][i, 0]].Y - contour[channels[2][i, 0]].X;
float LengthSD = (float)Math.Sqrt(Math.Pow(LengthXSD, 2) + Math.Pow(LengthYSD, 2));
//Расстояние от начала до конца вектора
float LengthXSE = contour[channels[0][i, 0]].X - contour[channels[1][i, 0]].X;
float LengthYSE = contour[channels[0][i, 0]].Y - contour[channels[1][i, 0]].X;
float LengthSE = (float)Math.Sqrt(Math.Pow(LengthXSE, 2) + Math.Pow(LengthYSE, 2));
//Расстояние от дефекта до центра
float LengthXDC = contour[channels[2][i, 0]].X - circle.Center.X;
float LengthYDC = contour[channels[2][i, 0]].Y - circle.Center.Y;
float LengthDC = (float)Math.Sqrt(Math.Pow(LengthXDC, 2) + Math.Pow(LengthYDC, 2));
//Отбор точек по условиям
if (LengthSC >= circle.Radius * 0.5 &&
(LengthSE <= circle.Radius * 0.8 || LengthSE >= circle.Radius) &&
(LengthDC <= LengthSD * 0.9 || LengthSD > circle.Radius * 0.4))
{
ResultImage.Draw(new System.Drawing.Point[] { contour[channels[0][i, 0]], contour[channels[2][i, 0]] }, new Bgr(0, 255, 0), 2);
PointsMemory.Add(new System.Drawing.PointF(contour[channels[0][i, 0]].X, contour[channels[0][i, 0]].Y));
}
ResultImage.Draw(new CircleF(circle.Center, circle.Radius), new Bgr(0, 255, 255), 2);
#endregion
}
}
foreach (System.Drawing.PointF pt in PointsMemory)
{
ResultImage.Draw(new CircleF(pt, 3), new Bgr(0, 0, 255), 3);
}
OutputImageBox.Source = BitmapSourceConvert.ToBitmapSource(ResultImage);
}
catch (Exception ex)
{
MessageBox.Show(ex.Message, "Ошибка", MessageBoxButton.OK, MessageBoxImage.Error);
}
}
private Mat DetectObject(Mat detectionFrame, Mat displayFrame, Rectangle box)
{
Image <Bgr, Byte> buffer_im = displayFrame.ToImage <Bgr, Byte>();
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
IOutputArray hirarchy = null;
// Construir lista de contur (contornos)
CvInvoke.FindContours(detectionFrame, contours, hirarchy, RetrType.List, ChainApproxMethod.ChainApproxSimple);
// seleccionar el contour (contorno) mas grande
if (contours.Size > 0)
{
double maxArea = 0;
int chosen = 0;
VectorOfPoint contour = null;
for (int i = 0; i < contours.Size; i++)
{
contour = contours[i];
double area = CvInvoke.ContourArea(contour);
if (area > maxArea)
{
maxArea = area;
chosen = i;
}
}
// Draw on a frame
//MarkDetectedObject(displayFrame, contours[chosen], maxArea);//dibuja una envoltura roja
VectorOfPoint hullPoints = new VectorOfPoint();
VectorOfInt hullInt = new VectorOfInt();
CvInvoke.ConvexHull(contours[chosen], hullPoints, true);
CvInvoke.ConvexHull(contours[chosen], hullInt, false);
Mat defects = new Mat();
if (hullInt.Size > 3)
{
CvInvoke.ConvexityDefects(contours[chosen], hullInt, defects);
}
box = CvInvoke.BoundingRectangle(hullPoints);
CvInvoke.Rectangle(displayFrame, box, drawingColor); //Box rectangulo que encierra el area mas grande
// cropbox = crop_color_frame(displayFrame, box);
buffer_im.ROI = box;
Image <Bgr, Byte> cropped_im = buffer_im.Copy();
textImage = cropped_im.Mat;
imagenFinal = cropped_im.Bitmap;
//imagenFinal.RotateFlip(RotateFlipType.Rotate180FlipNone);
//if (imagenFinal != null)
//{
// try
// {
// var assembly = Assembly.GetExecutingAssembly();
// var folder = Path.GetDirectoryName(assembly.Location);
// imagenFinal.Save(folder + "/texto.png", System.Drawing.Imaging.ImageFormat.Png);
// }
// catch (Exception)
// {
// throw;
// }
//}
return(displayFrame);
}
textImage = detectionFrame;
return(displayFrame);
}
}
private void DetectObject(Mat detectionFrame, Mat displayFrame, Rectangle box)
{
Image <Bgr, Byte> buffer_im = displayFrame.ToImage <Bgr, Byte>();
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
VectorOfPoint biggestContour = null;
IOutputArray hirarchy = null;
CvInvoke.FindContours(detectionFrame, contours, hirarchy, RetrType.List, ChainApproxMethod.ChainApproxSimple);
if (contours.Size > 0)
{
double maxArea = 0;
int chosen = 0;
VectorOfPoint contour = null;
for (int i = 0; i < contours.Size; i++)
{
contour = contours[i];
double area = CvInvoke.ContourArea(contour);
if (area > maxArea)
{
maxArea = area;
chosen = i;
}
}
//MarkDetectedObject(displayFrame, contours[chosen], maxArea);//dibuja una envoltura roja
VectorOfPoint hullPoints = new VectorOfPoint();
VectorOfInt hullInt = new VectorOfInt();
CvInvoke.ConvexHull(contours[chosen], hullPoints, true);
CvInvoke.ConvexHull(contours[chosen], hullInt, false);
Mat defects = new Mat();
if (hullInt.Size > 3)
{
CvInvoke.ConvexityDefects(contours[chosen], hullInt, defects);
}
box = CvInvoke.BoundingRectangle(hullPoints);
CvInvoke.Rectangle(displayFrame, box, drawingColor); //Box rectangulo que encierra el area mas grande
// cropbox = crop_color_frame(displayFrame, box);
buffer_im.ROI = box;
Image <Bgr, Byte> cropped_im = buffer_im.Copy();
pictureBox8.Image = cropped_im.Bitmap;
Point center = new Point(box.X + box.Width / 2, box.Y + box.Height / 2);//centro rectangulo MOUSE
VectorOfPoint start_points = new VectorOfPoint();
VectorOfPoint far_points = new VectorOfPoint();
if (!defects.IsEmpty)
{
Matrix <int> m = new Matrix <int>(defects.Rows, defects.Cols,
defects.NumberOfChannels);
defects.CopyTo(m);
int xe = 2000, ye = 2000;
int xs = 2000, ys = 2000;
int xer = 2000, yer = 2000;
int xsr = 2000, ysr = 2000;
int xem = 0, yem = 0;
int xsm = 0, ysm = 0;
int xez = 0, yez = 0;
int xsz = 0, ysz = 0;
int y = 0, x = 0;
int ym = 0, xm = 0;
int yr = 0, xr = 0;
int yz = 0, xz = 0;
for (int i = 0; i < m.Rows; i++)
{
int startIdx = m.Data[i, 0];
int endIdx = m.Data[i, 1];
int farIdx = m.Data[i, 2];
Point startPoint = contours[chosen][startIdx];
Point endPoint = contours[chosen][endIdx];
Point farPoint = contours[chosen][farIdx];
CvInvoke.Circle(displayFrame, endPoint, 3, new MCvScalar(0, 255, 255));
CvInvoke.Circle(displayFrame, startPoint, 3, new MCvScalar(255, 255, 0));
if (true)
{
if (endPoint.Y < ye)
{
xe = endPoint.X;
ye = endPoint.Y;
}
if (startPoint.Y < ys)
{
xs = startPoint.X;
ys = startPoint.Y;
}
if (ye < ys)
{
y = ye;
x = xe;
}
else
{
y = ys;
x = xs;
}
if (endPoint.Y > yem)
{
xem = endPoint.X;
yem = endPoint.Y;
}
if (startPoint.Y > ysm)
{
xsm = startPoint.X;
ysm = startPoint.Y;
}
if (yem > ysm)
{
ym = yem;
xm = xem;
}
else
{
y = ys;
x = xs;
}
if (endPoint.X < xer)
{
xer = endPoint.X;
yer = endPoint.Y;
}
if (startPoint.X < xsr)
{
xsr = startPoint.X;
ysr = startPoint.Y;
}
if (xer < xsr)
{
yr = yer;
xr = xer;
}
else
{
yr = ysr;
xr = xsr;
}
if (endPoint.X > xez)
{
xez = endPoint.X;
yez = endPoint.Y;
}
if (startPoint.X > xsz)
{
xsz = startPoint.X;
ysz = startPoint.Y;
}
if (xez > xsz)
{
yz = yez;
xz = xez;
}
else
{
yz = ysz;
xz = xsz;
}
}
/*var info = new string[] {
*
* $"Posicion: {endPoint.X}, {endPoint.Y}"
* };
*
* WriteMultilineText(displayFrame, info, new Point(endPoint.X + 5, endPoint.Y));*/
double distance = Math.Round(Math.Sqrt(Math.Pow((center.X - farPoint.X), 2) + Math.Pow((center.Y - farPoint.Y), 2)), 1);
if (distance < box.Height * 0.3)
{
CvInvoke.Circle(displayFrame, farPoint, 3, new MCvScalar(255, 0, 0));
}
CvInvoke.Line(displayFrame, startPoint, endPoint, new MCvScalar(0, 255, 0));
// CvInvoke.Line(displayFrame, startPoint, farPoint, new MCvScalar(0, 255, 255));
}
var infoe = new string[] { $"Punto", $"Posicion: {x}, {y}" };
var infos = new string[] { $"Punto", $"Posicion: {xm}, {ym}" };
var infor = new string[] { $"Punto", $"Posicion: {x}, {y}" };
var infoz = new string[] { $"Punto", $"Posicion: {xm}, {ym}" };
var infoCentro = new string[] { $"Centro", $"Posicion: {xm}, {ym}" };
var xCentro = (x + xm + xr + xz) / 4;
var yCentro = (y + ym + yr + yz) / 4;
WriteMultilineText(displayFrame, infoe, new Point(x + 30, y));
CvInvoke.Circle(displayFrame, new Point(x, y), 5, new MCvScalar(255, 0, 255), 2);
Image <Bgr, byte> temp = detectionFrame.ToImage <Bgr, byte>();
var temp2 = temp.SmoothGaussian(5).Convert <Gray, byte>().ThresholdBinary(new Gray(230), new Gray(255));
VectorOfVectorOfPoint contorno = new VectorOfVectorOfPoint();
Mat mat = new Mat();
CvInvoke.FindContours(temp2, contorno, mat, Emgu.CV.CvEnum.RetrType.External, Emgu.CV.CvEnum.ChainApproxMethod.LinkRuns);
for (int i = 0; i < contorno.Size; i++)
{
double perimetro = CvInvoke.ArcLength(contorno[i], true);
VectorOfPoint approx = new VectorOfPoint();
CvInvoke.ApproxPolyDP(contorno[i], approx, 0.04 * perimetro, true);
CvInvoke.DrawContours(displayFrame, contorno, i, new MCvScalar(0, 255, 255), 2);
}
WriteMultilineText(displayFrame, infos, new Point(xm + 30, ym));
CvInvoke.Circle(displayFrame, new Point(xm, ym), 5, new MCvScalar(255, 0, 255), 2);
WriteMultilineText(displayFrame, infor, new Point(xr + 30, yr));
CvInvoke.Circle(displayFrame, new Point(xr, yr), 5, new MCvScalar(255, 0, 255), 2);
WriteMultilineText(displayFrame, infoz, new Point(xz + 30, yz));
CvInvoke.Circle(displayFrame, new Point(xz, yz), 5, new MCvScalar(255, 0, 255), 2);
WriteMultilineText(displayFrame, infoz, new Point(xCentro + 30, yCentro));
CvInvoke.Circle(displayFrame, new Point(xCentro, yCentro), 2, new MCvScalar(0, 100, 0), 4);
//CvInvoke.Circle(picture, new Point(x * 2, y * 4), 20, new MCvScalar(255, 0, 255), 2);*/
}
}
}
}
private Mat DetectObject(Mat detectionFrame, Mat displayFrame, Rectangle box)
{
Image <Bgr, Byte> buffer_im = displayFrame.ToImage <Bgr, Byte>();
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
IOutputArray hirarchy = null;
// Construir lista de contur (contornos)
CvInvoke.FindContours(detectionFrame, contours, hirarchy, RetrType.List, ChainApproxMethod.ChainApproxSimple);
// seleccionar el contour (contorno) mas grande
if (contours.Size > 0)
{
double maxArea = 0;
int chosen = 0;
VectorOfPoint contour = null;
for (int i = 0; i < contours.Size; i++)
{
contour = contours[i];
double area = CvInvoke.ContourArea(contour);
if (area > maxArea)
{
maxArea = area;
chosen = i;
}
}
VectorOfPoint hullPoints = new VectorOfPoint();
VectorOfInt hullInt = new VectorOfInt();
CvInvoke.ConvexHull(contours[chosen], hullPoints, true);
CvInvoke.ConvexHull(contours[chosen], hullInt, false);
Mat defects = new Mat();
if (hullInt.Size > 3)
{
CvInvoke.ConvexityDefects(contours[chosen], hullInt, defects);
}
box = CvInvoke.BoundingRectangle(hullPoints);
CvInvoke.Rectangle(displayFrame, box, drawingColor); //Box rectangulo que encierra el area mas grande
center = new Point(box.X + box.Width / 2, box.Y + box.Height / 2); //centro rectangulo MOUSE
var infoCentro = new string[] { $"Centro", $"Posicion: {center.X}, {center.Y}" };
WriteMultilineText(displayFrame, infoCentro, new Point(center.X + 30, center.Y));
CvInvoke.Circle(displayFrame, new Point(center.X, center.Y), 2, new MCvScalar(0, 100, 0), 4);
detectGesture = true;
buffer_im.Dispose();
defects.Dispose();
detectionFrame.Dispose();
return(displayFrame);
}
buffer_im.Dispose();
detectionFrame.Dispose();
detectGesture = false;
return(displayFrame);
}
}
private void ExtractContourAndHull(Image <Bgr, byte> originalImage, Image <Gray, byte> skin)
{
var contours = new VectorOfVectorOfPoint();
CvInvoke.FindContours(skin, contours, new Mat(), RetrType.List, ChainApproxMethod.ChainApproxSimple);
var result2 = 0;
VectorOfPoint biggestContour = null;
if (contours.Size != 0)
{
biggestContour = contours[0];
}
for (var i = 0; i < contours.Size; i++)
{
var result1 = contours[i].Size;
if (result1 <= result2)
{
continue;
}
result2 = result1;
biggestContour = contours[i];
}
if (biggestContour == null)
{
return;
}
currentContour = new VectorOfPoint();
CvInvoke.ApproxPolyDP(biggestContour, currentContour, 0, true);
//TODO Get to know why it gives exception
//ImageFrame.Draw(biggestContour, 3, new Bgr(Color.LimeGreen));
biggestContour = currentContour;
var pointsToFs = new PointF[currentContour.Size];
for (var i = 0; i < currentContour.Size; i++)
{
pointsToFs[i] = new PointF(currentContour[i].X, currentContour[i].Y);
}
var hull = CvInvoke.ConvexHull(pointsToFs, true);
pointsToFs = new PointF[biggestContour.Size];
for (var i = 0; i < biggestContour.Size; i++)
{
pointsToFs[i] = new PointF(biggestContour[i].X, biggestContour[i].Y);
}
box = CvInvoke.MinAreaRect(pointsToFs);
var points = box.GetVertices();
var ps = new Point[points.Length];
for (var i = 0; i < points.Length; i++)
{
ps[i] = new Point((int)points[i].X, (int)points[i].Y);
}
var hullToPoints = new Point[hull.Length];
for (var i = 0; i < hull.Length; i++)
{
hullToPoints[i] = Point.Round(hull[i]);
}
originalImage.DrawPolyline(hullToPoints, true, new Bgr(200, 125, 75), 2);
originalImage.Draw(new CircleF(new PointF(box.Center.X, box.Center.Y), 3), new Bgr(200, 125, 75), 2);
var convexHull = new VectorOfInt();
CvInvoke.ConvexHull(currentContour, convexHull, false, false);
defects = new Mat();
CvInvoke.ConvexityDefects(currentContour, convexHull, defects);
if (!defects.IsEmpty)
{
Matrix <int> m = new Matrix <int>(defects.Rows, defects.Cols,
defects.NumberOfChannels); // copy Mat to a matrix...
defects.CopyTo(m);
Matrix <int>[] channels = m.Split();
if (channels.Length >= 2)
{
startIndex = channels.ElementAt(0).Data;
endIndex = channels.ElementAt(1).Data;
depthIndex = channels.ElementAt(2).Data;
}
}
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = new Mat();
capture.Retrieve(frame, 0);
//preprocessing
Image <Bgr, byte> finalImg = frame.ToImage <Bgr, byte>().Flip(FlipType.Horizontal);
Image <Gray, byte> processingImg = finalImg.Convert <Gray, byte>();
BiTonalLevel.Dispatcher.BeginInvoke(new Action(() =>
{
if (BiTonalLevel.Value > 0)
{
processingImg = processingImg.ThresholdBinary(new Gray(BiTonalLevel.Value), new Gray(255));
}
}));
BlurLevel.Dispatcher.BeginInvoke(new Action(() =>
{
if (BlurLevel.Value > 1)
{
CvInvoke.Blur(processingImg, processingImg, new System.Drawing.Size((int)BlurLevel.Value, (int)BlurLevel.Value), new System.Drawing.Point(-1, -1));
}
}));
//morphological processing
processingImg.MorphologyEx(firstMorphOp, kernel, new System.Drawing.Point(-1, -1), firstMorphSteps, BorderType.Default, new MCvScalar());
if (doubleMorph)
{
processingImg.MorphologyEx(secondMorphOp, kernel2, new System.Drawing.Point(-1, -1), secondMorphSteps, BorderType.Default, new MCvScalar());
}
ProcessingVideoBox.Dispatcher.BeginInvoke(new Action(() => ProcessingVideoBox.Source = ToBitmapGrey(processingImg)));
//edge detection
Mat edges = new Mat(frame.Size, frame.Depth, 1);
CvInvoke.Canny(processingImg, edges, lowerTresholdLevel, upperTresholdLevel, cannyKernelSize);
//contours finding
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
Mat hierarchy = new Mat();
int largest_contour_index = 0;
double largest_area = 0;
CvInvoke.FindContours(edges, contours, hierarchy, contouringMode, contouringMethod);
for (int i = 0; i < contours.Size; i++)
{
double a = CvInvoke.ContourArea(contours[i], false);
if (a > largest_area)
{
largest_area = a;
largest_contour_index = i;
}
}
CvInvoke.DrawContours(finalImg, contours, largest_contour_index, redColor, 3, LineType.EightConnected, hierarchy);
//defects points finding
VectorOfInt hull = new VectorOfInt();
Mat defects = new Mat();
if (contours.Size > 0)
{
VectorOfPoint largestContour = new VectorOfPoint(contours[largest_contour_index].ToArray());
CvInvoke.ConvexHull(largestContour, hull, false, true);
CvInvoke.ConvexityDefects(largestContour, hull, defects);
if (!defects.IsEmpty)
{
Matrix <int> m = new Matrix <int>(defects.Rows, defects.Cols, defects.NumberOfChannels);
defects.CopyTo(m);
Matrix <int>[] channels = m.Split();
for (int i = 1; i < defects.Rows; ++i)
{
finalImg.Draw(new System.Drawing.Point[] { largestContour[channels[0][i, 0]], largestContour[channels[1][i, 0]] }, new Bgr(100, 255, 100), 2);
CvInvoke.Circle(finalImg, new System.Drawing.Point(largestContour[channels[0][i, 0]].X, largestContour[channels[0][i, 0]].Y), 7, new MCvScalar(255, 0, 0), -1);
}
}
}
MainVideoBox.Dispatcher.BeginInvoke(new Action(() => MainVideoBox.Source = ToBitmapFinal(finalImg)));
}
public void Tick(Object sender, EventArgs args)
{
if (mKinect != null)
{
MultiSourceFrame frame = mFrameReader.AcquireLatestFrame();
TrackFingers();
if (frame != null)
{
using (var depthFrame = frame.DepthFrameReference.AcquireFrame())
{
if (depthFrame != null)
{
if (depthData == null)
{
depthWidth = depthFrame.FrameDescription.Width;
depthHeight = depthFrame.FrameDescription.Height;
depthData = new ushort[depthWidth * depthHeight];
pixelData = new byte[depthWidth * depthHeight * 3];
mFrame = new Mat(depthHeight, depthWidth, DepthType.Cv8U, 1);
}
ushort minDepth = depthFrame.DepthMinReliableDistance;
ushort maxDepth = depthFrame.DepthMaxReliableDistance;
depthFrame.CopyFrameDataToArray(depthData);
Image <Gray, Byte> img = mFrame.ToImage <Gray, Byte>();
for (int i = 0; i < depthData.Length; i++)
{
ushort depth = depthData[i];
//byte intensity = (byte)(depth >= minDepth && depth <= maxDepth ? depth : 0);
byte intensity = (byte)(depth < 1000 && depth > 10 ? 0 : 255);
img.Data[i / depthWidth, i % depthWidth, 0] = intensity;
}
mFrame = img.Mat;
// DISPLAY Depth image
//(Controls["FrameImageBox"] as ImageBox).Image = img;
//*********************
// Gaussian Blur
//*********************
CvInvoke.GaussianBlur(img, img, new Size(5, 5), 0);
//*********************
// Threshold
//*********************
//mFrame = img.Mat;
//Mat thresholds = new Mat(); ;
//CvInvoke.Threshold(mFrame, thresholds, THRESHOLD, THRESHOLD_MAX_VALUE, ThresholdType.Binary);
//// DISPLAY Thresholds
//(Controls["FrameImageBox"] as ImageBox).Image = img;
//*********************
// Contours
//*********************
Mat hierarchy = new Mat();
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
VectorOfVectorOfPointF significantContours = new VectorOfVectorOfPointF();
CvInvoke.FindContours(mFrame, contours, hierarchy, RetrType.Tree, ChainApproxMethod.ChainApproxNone);
Image <Gray, Byte> contourImage = new Image <Gray, Byte>(mFrame.Size);
for (int i = 0; i < contours.Size; i++)
{
if (CvInvoke.ContourArea(contours[i]) > 500.0)
{
VectorOfPointF bigContour = new VectorOfPointF();
System.Drawing.PointF[] points = new System.Drawing.PointF[contours[i].Size];
Point[] intPoints = contours[i].ToArray();
for (int j = 0; j < intPoints.Length; j++)
{
points[j] = intPoints[j];
}
bigContour.Push(points);
significantContours.Push(bigContour);
}
}
//if (contours.Size > 0)
//{
// CvInvoke.DrawContours(contourImage, significantContours, -1, new MCvScalar(255, 0, 0));
//}
//(Controls["FrameImageBox"] as ImageBox).Image = contourImage;
//*********************
// Convex Hulls
//*********************
for (int i = 0; i < significantContours.Size; i++)
{
System.Drawing.PointF[] hullPoints;
VectorOfPoint contourPoints = new VectorOfPoint(Array.ConvertAll(significantContours[i].ToArray(), Point.Round));
VectorOfInt convexHull = new VectorOfInt();
hullPoints = CvInvoke.ConvexHull(significantContours[i].ToArray());
CvInvoke.ConvexHull(contourPoints, convexHull);
CvInvoke.Polylines(mFrame, Array.ConvertAll(hullPoints, Point.Round), true, new MCvScalar(255, 255, 255));
// How many defects tho?
//VectorOfVectorOfInt defects = new VectorOfVectorOfInt();
Mat defects = new Mat();
CvInvoke.ConvexityDefects(contourPoints /*significantContours[i]*/,
convexHull /*new VectorOfPointF(hullPoints)*/,
defects);
if (!defects.IsEmpty)
{
Matrix <int> m = new Matrix <int>(defects.Rows, defects.Cols, defects.NumberOfChannels);
defects.CopyTo(m);
List <Point> validPoints = new List <Point>();
// Draw tha defacts
for (int d = 0; d < m.Rows; d++)
{
int startIndex = m.Data[d, 0];
int endIndex = m.Data[d, 1];
int farthestIndex = m.Data[d, 2];
Point farthestPoint = contourPoints[farthestIndex];
Point startPoint = contourPoints[startIndex];
if (IsDefectUnique(startPoint, validPoints) &&
IsDefectOutsideHandRadius(startPoint))
{
validPoints.Add(startPoint);
}
//if (true/*endIndex - startIndex > 10*/)
//{
// CvInvoke.Circle(mFrame, startPoint, 3, new MCvScalar(255, 0, 0), 2);
//}
}
// Draw valid indices
foreach (Point p in validPoints)
{
CvInvoke.Circle(mFrame, p, 3, new MCvScalar(255, 0, 0), 2);
}
}
}
(Controls["FrameImageBox"] as ImageBox).Image = mFrame;
}
}
}
}
}
public VectorOfPoint FindLargestContour(IInputOutputArray cannyEdges, IInputOutputArray result, out int num)
{
int largest_contour_index = 0;
double largest_area = 0;
int handnum = 0;
VectorOfPoint largestContour;
int defectcount = 0;
num = 0;
defectcount = 0;
using (Mat hierachy = new Mat())
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
IOutputArray hirarchy;
CvInvoke.FindContours(cannyEdges, contours, hierachy, RetrType.List, ChainApproxMethod.ChainApproxSimple);
for (int i = 0; i < contours.Size; i++)
{
MCvScalar color = new MCvScalar(0, 0, 255);
double a = CvInvoke.ContourArea(contours[i], false); // Find the area of contour
if (a > largest_area)
{
largest_area = a;
largest_contour_index = i; //Store the index of largest contour
}
CvInvoke.DrawContours(result, contours, largest_contour_index, new MCvScalar(255, 0, 0));
}
if (largest_area == 0)
{
largestContour = new VectorOfPoint();
goto goto3;
}
int num4 = 0;
int num1 = 0;
int num2 = 0;
CvInvoke.DrawContours(result, contours, largest_contour_index, new MCvScalar(0, 0, 255), 3, LineType.EightConnected, hierachy);
// RotatedRect contour_center= CvInvoke.MinAreaRect(hull[0]);
// Point armcenter = new Point();
// armcenter.X = (int)contour_center.Center.X;
// armcenter.Y = (int)contour_center.Center.Y;
// CvInvoke.Circle(result, armcenter, 10, new MCvScalar(255, 255, 255));
try
{
// CascadeClassifier haar = new CascadeClassifier("C:\\Users\\ykk\\Downloads\\Opencv-master\\aarcascade\\closed_frontal_palm.xml");
using (VectorOfPoint contour = contours[largest_contour_index])
using (Mat defects = new Mat())
using (VectorOfPoint approxContour = new VectorOfPoint())
using (VectorOfPoint hull = new VectorOfPoint())
using (VectorOfInt Hull = new VectorOfInt())
{
CvInvoke.ApproxPolyDP(contour, approxContour, 50, true);
// CvInvoke.DrawContours(result, approxContour, 0, new MCvScalar(255, 0, 0));
CvInvoke.ConvexHull(contour, hull, false);
CvInvoke.ConvexHull(contour, Hull, false, false);
CvInvoke.Polylines(result, hull, true, new MCvScalar(0, 255, 0), 1, LineType.AntiAlias);
CvInvoke.ConvexityDefects(contour, Hull, defects);
RotatedRect box = CvInvoke.MinAreaRect(contour);
Rectangle rect = CvInvoke.BoundingRectangle(hull);
CvInvoke.Rectangle(result, rect, new MCvScalar(255, 100, 0));
Point CENTER = new Point(rect.X + rect.Width / 2, rect.Y + rect.Height / 2);
if (defects.Cols == 1 && defects.Rows > 0)
{
Matrix <int> m = new Matrix <int>(defects.Rows, defects.Cols, defects.NumberOfChannels); // copy Mat to a matrix...
defects.CopyTo(m);
Matrix <int>[] channels = m.Split();
float max = 0;
float distance = 0;
//List<PointF> palm = new List<PointF>();
int[] Distance = new int[defects.Rows];
VectorOfPoint palm_points = new VectorOfPoint();
for (int i = 0; i < defects.Rows; i++)
{
Distance[i] = channels[3][i, 0];
//Distance[i]= (int)Math.Sqrt(Math.Pow(contour[channels[2][i,0]].X - contour[channels[2][i,0]].X, 2) + Math.Pow(contour[channels[2][i, 0]].Y- contour[channels[2][i, 0]].Y, 2));
max = (int)Math.Max(max, Distance[i]);
}
List <PointF> importantdepthpoint = new List <PointF>();
for (int i = 0; i < defects.Rows; i++)
{
if (Distance[i] > 0.15 * max)
{
importantdepthpoint.Add(new Point(contour[channels[2][i, 0]].X, contour[channels[2][i, 0]].Y));
}
}
PointF[] depth = importantdepthpoint.ToArray();
CircleF palm = CvInvoke.MinEnclosingCircle(depth);
//palm = new CircleF(palm.Center,(float))
CvInvoke.Circle(result, new Point((int)palm.Center.X, (int)palm.Center.Y), (int)palm.Radius, new MCvScalar(255, 100, 255), 3);
for (int i = 0; i < defects.Rows; i++)
{
int startIdx = channels[0][i, 0];
int endIdx = channels[1][i, 0];
int hhh = channels[2][i, 0];
Point p1 = contour[startIdx];
Point p2 = contour[endIdx];
Point p3 = contour[hhh];
LineSegment2D startdepthline = new LineSegment2D(p1, p3);
LineSegment2D depthendline = new LineSegment2D(p3, p2);
CircleF startcircle = new CircleF(p1, (float)5);
CircleF depthcircle = new CircleF(p3, 5f);
CircleF endcircle = new CircleF(p2, 5f);
distance = (float)(channels[3][i, 0] / 256);
// CvInvoke.Circle(result, p1, 8, new MCvScalar(255, 100, 0));
// CvInvoke.Circle(result, p2, 20, new MCvScalar(100, 255, 255));
//CvInvoke.Circle(result, p3, 20, new MCvScalar(0, 255, 100));
if (distance > 25 && distance < 110)
{
double angle = Math.Atan2(CENTER.Y - p1.Y, CENTER.X - p1.X) * 180 / Math.PI;
float inangle = innerAngle((float)p1.X, (float)p1.Y, (float)p2.X, (float)p2.Y, (float)p3.X, (float)p3.Y);
double length = Math.Sqrt(Math.Pow(p1.X - p3.X, 2) + Math.Pow(p1.Y - p3.Y, 2));
float Angle = getAngle(p1, p3, p2);
// CvInvoke.PointPolygonTest(palm, p1,false);
if (!(p2.X < palm.Center.X + palm.Radius + 15 && p2.X > palm.Center.X - palm.Radius - 15 && p2.Y > palm.Center.Y - palm.Radius - 15 && p2.Y < palm.Center.Y + palm.Radius + 15))
// if (!(p1.X < palm.Center.X && p1.X < palm.Center.X + palm.Radius + 15 && p1.X > palm.Center.X - palm.Radius - 15 && p1.Y < palm.Center.Y && p1.Y < palm.Center.Y + palm.Radius + 15 && p1.Y > palm.Center.Y - palm.Radius - 15))
{
//if (Math.Abs(inangle) > 20 && Math.Abs(inangle) < 200 && angle > -180 && angle < 270)
if (Angle > 20 && Angle < 100 && length < 120 && length > 40)
{
if ((startcircle.Center.Y < box.Center.Y || depthcircle.Center.Y < box.Center.Y) && (startcircle.Center.Y < depthcircle.Center.Y) && (Math.Sqrt(Math.Pow(startcircle.Center.X - depthcircle.Center.X, 2) + Math.Pow(startcircle.Center.Y - depthcircle.Center.Y, 2)) > box.Size.Height / 7))
{
//hand = true;
defectcount++;
handnum = defectcount + 1;
CvInvoke.Line(result, p1, p3, new MCvScalar(255, 255, 0), 5);
CvInvoke.Line(result, p2, p3, new MCvScalar(255, 255, 0), 5);
CvInvoke.PutText(result, (int)length + " " + (int)Angle, p1, FontFace.HersheyPlain, 1, new MCvScalar(255, 255, 0));
// currentFrame.Draw(startDepthLine, new Bgr(Color.Green), 2);
}
}
else if (defectcount == 0)
{
CvInvoke.Line(result, p1, p3, new MCvScalar(25, 200, 0), 5);
CvInvoke.Line(result, p2, p3, new MCvScalar(25, 200, 0), 5);
CvInvoke.PutText(result, (int)distance + " " + Angle.ToString(), p1, FontFace.HersheyPlain, 1, new MCvScalar(255, 255, 0));
handnum = 1;
}
}
}
else
{
CvInvoke.Circle(result, contour[channels[0][i, 0]], 4, new MCvScalar(255, 255, 255), 5);
CvInvoke.PutText(result, (int)distance + " ", p1, FontFace.HersheyPlain, 1, new MCvScalar(255, 255, 0), 2);
//CvInvoke.Circle(result, contour[channels[1][i, 0]], 4, new MCvScalar(255, 255, 0),5);
}
distance = channels[3][i, 0];
if (distance <= 10000)
{
continue;
}
//defectcount++;
/* if (distance <= 20000) { continue; }
*
*
* CvInvoke.Circle(result, p1, 8, new MCvScalar(255, 255, 0));
* CvInvoke.Circle(result, p2, 7, new MCvScalar(255, 255, 255));
* CvInvoke.Circle(result, p3, 10, new MCvScalar(0, 255, 255));
* defectcount++;
*
*/
}
// RotatedRect con = CvInvoke.MinAreaRect(contour);
//CircleF palmcircle = CvInvoke.MinEnclosingCircle(palm.ToArray());
//int radiu = (int)(1.1 * (con.Center.Y - palmcircle.Center.Y));
//if (radiu < 0) radiu = -radiu;
// CvInvoke.Circle(result,new Point((int)palmcircle.Center.X,(int)palmcircle.Center.Y),radiu,new MCvScalar(255,0,255));
}
num = handnum;
// CvInvoke.ConvexityDefects(contour, hull, defects);
/* Mat defects = new Mat();
* largestContour = new VectorOfPoint(contours[largest_contour_index].ToArray());
* VectorOfVectorOfPoint La = new VectorOfVectorOfPoint(contours[largest_contour_index]);
* if (largestContour != null)
* {
*
* for (int i = 0; i < La.Size; i++)
*
* {
*
* VectorOfPoint contour;
* Mat hierarchy = new Mat();
* VectorOfInt hull = new VectorOfInt();
* contour = La[i];
* CvInvoke.ConvexHull(contour, hull, false, false);
* //CvInvoke.DrawContours(result,hull,1,new MCvScalar(255,255,0));
* // CvInvoke.Polylines(result, hull, true, new MCvScalar(0, 255, 0), 1, LineType.AntiAlias);
* CvInvoke.ConvexityDefects(contour, hull, defects);
* Matrix<int> m = new Matrix<int>(defects.Rows, defects.Cols, defects.NumberOfChannels); // copy Mat to a matrix...
* defects.CopyTo(m);
* Matrix<int>[] channels = m.Split();
* for (i = 0; i < defects.Rows; i++)
* {
* Point p1 = contour[channels[0][i, 0]];
* Point p2 = contour[channels[1][i, 0]];
* Point p3 = contour[channels[2][i, 0]];
* float distance = channels[3][i, 0];
* if (distance > 10000) { continue; }
* CvInvoke.Circle(result, p1, 3, new MCvScalar(255, 255, 0));
* CvInvoke.Circle(result, p2, 8, new MCvScalar(0, 255, 0));
* CvInvoke.Circle(result, p3, 3, new MCvScalar(0, 255, 255));
* defectcount++;
*
* }
*
*
*
*/
// }
/* using (VectorOfPoint contour = La[i])
* using ( defects = new Mat())
* using (VectorOfPoint approxContour = new VectorOfPoint())
* using (VectorOfInt hull = new VectorOfInt())
* {
* CvInvoke.ApproxPolyDP(contour, approxContour, 50, true);
* CvInvoke.ConvexHull(approxContour, hull, false);
* // CvInvoke.DrawContours(result,contours,i,new MCvScalar(0,255,0));
* CvInvoke.Polylines(result, hull, true, new MCvScalar(0, 255, 0), 1, LineType.AntiAlias);
* CvInvoke.ConvexityDefects(contour, hull, defects);
*
* if (!defects.IsEmpty)
* {
* int nomdef = defects.Total.ToInt32();
*
*
* }
*
*/
/*
* for (int u = 0; u < defects.; u++)
* {
*
* Point p1 = contour[defects[u][0]];
* Point p2 = contour[defects[u][1]];
* Point p3 = contour[defects[u][2]];
* float dist = defects[u][3];
* if (dist <= 1000) { continue; }
* CvInvoke.Circle(result, p1, 3, new MCvScalar(255, 255, 0));
* CvInvoke.Circle(result, p2, 8, new MCvScalar(0, 255, 0));
* CvInvoke.Circle(result, p3, 3, new MCvScalar(0, 255, 255));
* defectcount++;
* num = p1.X;
* }
*/
//2个扩
largestContour = new VectorOfPoint();
//CvInvokde.DrawContours(, contours, largest_contour_index, new MCvScalar(0, 0, 255), 1, LineType.EightConnected)
//}
}
}
catch (Exception e)
{
MessageBox.Show(e.ToString());
int value = num1;
int value2 = num2;
int vaalu = num4;
largestContour = new VectorOfPoint();
num = 0;
}
}
goto3:
return(largestContour);
}
