public static void GetSingleContour(Bitmap src, Point point, int id, Bitmap scene, out Bitmap result, out double area)
{
string adr = "temp.jpg";
File.Delete(adr);
src.Save(adr);
IplImage image = Cv.LoadImage(adr, LoadMode.AnyColor);
IplImage gray = Cv.CreateImage(Cv.GetSize(image), BitDepth.U8, 1);
IplImage bin = Cv.CreateImage(Cv.GetSize(image), BitDepth.U8, 1);
scene.Save(adr);
IplImage dst = Cv.LoadImage(adr, LoadMode.AnyColor);
Cv.CvtColor(image, gray, ColorConversion.RgbToGray);
Cv.InRangeS(gray, 150, 255, bin);
CvMemStorage storage = Cv.CreateMemStorage(0);
CvSeq <CvPoint> contours = null;
int cont = Cv.FindContours(bin, storage, out contours, CvContour.SizeOf, ContourRetrieval.List, ContourChain.ApproxTC89KCOS, Cv.Point(0, 0));
contours = Cv.ApproxPoly(contours, CvContour.SizeOf, storage, ApproxPolyMethod.DP, 0, true);
double temp = 0;
for (CvSeq <CvPoint> seq0 = contours; seq0 != null; seq0 = seq0.HNext)
{
if (Cv.PointPolygonTest(seq0, new CvPoint2D32f(point.X, point.Y), false) > 0 &&
Cv.ContourArea(seq0) > 1000 &&
Cv.ContourArea(seq0) < (image.Height * image.Width * 0.5))
{
CvMoments moments = new CvMoments();
Cv.Moments(seq0, out moments, true);
int xc = (int)(moments.M10 / moments.M00);
int yc = (int)(moments.M01 / moments.M00);
CvConnectedComp comp;
if (id == 0)
{
Cv.FloodFill(dst, Cv.Point(point.X, point.Y), Cv.RGB(200, 0, 0), Cv.ScalarAll(10), Cv.ScalarAll(10), out comp, FloodFillFlag.FixedRange, null);
}
else
{
Cv.FloodFill(dst, Cv.Point(point.X, point.Y), Cv.RGB(0, 150, 50), Cv.ScalarAll(10), Cv.ScalarAll(10), out comp, FloodFillFlag.FixedRange, null);
}
dst.PutText(
id.ToString(),
Cv.Point(xc, yc),
new CvFont(FontFace.HersheySimplex, 2, 2, 1, 5, LineType.Link8),
CvColor.Black);
temp = Cv.ContourArea(seq0);
}
}
result = dst.ToBitmap();
area = temp;
}
public Moments()
{
// (1)画像を読み込む．3チャンネル画像の場合はCOIがセットされていなければならない
using (IplImage srcImg = new IplImage(Const.ImageLenna, LoadMode.AnyColor | LoadMode.AnyDepth))
{
if (srcImg.NChannels == 3 && srcImg.COI == 0)
{
srcImg.COI = 1;
}
// (2)入力画像の３次までの画像モーメントを計算する
CvMoments moments = new CvMoments(srcImg, false);
srcImg.COI = 0;
// (3)モーメントやHuモーメント不変量を，得られたCvMoments構造体の値を使って計算する．
double spatialMoment = moments.GetSpatialMoment(0, 0);
double centralMoment = moments.GetCentralMoment(0, 0);
double normCMoment = moments.GetNormalizedCentralMoment(0, 0);
CvHuMoments huMoments = new CvHuMoments(moments);
// (4)得られたモーメントやHuモーメント不変量を文字として画像に描画
using (CvFont font = new CvFont(FontFace.HersheySimplex, 1.0, 1.0, 0, 2, LineType.Link8))
{
string[] text = new string[10];
text[0] = string.Format("spatial={0:F3}", spatialMoment);
text[1] = string.Format("central={0:F3}", centralMoment);
text[2] = string.Format("norm={0:F3}", spatialMoment);
text[3] = string.Format("hu1={0:F10}", huMoments.Hu1);
text[4] = string.Format("hu2={0:F10}", huMoments.Hu2);
text[5] = string.Format("hu3={0:F10}", huMoments.Hu3);
text[6] = string.Format("hu4={0:F10}", huMoments.Hu4);
text[7] = string.Format("hu5={0:F10}", huMoments.Hu5);
text[8] = string.Format("hu6={0:F10}", huMoments.Hu6);
text[9] = string.Format("hu7={0:F10}", huMoments.Hu7);
CvSize textSize = font.GetTextSize(text[0]);
for (int i = 0; i < 10; i++)
{
srcImg.PutText(text[i], new CvPoint(10, (textSize.Height + 3) * (i + 1)), font, CvColor.Black);
}
}
// (5)入力画像とモーメント計算結果を表示，キーが押されたときに終了
using (CvWindow window = new CvWindow("Image", WindowMode.AutoSize))
{
window.ShowImage(srcImg);
Cv.WaitKey(0);
}
}
}
public Moments()
{
using (IplImage srcImg = new IplImage(FilePath.Image.Lenna, LoadMode.AnyColor | LoadMode.AnyDepth))
{
if (srcImg.NChannels == 3 && srcImg.COI == 0)
{
srcImg.COI = 1;
}
CvMoments moments = new CvMoments(srcImg, false);
srcImg.COI = 0;
double spatialMoment = moments.GetSpatialMoment(0, 0);
double centralMoment = moments.GetCentralMoment(0, 0);
double normCMoment = moments.GetNormalizedCentralMoment(0, 0);
CvHuMoments huMoments = new CvHuMoments(moments);
// drawing
using (CvFont font = new CvFont(FontFace.HersheySimplex, 1.0, 1.0, 0, 2, LineType.Link8))
{
string[] text = new string[10];
text[0] = string.Format("spatial={0:F3}", spatialMoment);
text[1] = string.Format("central={0:F3}", centralMoment);
text[2] = string.Format("norm={0:F3}", spatialMoment);
text[3] = string.Format("hu1={0:F10}", huMoments.Hu1);
text[4] = string.Format("hu2={0:F10}", huMoments.Hu2);
text[5] = string.Format("hu3={0:F10}", huMoments.Hu3);
text[6] = string.Format("hu4={0:F10}", huMoments.Hu4);
text[7] = string.Format("hu5={0:F10}", huMoments.Hu5);
text[8] = string.Format("hu6={0:F10}", huMoments.Hu6);
text[9] = string.Format("hu7={0:F10}", huMoments.Hu7);
CvSize textSize = font.GetTextSize(text[0]);
for (int i = 0; i < 10; i++)
{
srcImg.PutText(text[i], new CvPoint(10, (textSize.Height + 3) * (i + 1)), font, CvColor.Black);
}
}
using (var window = new CvWindow("Image", WindowMode.AutoSize))
{
window.ShowImage(srcImg);
Cv.WaitKey(0);
}
}
}
public static void GetAllObjects(Bitmap src, Point point, out Bitmap result, out ComplexObject etalon, out List <ComplexObject> allcontours)
{
allcontours = new List <ComplexObject>();
etalon = new ComplexObject();
string adr = "temp.jpg";
if (File.Exists(adr))
{
File.Delete(adr);
}
src.Save(adr);
IplImage image = Cv.LoadImage(adr, LoadMode.AnyColor);
if (File.Exists(adr))
{
File.Delete(adr);
}
IplImage gray = Cv.CreateImage(Cv.GetSize(image), BitDepth.U8, 1);
IplImage bin = Cv.CreateImage(Cv.GetSize(image), BitDepth.U8, 1);
IplImage dst = Cv.CloneImage(image);
Cv.CvtColor(image, gray, ColorConversion.RgbToGray);
Cv.InRangeS(gray, 150, 255, bin);
CvMemStorage storage = Cv.CreateMemStorage(0);
CvSeq <CvPoint> contours = null;
int cont = Cv.FindContours(bin, storage, out contours, CvContour.SizeOf, ContourRetrieval.List, ContourChain.ApproxTC89KCOS, Cv.Point(0, 0));
contours = Cv.ApproxPoly(contours, CvContour.SizeOf, storage, ApproxPolyMethod.DP, 0, true);
int id = 1;
for (CvSeq <CvPoint> seq0 = contours; seq0 != null; seq0 = seq0.HNext)
{
if (Cv.ContourArea(seq0) > 1000 && Cv.ContourArea(seq0) < (image.Height * image.Width * 0.5))
{
CvMoments moments = new CvMoments();
Cv.Moments(seq0, out moments, true);
double xc = (moments.M10 / moments.M00);
double yc = (moments.M01 / moments.M00);
double distance = Math.Sqrt(xc * xc + yc * yc);
if (Cv.PointPolygonTest(seq0, new CvPoint2D32f(point.X, point.Y), false) > 0)
{
etalon = new ComplexObject(seq0, new CvPoint2D32f(xc, yc), true, 0, Cv.ContourArea(seq0), distance);
Cv.DrawContours(dst, seq0, Cv.RGB(250, 0, 0), Cv.RGB(50, 250, 0), 0, -1, LineType.Link8);
dst.PutText(
"0",
Cv.Point((int)xc, (int)yc),
new CvFont(FontFace.HersheySimplex, 2, 2, 1, 5, LineType.Link8),
CvColor.Black);
}
else
{
allcontours.Add(new ComplexObject(seq0, new CvPoint2D32f(xc, yc), false, id, Cv.ContourArea(seq0), distance));
id++;
}
}
}
allcontours.Sort(delegate(ComplexObject ob1, ComplexObject ob2)
{
return(ob1.Distance.CompareTo(ob2.Distance));
});
for (int i = 0; i < allcontours.Count; i++)
{
allcontours[i].Id = i + 1;
Cv.DrawContours(dst, allcontours[i].Cont, Cv.RGB(0, 150, 50), Cv.RGB(50, 250, 0), 0, -1, LineType.Link8);
dst.PutText(
allcontours[i].Id.ToString(),
allcontours[i].Center,
new CvFont(FontFace.HersheySimplex, 2, 2, 1, 5, LineType.Link8),
CvColor.Black);
}
allcontours.Sort(delegate(ComplexObject ob1, ComplexObject ob2)
{
return(ob1.Id.CompareTo(ob2.Id));
});
result = dst.ToBitmap();
}
public static void GetAllObjects(Bitmap src, out Bitmap result, out List <BloodObjects> allObjects, string adrWEB)
{
allObjects = new List <BloodObjects>();
string adr = string.Empty;
try
{
adr = "temp.jpg";
File.Delete(adr);
src.Save(adr);
}
catch (System.Runtime.InteropServices.ExternalException)
{
adr = adrWEB;
File.Delete(adr);
src.Save(adr);
}
IplImage image = Cv.LoadImage(adr, LoadMode.AnyColor);
IplImage gray = Cv.CreateImage(Cv.GetSize(image), BitDepth.U8, 1);
IplImage bin = Cv.CreateImage(Cv.GetSize(image), BitDepth.U8, 1);
IplImage dst = Cv.CloneImage(image);
Cv.CvtColor(image, gray, ColorConversion.RgbToGray);
Cv.InRangeS(gray, 150, 255, bin);
CvMemStorage storage = Cv.CreateMemStorage(0);
CvSeq <CvPoint> contours = null;
int cont = Cv.FindContours(bin, storage, out contours, CvContour.SizeOf, ContourRetrieval.List, ContourChain.ApproxTC89KCOS, Cv.Point(0, 0));
contours = Cv.ApproxPoly(contours, CvContour.SizeOf, storage, ApproxPolyMethod.DP, 0, true);
int id = 0;
for (CvSeq <CvPoint> seq0 = contours; seq0 != null; seq0 = seq0.HNext)
{
if (Cv.ContourArea(seq0) > 100 && Cv.ContourArea(seq0) < (image.Height * image.Width * 0.5))
{
CvMoments moments = new CvMoments();
Cv.Moments(seq0, out moments, true);
double xc = (moments.M10 / moments.M00);
double yc = (moments.M01 / moments.M00);
double distance = Math.Sqrt(xc * xc + yc * yc);
allObjects.Add(new BloodObjects(
id,
seq0,
seq0.ToList(),
Cv.ContourArea(seq0),
new CvPoint2D32f(xc, yc),
distance,
Math.Pow(Cv.ContourPerimeter(seq0), 2) / Cv.ContourArea(seq0),
Cv.ContourPerimeter(seq0),
Group.Interest));
id++;
}
}
allObjects = Classified(allObjects);
allObjects.Sort(delegate(BloodObjects ob1, BloodObjects ob2)
{
return(ob1.Distance.CompareTo(ob2.Distance));
});
for (int i = 0; i < allObjects.Count; i++)
{
allObjects[i].Id = i;
if (allObjects[i].Group == Group.Interest)
{
Cv.DrawContours(dst, allObjects[i].Contour, Cv.RGB(0, 250, 0), Cv.RGB(50, 250, 0), 0, -1, LineType.Link8);
}
else if (allObjects[i].Group == Group.Small)
{
Cv.DrawContours(dst, allObjects[i].Contour, Cv.RGB(0, 0, 250), Cv.RGB(50, 250, 0), 0, -1, LineType.Link8);
}
else
{
Cv.DrawContours(dst, allObjects[i].Contour, Cv.RGB(250, 0, 0), Cv.RGB(50, 250, 0), 0, -1, LineType.Link8);
}
dst.PutText(
allObjects[i].Id.ToString(),
allObjects[i].Center,
new CvFont(FontFace.HersheySimplex, 0.4, 0.4, 0.5, 1, LineType.Link8),
CvColor.Black);
}
allObjects.Sort(delegate(BloodObjects ob1, BloodObjects ob2)
{
return(ob1.Id.CompareTo(ob2.Id));
});
result = dst.ToBitmap();
}
private void task()
{
Camera camera = Camera.GetInstance();
MotorControler mc = MotorControler.GetInstance(parameterManager);
Vector3 CurrentPoint = mc.GetPoint();
Vector3 p = new Vector3();
int BinarizeThreshold = 10;
int BrightnessThreshold = 7;
Mat sum = Mat.Zeros(440, 512, MatType.CV_8UC1);
string datfileName = string.Format(@"c:\img\{0}.dat", System.DateTime.Now.ToString("yyyyMMdd_HHmmss_fff"));
BinaryWriter writer = new BinaryWriter(File.Open(datfileName, FileMode.Create));
for (int i = 0; i < 10; i++)
{
byte[] b = camera.ArrayImage;
writer.Write(b);
p = mc.GetPoint();
Mat mat = new Mat(440, 512, MatType.CV_8U, b);
mat.ImWrite(String.Format(@"c:\img\{0}_{1}_{2}_{3}.bmp",
System.DateTime.Now.ToString("yyyyMMdd_HHmmss_fff"),
(int)(p.X * 1000),
(int)(p.Y * 1000),
(int)(p.Z * 1000)));
Cv2.GaussianBlur(mat, mat, Cv.Size(3, 3), -1);
Mat gau = mat.Clone();
Cv2.GaussianBlur(gau, gau, Cv.Size(31, 31), -1);
Cv2.Subtract(gau, mat, mat);
Cv2.Threshold(mat, mat, BinarizeThreshold, 1, ThresholdType.Binary);
Cv2.Add(sum, mat, sum);
mc.MoveDistance(-0.003, VectorId.Z);
mc.Join();
}
Cv2.Threshold(sum, sum, BrightnessThreshold, 1, ThresholdType.Binary);
//Cv2.FindContoursをつかうとAccessViolationExceptionになる(Release/Debug両方)ので、C-API風に書く
using (CvMemStorage storage = new CvMemStorage())
{
using (CvContourScanner scanner = new CvContourScanner(sum.ToIplImage(), storage, CvContour.SizeOf, ContourRetrieval.Tree, ContourChain.ApproxSimple))
{
//string fileName = string.Format(@"c:\img\{0}.txt",
// System.DateTime.Now.ToString("yyyyMMdd_HHmmss_fff"));
string fileName = string.Format(@"c:\img\u.txt");
foreach (CvSeq <CvPoint> c in scanner)
{
CvMoments mom = new CvMoments(c, false);
if (c.ElemSize < 2)
{
continue;
}
if (mom.M00 == 0.0)
{
continue;
}
double mx = mom.M10 / mom.M00;
double my = mom.M01 / mom.M00;
File.AppendAllText(fileName, string.Format("{0:F} {1:F}\n", mx, my));
}
}
}
sum *= 255;
sum.ImWrite(String.Format(@"c:\img\{0}_{1}_{2}.bmp",
System.DateTime.Now.ToString("yyyyMMdd_HHmmss_fff"),
(int)(p.X * 1000),
(int)(p.Y * 1000)));
Vector2 encoderPoint = new Vector2(-1, -1);
encoderPoint.X = mc.GetPoint().X;
encoderPoint.Y = mc.GetPoint().Y;//おこられたのでしかたなくこうする 吉田20150427
Vector2 viewerPoint = new Vector2(-1, -1);
if (TigerPatternMatch.PatternMatch(ref viewerPoint))
{
encoderPoint = coordManager.TransToEmulsionCoord(viewerPoint);
mc.MovePointXY(encoderPoint);
mc.Join();
}
}
static OpenCvSharp.CPlusPlus.Point TrackDetection(List <Mat> mats, int px, int py, int shiftx = 2, int shifty = 2, int shiftpitch = 4, int windowsize = 40, int phthresh = 5, bool debugflag = false)
{
int x0 = px - 256;
int y0 = py - 220;
List <rawmicrotrack> rms = new List <rawmicrotrack>();
// Point2d pixel_cen = TrackDetection(binimages, 256, 220, 3, 3, 4, 90, 3);
int counter = 0;
for (int ax = -shiftx; ax <= shiftx; ax++)
{
for (int ay = -shifty; ay <= shifty; ay++)
{
using (Mat big = Mat.Zeros(600, 600, MatType.CV_8UC1))
using (Mat imgMask = Mat.Zeros(big.Height, big.Width, MatType.CV_8UC1))
{
//make the size of mask
int ystart = big.Height / 2 + y0 - windowsize / 2;
int yend = big.Height / 2 + y0 + windowsize / 2;
int xstart = big.Width / 2 + x0 - windowsize / 2;
int xend = big.Width / 2 + x0 + windowsize / 2;
//make mask as shape of rectangle. by use of opencv
OpenCvSharp.CPlusPlus.Rect recMask = new OpenCvSharp.CPlusPlus.Rect(xstart, ystart, windowsize, windowsize);
Cv2.Rectangle(imgMask, recMask, 255, -1);//brightness=1, fill
for (int p = 0; p < mats.Count; p++)
{
int startx = big.Width / 2 - mats[p].Width / 2 + (int)(p * ax * shiftpitch / 8.0);
int starty = big.Height / 2 - mats[p].Height / 2 + (int)(p * ay * shiftpitch / 8.0);
Cv2.Add(
big[starty, starty + mats[p].Height, startx, startx + mats[p].Width],
mats[p],
big[starty, starty + mats[p].Height, startx, startx + mats[p].Width]);
}
using (Mat big_c = big.Clone())
{
Cv2.Threshold(big, big, phthresh, 255, ThresholdType.ToZero);
Cv2.BitwiseAnd(big, imgMask, big);
//Mat roi = big[ystart, yend , xstart, xend];//メモリ領域がシーケンシャルにならないから輪郭抽出のときに例外が出る。
if (debugflag == true)
{//
//bigorg.ImWrite(String.Format(@"{0}_{1}_{2}.png",counter,ax,ay));
//Mat roiwrite = roi.Clone() * 30;
//roiwrite.ImWrite(String.Format(@"roi_{0}_{1}_{2}.png", counter, ax, ay));
Cv2.Rectangle(big_c, recMask, 255, 1);//brightness=1, fill
Cv2.ImShow("big_cx30", big_c * 30);
Cv2.ImShow("bigx30", big * 30);
//Cv2.ImShow("imgMask", imgMask);
//Cv2.ImShow("roi", roi * 30);
Cv2.WaitKey(0);
}
}//using big_c
using (CvMemStorage storage = new CvMemStorage())
using (CvContourScanner scanner = new CvContourScanner(big.ToIplImage(), storage, CvContour.SizeOf, ContourRetrieval.Tree, ContourChain.ApproxSimple))
{
foreach (CvSeq <CvPoint> c in scanner)
{
CvMoments mom = new CvMoments(c, false);
if (c.ElemSize < 2)
{
continue;
}
if (mom.M00 < 1.0)
{
continue;
}
double mx = mom.M10 / mom.M00;
double my = mom.M01 / mom.M00;
rawmicrotrack rm = new rawmicrotrack();
rm.ax = ax;
rm.ay = ay;
rm.cx = (int)(mx - big.Width / 2);
rm.cy = (int)(my - big.Height / 2);
rm.pv = (int)(mom.M00);
rms.Add(rm);
//Console.WriteLine(string.Format("{0} {1} {2} {3} {4}", rm.pv, ax, ay, rm.cx, rm.cy ));
}
}//using contour
//big_c.Dispose();
counter++;
}//using Mat
}//ay
}//ax
OpenCvSharp.CPlusPlus.Point trackpos = new OpenCvSharp.CPlusPlus.Point(0, 0);
if (rms.Count > 0)
{
rawmicrotrack rm = new rawmicrotrack();
double meancx = 0;
double meancy = 0;
double meanax = 0;
double meanay = 0;
double meanph = 0;
double meanpv = 0;
double sumpv = 0;
for (int i = 0; i < rms.Count; i++)
{
meanpv += rms[i].pv * rms[i].pv;
meancx += rms[i].cx * rms[i].pv;
meancy += rms[i].cy * rms[i].pv;
meanax += rms[i].ax * rms[i].pv;
meanay += rms[i].ay * rms[i].pv;
sumpv += rms[i].pv;
}
meancx /= sumpv;//重心と傾きを輝度値で重み付き平均
meancy /= sumpv;
meanax /= sumpv;
meanay /= sumpv;
meanpv /= sumpv;
trackpos = new OpenCvSharp.CPlusPlus.Point(
(int)(meancx) + 256 - meanax * shiftpitch,
(int)(meancy) + 220 - meanay * shiftpitch
);
double anglex = (meanax * shiftpitch * 0.267) / (3.0 * 7.0 * 2.2);
double angley = (meanay * shiftpitch * 0.267) / (3.0 * 7.0 * 2.2);
Console.WriteLine(string.Format("{0:f4} {1:f4}", anglex, angley));
}
else
{
trackpos = new OpenCvSharp.CPlusPlus.Point(-1, -1);
}
return(trackpos);
}//track detection
private void task()
{
TracksManager tm = parameterManager.TracksManager;
Track myTrack = tm.GetTrack(tm.TrackingIndex);
MotorControler mc = MotorControler.GetInstance(parameterManager);
Camera camera = Camera.GetInstance();
List <Mat> image_set = new List <Mat>();
List <Mat> image_set_reverse = new List <Mat>();
Surface surface = Surface.GetInstance(parameterManager);//表面認識から境界値を取得
double uptop = surface.UpTop;
double upbottom = surface.UpBottom;
double lowtop = surface.LowTop;
double lowbottom = surface.LowBottom;
double now_x = mc.GetPoint().X;
double now_y = mc.GetPoint().Y;
double now_z = mc.GetPoint().Z;
common_dx = myTrack.MsDX + ((0.265625 * over_dx * 3) / (0.024 * 2.2 * 1000));
common_dy = myTrack.MsDY - ((0.265625 * over_dy * 3) / (0.024 * 2.2 * 1000));
for (int i = 0; i < 8; i++)
{ //myTrack.MsD○はdz1mmあたりのd○の変位mm
double next_x = now_x - i * common_dx * 0.003 * 2.2; //3μm間隔で撮影
double next_y = now_y - i * common_dy * 0.003 * 2.2; //Shrinkage Factor は2.2で計算(仮)
mc.MovePoint(next_x, next_y, now_z - 0.003 * i);
mc.Join();
byte[] b = camera.ArrayImage;
Mat image = new Mat(440, 512, MatType.CV_8U, b);
Mat imagec = image.Clone();
image_set.Add(imagec);
}
for (int i = 7; i >= 0; i--)
{
image_set_reverse.Add(image_set[i]);
}
int n = image_set.Count();//１回分の取得画像の枚数
Mat cont = new Mat(440, 512, MatType.CV_8U);
Mat gau_1 = new Mat(440, 512, MatType.CV_8U);
Mat gau_2 = new Mat(440, 512, MatType.CV_8U);
Mat sub = new Mat(440, 512, MatType.CV_8U);
Mat bin = new Mat(440, 512, MatType.CV_8U);
double Max_kido;
double Min_kido;
OpenCvSharp.CPlusPlus.Point maxloc;
OpenCvSharp.CPlusPlus.Point minloc;
List <Mat> two_set = new List <Mat>();
List <Mat> Part_img = new List <Mat>();
for (int i = 0; i < image_set.Count(); i++)
{
Cv2.GaussianBlur((Mat)image_set_reverse[i], gau_1, Cv.Size(3, 3), -1); //パラメータ見ないといけない。
Cv2.GaussianBlur(gau_1, gau_2, Cv.Size(51, 51), -1); //パラメータ見ないといけない。
Cv2.Subtract(gau_2, gau_1, sub);
Cv2.MinMaxLoc(sub, out Min_kido, out Max_kido, out minloc, out maxloc);
cont = (sub - Min_kido) * 255 / (Max_kido - Min_kido);
cont.ImWrite(string.Format(@"C:\set\cont_{0}.bmp", i));
Cv2.Threshold(cont, bin, 115, 1, ThresholdType.Binary);//パラメータ見ないといけない。
two_set.Add(bin);
}
List <mm> white_area = new List <mm>();
int x0 = 256;
int y0 = 220;//視野の中心
for (int delta_xx = -1; delta_xx <= 1; delta_xx++)//一番下の画像よりどれだけずらすか
{
for (int delta_yy = -1; delta_yy <= 1; delta_yy++)
{
{
// //積層写真の型作り（行列の中身は０行列）
// Mat superimposed = Mat.Zeros(440 + (n - 1) * Math.Abs(delta_yy), 512 + (n - 1) * Math.Abs(delta_xx), MatType.CV_8UC1);
//
// //各写真の型作り
// for (int i = 0; i < two_set.Count; i++) {
// Mat Part = Mat.Zeros(440 + (n - 1) * Math.Abs(delta_yy), 512 + (n - 1) * Math.Abs(delta_xx), MatType.CV_8UC1);
// Part_img.Add(Part);
// }
//積層写真の型作り（行列の中身は０行列）
Mat superimposed = Mat.Zeros(440 + 3 * Math.Abs(delta_yy), 512 + 3 * Math.Abs(delta_xx), MatType.CV_8UC1);
//各写真の型作り
for (int i = 0; i < two_set.Count; i++)
{
Mat Part = Mat.Zeros(440 + 3 * Math.Abs(delta_yy), 512 + 3 * Math.Abs(delta_xx), MatType.CV_8UC1);
Part_img.Add(Part);
}//2枚を１セットにしてずらす場合
if (delta_xx >= 0 && delta_yy >= 0)//画像の右下への移動
{
for (int i = 0; i < two_set.Count; i++)
{
if (i == 0 || i == 1)
{
Part_img[i][
0
, 440
, 0
, 512
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 2 || i == 3)
{
Part_img[i][
0 + Math.Abs(delta_yy) //yの値のスタート地点
, 440 + Math.Abs(delta_yy) //yの値のゴール地点
, 0 + Math.Abs(delta_xx) //xの値のスタート地点
, 512 + Math.Abs(delta_xx) //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 4 || i == 5)
{
Part_img[i][
0 + 2 * Math.Abs(delta_yy) //yの値のスタート地点
, 440 + 2 * Math.Abs(delta_yy) //yの値のゴール地点
, 0 + 2 * Math.Abs(delta_xx) //xの値のスタート地点
, 512 + 2 * Math.Abs(delta_xx) //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 6 || i == 7)
{
Part_img[i][
0 + 3 * Math.Abs(delta_yy) //yの値のスタート地点
, 440 + 3 * Math.Abs(delta_yy) //yの値のゴール地点
, 0 + 3 * Math.Abs(delta_xx) //xの値のスタート地点
, 512 + 3 * Math.Abs(delta_xx) //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
}
for (int i = 0; i < Part_img.Count(); i++)
{
superimposed += Part_img[i];
}
Cv2.Threshold(superimposed, superimposed, 5, 255, ThresholdType.ToZero);//パラメータ見ないといけない。
superimposed.SubMat(0
, 440
, 0
, 512).CopyTo(superimposed); //１枚目の画像の大きさ、場所で切り取る
}
if (delta_xx >= 0 && delta_yy < 0)//画像の右上への移動
{
for (int i = 0; i < two_set.Count; i++)
{
if (i == 0 || i == 1)
{
Part_img[i][
0 + 3
, 440 + 3
, 0
, 512
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 2 || i == 3)
{
Part_img[i][
0 + 3 - 1 //yの値のスタート地点
, 440 + 3 - 1 //yの値のゴール地点
, 0 + Math.Abs(delta_xx) //xの値のスタート地点
, 512 + Math.Abs(delta_xx) //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 4 || i == 5)
{
Part_img[i][
0 + 3 - 2 //yの値のスタート地点
, 440 + 3 - 2 //yの値のゴール地点
, 0 + 2 * Math.Abs(delta_xx) //xの値のスタート地点
, 512 + 2 * Math.Abs(delta_xx) //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 6 || i == 7)
{
Part_img[i][
0 + 3 - 3 //yの値のスタート地点
, 440 + 3 - 3 //yの値のゴール地点
, 0 + 3 * Math.Abs(delta_xx) //xの値のスタート地点
, 512 + 3 * Math.Abs(delta_xx) //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
}
for (int i = 0; i < Part_img.Count(); i++)
{
superimposed += Part_img[i];
}
Cv2.Threshold(superimposed, superimposed, 5, 255, ThresholdType.ToZero);//パラメータ見ないといけない。
superimposed.SubMat(0 + 3
, 440 + 3
, 0
, 512).CopyTo(superimposed); //１枚目の画像の大きさ、場所で切り取る
}
if (delta_xx < 0 && delta_yy < 0)//画像の左上への移動
{
for (int i = 0; i < two_set.Count; i++)
{
if (i == 0 || i == 1)
{
Part_img[i][
0 + 3
, 440 + 3
, 0 + 3
, 512 + 3
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 2 || i == 3)
{
Part_img[i][
0 + 3 - 1 //yの値のスタート地点
, 440 + 3 - 1 //yの値のゴール地点
, 0 + 3 - 1 //xの値のスタート地点
, 512 + 3 - 1 //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 4 || i == 5)
{
Part_img[i][
0 + 3 - 2 //yの値のスタート地点
, 440 + 3 - 2 //yの値のゴール地点
, 0 + 3 - 2 //xの値のスタート地点
, 512 + 3 - 2 //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 6 || i == 7)
{
Part_img[i][
0 + 3 - 3 //yの値のスタート地点
, 440 + 3 - 3 //yの値のゴール地点
, 0 + 3 - 3 //xの値のスタート地点
, 512 + 3 - 3 //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
}
for (int i = 0; i < Part_img.Count(); i++)
{
superimposed += Part_img[i];
}
Cv2.Threshold(superimposed, superimposed, 5, 255, ThresholdType.ToZero);//パラメータ見ないといけない。
superimposed.SubMat(0 + 3
, 440 + 3
, 0 + 3
, 512 + 3).CopyTo(superimposed); //１枚目の画像の大きさ、場所で切り取る
}
if (delta_xx < 0 && delta_yy >= 0)//画像の左下への移動
{
for (int i = 0; i < two_set.Count; i++)
{
if (i == 0 || i == 1)
{
Part_img[i][
0
, 440
, 0 + 3
, 512 + 3
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 2 || i == 3)
{
Part_img[i][
0 + Math.Abs(delta_yy) //yの値のスタート地点
, 440 + Math.Abs(delta_yy) //yの値のゴール地点
, 0 + 3 - 1 //xの値のスタート地点
, 512 + 3 - 1 //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 4 || i == 5)
{
Part_img[i][
0 + 2 * Math.Abs(delta_yy) //yの値のスタート地点
, 440 + 2 * Math.Abs(delta_yy) //yの値のゴール地点
, 0 + 3 - 2 //xの値のスタート地点
, 512 + 3 - 2 //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
else if (i == 6 || i == 7)
{
Part_img[i][
0 + 3 * Math.Abs(delta_yy) //yの値のスタート地点
, 440 + 3 * Math.Abs(delta_yy) //yの値のゴール地点
, 0 + 3 - 3 //xの値のスタート地点
, 512 + 3 - 3 //xの値のゴール地点
] = two_set[i]; //処理済み画像をPartの対応する部分に入れていく
}
}
for (int i = 0; i < Part_img.Count(); i++)
{
superimposed += Part_img[i];
}
Cv2.Threshold(superimposed, superimposed, 5, 255, ThresholdType.ToZero);//パラメータ見ないといけない。
superimposed.SubMat(0
, 440
, 0 + 3
, 512 + 3).CopyTo(superimposed); //１枚目の画像の大きさ、場所で切り取る
}
Mat one1 = Mat.Ones(y0 - 20, 512, MatType.CV_8UC1);//視野の中心からどれだけの窓を開けるか
Mat one2 = Mat.Ones(41, x0 - 20, MatType.CV_8UC1);
Mat one3 = Mat.Ones(41, 491 - x0, MatType.CV_8UC1);
Mat one4 = Mat.Ones(419 - y0, 512, MatType.CV_8UC1);
superimposed[0, y0 - 20, 0, 512] = one1 * 0;
superimposed[y0 - 20, y0 + 21, 0, x0 - 20] = one2 * 0;
superimposed[y0 - 20, y0 + 21, x0 + 21, 512] = one3 * 0;
superimposed[y0 + 21, 440, 0, 512] = one4 * 0;//中心から○μｍの正方形以外は黒くする。
superimposed.ImWrite("C:\\set\\superimposed25_1.bmp");
using (CvMemStorage storage = new CvMemStorage())
{
using (CvContourScanner scanner = new CvContourScanner(superimposed.ToIplImage(), storage, CvContour.SizeOf, ContourRetrieval.Tree, ContourChain.ApproxSimple))
{
foreach (CvSeq <CvPoint> c in scanner)
{
CvMoments mom = new CvMoments(c, false);
if (c.ElemSize < 2)
{
continue;
}
if (mom.M00 == 0.0)
{
continue;
}
double mx = mom.M10 / mom.M00;
double my = mom.M01 / mom.M00;
mm koko = new mm();
koko.white_x = mx;
koko.white_y = my;
koko.white_kido = mom.M00;
koko.white_dx = delta_xx;
koko.white_dy = delta_yy;
white_area.Add(koko);
stage.WriteLine(String.Format("mx={0:f2} , my={1:f2} , dx={2:f2} , dy={3:f2} , M={4:f2}", mx, my, delta_xx, delta_yy, mom.M00));
}
}
}
Part_img.Clear();
} //pixel移動x
} //pixel移動y
}
if (white_area.Count > 0)
{
double center_x = 0;
double center_y = 0;
double center_dx = 0;
double center_dy = 0;
double kido_sum = 0;
for (int i = 0; i < white_area.Count; i++)
{
kido_sum += white_area[i].white_kido;
center_x += white_area[i].white_x * white_area[i].white_kido;
center_y += white_area[i].white_y * white_area[i].white_kido;
center_dx += white_area[i].white_dx * white_area[i].white_kido;
center_dy += white_area[i].white_dy * white_area[i].white_kido;
}
center_x = center_x / kido_sum;
center_y = center_y / kido_sum;
center_dx = center_dx / kido_sum;
center_dy = center_dy / kido_sum;
int c_o_g_x;
int c_o_g_y;
if (center_x >= 0)
{
c_o_g_x = (int)(center_x + 0.5);
}
else
{
c_o_g_x = (int)(center_x - 0.5);
}
if (center_x >= 0)
{
c_o_g_y = (int)(center_y + 0.5);
}
else
{
c_o_g_y = (int)(center_y - 0.5);
}
int dx_pixel = c_o_g_x - x0;
int dy_pixel = c_o_g_y - y0;
double dx_micron = dx_pixel * 0.265625 / 1000;
double dy_micron = dy_pixel * 0.265625 / 1000;
double now_x2 = mc.GetPoint().X;
double now_y2 = mc.GetPoint().Y;
mc.MovePointXY(now_x2 - dx_micron, now_y2 + dy_micron);//pixelの軸とstageの軸の関係から
mc.Join();
over_dx = center_dx;
over_dy = center_dy;
}
}
private void BeamDetection(string outputfilename, bool isup)
{// beam Detection
int BinarizeThreshold = 60;
int BrightnessThreshold = 4;
int nop = 7;
double dz = 0;
if (isup == true)
{
dz = -0.003;
}
else
{
dz = 0.003;
}
Camera camera = Camera.GetInstance();
MotorControler mc = MotorControler.GetInstance(parameterManager);
Vector3 InitPoint = mc.GetPoint();
Vector3 p = new Vector3();
TracksManager tm = parameterManager.TracksManager;
int mod = parameterManager.ModuleNo;
int pl = parameterManager.PlateNo;
Track myTrack = tm.GetTrack(tm.TrackingIndex);
string[] sp = myTrack.IdString.Split('-');
//string datfileName = string.Format("{0}.dat", System.DateTime.Now.ToString("yyyyMMdd_HHmmss"));
string datfileName = string.Format(@"c:\test\bpm\{0}\{1}-{2}-{3}-{4}-{5}.dat", mod, mod, pl, sp[0], sp[1], System.DateTime.Now.ToString("ddHHmmss"));
BinaryWriter writer = new BinaryWriter(File.Open(datfileName, FileMode.Create));
byte[] bb = new byte[440 * 512 * nop];
string fileName = string.Format("{0}", outputfilename);
StreamWriter twriter = File.CreateText(fileName);
string stlog = "";
List <ImageTaking> LiIT = TakeSequentialImage(0.0, 0.0, dz, nop);
Mat sum = Mat.Zeros(440, 512, MatType.CV_8UC1);
for (int i = 0; i < LiIT.Count; i++)
{
Mat bin = (Mat)DogContrastBinalize(LiIT[i].img, 31, BinarizeThreshold);
Cv2.Add(sum, bin, sum);
//byte[] b = LiIT[i].img.ToBytes();//format is .png
MatOfByte mob = new MatOfByte(LiIT[i].img);
byte[] b = mob.ToArray();
b.CopyTo(bb, 440 * 512 * i);
}
mc.MovePointZ(InitPoint.Z);
mc.Join();
Cv2.Threshold(sum, sum, BrightnessThreshold, 1, ThresholdType.Binary);
//Cv2.FindContoursをつかうとAccessViolationExceptionになる(Release/Debug両方)ので、C-API風に書く
using (CvMemStorage storage = new CvMemStorage())
{
using (CvContourScanner scanner = new CvContourScanner(sum.ToIplImage(), storage, CvContour.SizeOf, ContourRetrieval.Tree, ContourChain.ApproxSimple))
{
//string fileName = string.Format(@"c:\img\{0}.txt",
// System.DateTime.Now.ToString("yyyyMMdd_HHmmss_fff"));
foreach (CvSeq <CvPoint> c in scanner)
{
CvMoments mom = new CvMoments(c, false);
if (c.ElemSize < 2)
{
continue;
}
if (mom.M00 == 0.0)
{
continue;
}
double mx = mom.M10 / mom.M00;
double my = mom.M01 / mom.M00;
stlog += string.Format("{0:F} {1:F}\n", mx, my);
}
}
}
twriter.Write(stlog);
twriter.Close();
writer.Write(bb);
writer.Flush();
writer.Close();
sum *= 255;
sum.ImWrite(String.Format(@"c:\img\{0}_{1}_{2}.bmp",
System.DateTime.Now.ToString("yyyyMMdd_HHmmss"),
(int)(p.X * 1000),
(int)(p.Y * 1000)));
}//BeamDetection
