public void Bitwise()
{
const int count = 256;
var random = new Random(0);
var array1 = Enumerable.Range(0, count).Select(i => (byte)i).OrderBy(_ => random.Next()).ToArray();
var array2 = Enumerable.Range(0, count).Select(i => (byte)i).OrderBy(_ => random.Next()).ToArray();
using var mat1 = new Mat(count, 1, MatType.CV_8UC1, array1);
using var mat2 = new Mat(count, 1, MatType.CV_8UC1, array2);
using var and = new Mat();
using var or = new Mat();
using var xor = new Mat();
using var not = new Mat();
Cv2.BitwiseAnd(mat1, mat2, and);
Cv2.BitwiseOr(mat1, mat2, or);
Cv2.BitwiseXor(mat1, mat2, xor);
Cv2.BitwiseNot(mat1, not);
for (int i = 0; i < count; i++)
{
Assert.Equal((byte)(array1[i] & array2[i]), and.Get <byte>(i));
Assert.Equal((byte)(array1[i] | array2[i]), or.Get <byte>(i));
Assert.Equal((byte)(array1[i] ^ array2[i]), xor.Get <byte>(i));
Assert.Equal((byte)(~array1[i]), not.Get <byte>(i));
}
}
public IplImage BitwiseMat(IplImage src)
{
Mat Input1 = new Mat(src);
Mat Input2 = new Mat(this.Binary(src, 150));
Mat bitwise = new Mat();
Window win_src1 = new Window("src1", WindowMode.StretchImage, Input1);
Window win_src2 = new Window("src2", WindowMode.StretchImage, Input2);
Cv2.BitwiseNot(Input1, bitwise);
Window win_Not = new Window("BitwiseNot", WindowMode.StretchImage, bitwise);
Cv2.BitwiseAnd(Input1, Input2.CvtColor(ColorConversion.GrayToBgr), bitwise);
Window win_And = new Window("BitwiseAnd", WindowMode.StretchImage, bitwise);
Cv2.BitwiseOr(Input1, Input2.CvtColor(ColorConversion.GrayToBgr), bitwise);
Window win_Or = new Window("BitwiseOr", WindowMode.StretchImage, bitwise);
Cv2.BitwiseXor(Input1, Input2.CvtColor(ColorConversion.GrayToBgr), bitwise);
Window win_Xor = new Window("BitwiseXor", WindowMode.StretchImage, bitwise);
//IplImage 형식//
//Cv.Not();
//Cv.And();
//Cv.Or();
//Cv.Xor();
//IplImage 형식//
return(Input2.ToIplImage());
}
public void Apply(Mat src)
{
using (ResourceTracker t = new ResourceTracker())
{
Stopwatch sw = new Stopwatch();
sw.Start();
Size srcSize = src.Size();
//todo: 只对脸部进行亮肤https://blog.csdn.net/cnbloger/article/details/77949949
//https://blog.csdn.net/skyqsdyy/article/details/89467143
//todo: 对src进行美颜、瘦脸、亮肤等。只要控制在一帧50ms之内即可。
Mat matMask = t.NewMat(srcSize, MatType.CV_8UC1, new Scalar(0));
RenderGreenScreenMask(src, matMask);
//the area is by integer instead of double, so that it can improve the performance of comparision of areas
int minBlockArea = (int)(srcSize.Width * srcSize.Height * this.MinBlockPercent);
var contoursExternalForeground = Cv2.FindContoursAsArray(matMask, RetrievalModes.External, ContourApproximationModes.ApproxNone)
.Select(c => new { contour = c, Area = (int)Cv2.ContourArea(c) })
.Where(c => c.Area >= minBlockArea)
.OrderByDescending(c => c.Area).Take(5).Select(c => c.contour);
//contoursExternalForeground = contoursExternalForeground.Select(c=>Cv2.ApproxPolyDP(c,0.5,true));
//a new Mat used for rendering the selected Contours
var matMaskForeground = t.NewMat(srcSize, MatType.CV_8UC1, new Scalar(0));
//thickness: -1 means filling the inner space
matMaskForeground.DrawContours(contoursExternalForeground, -1, new Scalar(255),
thickness: -1);
//matInternalHollow is the inner Hollow parts of body part.
var matInternalHollow = t.NewMat(srcSize, MatType.CV_8UC1, new Scalar(0));
Cv2.BitwiseXor(matMaskForeground, matMask, matInternalHollow);
int minHollowArea = (int)(minBlockArea * 0.5);//the lower size limitation of InternalHollow is less than minBlockArea, because InternalHollows are smaller
//find the Contours of Internal Hollow
var contoursInternalHollow = Cv2.FindContoursAsArray(matInternalHollow, RetrievalModes.External, ContourApproximationModes.ApproxNone)
.Select(c => new { contour = c, Area = Cv2.ContourArea(c) })
.Where(c => c.Area >= minHollowArea)
.OrderByDescending(c => c.Area).Take(10).Select(c => c.contour);
//draw hollows
foreach (var c in contoursInternalHollow)
{
matMaskForeground.FillConvexPoly(c, new Scalar(0));
}
var element = t.T(Cv2.GetStructuringElement(MorphShapes.Cross, new Size(3, 3)));
//smooth the edge of matMaskForeground
Cv2.MorphologyEx(matMaskForeground, matMaskForeground, MorphTypes.Close,
element, iterations: 6);
Cv2.GaussianBlur(matMaskForeground, matMaskForeground, new Size(3, 3), 0, 0);
var foreground = t.NewMat(src.Size(), MatType.CV_8UC4, new Scalar(0));
ZackCVHelper.AddAlphaChannel(src, foreground, matMaskForeground);
//resize the _backgroundImage to the same size of src
Cv2.Resize(_backgroundImage, src, src.Size());
//draw foreground(people) on the backgroundimage
ZackCVHelper.DrawOverlay(src, foreground);
Debug.WriteLine($"5:{sw.ElapsedMilliseconds}");
}
}
public Mat Process(Mat frame)
{
mFrame = frame;
Size blurWinSize = new Size(mBlurWinWidth, mBlurWinHeight);
mFrame.Blur(blurWinSize);
var reshaped = mFrame.Reshape(cn: 3, rows: mFrame.Rows * mFrame.Cols);
var samples = new Mat();
reshaped.ConvertTo(samples, MatType.CV_32FC3);
var bestLabels = new Mat();
var centers = new Mat();
Cv2.Kmeans(samples,
mClustNum,
bestLabels,
new TermCriteria(type: CriteriaType.Eps | CriteriaType.MaxIter, maxCount: 10, epsilon: 1.0),
3,
KMeansFlags.PpCenters,
centers);
//This is not optimal solution, but it works in this case.
Mat clusteredImage = new Mat(mFrame.Rows, mFrame.Cols, mFrame.Type());
for (var size = 0; size < mFrame.Cols * mFrame.Rows; size++)
{
var clusterIndex = bestLabels.At <int>(0, size);
var newPixel = new Vec3b
{
Item0 = (byte)(centers.At <float>(clusterIndex, 0)), // B
Item1 = (byte)(centers.At <float>(clusterIndex, 1)), // G
Item2 = (byte)(centers.At <float>(clusterIndex, 2)) // R
};
clusteredImage.Set(size / mFrame.Cols, size % mFrame.Cols, newPixel);
}
mFrame = clusteredImage;
Mat gray = mFrame.CvtColor(ColorConversionCodes.BGR2GRAY);
Mat thresh = gray.Threshold(140, 255, ThresholdTypes.Otsu);
Mat erode = thresh.Erode(new Mat());
Mat dilate = erode.Dilate(new Mat());
Mat morph = new Mat();
Cv2.BitwiseXor(erode, dilate, morph);
return(morph);
}
//static Mat pre_Prosessing()
//{
// Mat fdfdfd= new Mat();
// return fdfdfd; 이미지와 배열을 리턴해줘야한다.
//}//전처리하는부분
static void Main(string[] args)
{
Mat src = Cv2.ImRead("./samples2/209.bmp");
Mat gray = new Mat(src.Size(), MatType.CV_8UC1);
Mat binary = new Mat(src.Size(), MatType.CV_8UC1);
Mat dst = src.Clone();
Mat rotate = new Mat();
Mat Roi = new Mat();
double angle = default;
Point[][] contours;
HierarchyIndex[] hier;
Mat kernel = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
Cv2.CvtColor(src, gray, ColorConversionCodes.BGR2GRAY);
Cv2.Threshold(gray, binary, 40, 255, ThresholdTypes.Binary);
Cv2.ImShow("aa", binary);
// 존좋탱
//Point[][] contour;
//HierarchyIndex[] hieracy;
//Cv2.FindContours(binary, out contour, out hieracy, RetrievalModes.CComp, ContourApproximationModes.ApproxSimple);
//Cv2.DrawContours(src, contour, -1, new Scalar(0, 0, 255), 3);
//Cv2.ImShow("cc", src);
// 진우탱 : 레이블을 계산 - 2개 초과이면 불량품
Mat ds = gray.Clone();
Mat noise = new Mat();
Cv2.Threshold(ds, ds, 195, 255, ThresholdTypes.Binary);
Cv2.BitwiseXor(binary, ds, noise);
Cv2.BitwiseXor(noise, ds, noise);
Cv2.ImShow("noise", noise);
Point[][] contour;
HierarchyIndex[] hieracy;
Cv2.FindContours(ds, out contour, out hieracy, RetrievalModes.CComp, ContourApproximationModes.ApproxNone);
Cv2.DrawContours(src, contour, -1, new Scalar(0, 0, 255), 3);
Cv2.ImShow("linecheck", src);
Console.WriteLine("개수 : " + contour.Length);
if (contour.Length > 2)
{
Console.WriteLine("불량품");
}
else
{
Console.WriteLine("양품");
}
//Cv2.ImShow("bb", binary - gray);
//Cv2.MorphologyEx(binary, binary, MorphTypes.Close, kernel, new Point(-1, -1), 5);
//Cv2.MorphologyEx(binary, binary, MorphTypes.Erode, kernel, new Point(-1, -1), 20);
//Cv2.MorphologyEx(binary, binary, MorphTypes.Dilate, kernel, new Point(-1, -1), 20);
//Cv2.FindContours(binary, out contours, out hier, RetrievalModes.External, ContourApproximationModes.ApproxTC89KCOS);
//Point[] point_rect = new Point[4];
//for (int i = 0; i < contours.Length; i++)
//{
// double perimeter = Cv2.ArcLength(contours[i], true);
// double epsilon = perimeter * 0.04;
// Point[] approx = Cv2.ApproxPolyDP(contours[i], epsilon, true);
// Point[][] draw_approx = new Point[][] { approx };
// // Cv2.DrawContours(dst, contours, -1, new Scalar(0, 0, 255), 2, LineTypes.AntiAlias);
// Cv2.DrawContours(dst, draw_approx, -1, new Scalar(255, 0, 0), 2, LineTypes.AntiAlias);
// // 좌표를 표시하는 부분
// for (int j = 0; j < approx.Length; j++)
// {
// Cv2.Circle(dst, approx[j], 1, new Scalar(0, 0, 255), 3);
// point_rect[j] = approx[j];
// Console.WriteLine(point_rect[j]);
// }
//}
////ROI를 검출하는 로직 x의 min, max 과 y의 min,max 찾기
//int max_x = 0;
//int min_x = int.MaxValue;
//int max_y = 0;
//int min_y = int.MaxValue;
//angle = calculate_angle(point_rect);
//Roi = make_ROI(dst, min_y, max_y, min_x, max_x, point_rect);
//rotate = Rotate_rect(Roi, angle);
//Console.WriteLine(angle);
//Cv2.ImShow("src", src);
//Cv2.ImShow("binary", binary);
//Cv2.ImShow("dst", dst);
//Cv2.ImShow("Roi", Roi);
//Cv2.ImShow("Rotate", rotate);
Cv2.WaitKey(0);
Cv2.DestroyAllWindows();
}
