public void Run()
{
Mat src = new Mat(FilePath.Image.Girl, ImreadModes.Color);
Mat dst = new Mat(FilePath.Image.Lenna, ImreadModes.Color);
Mat src0 = src.Resize(dst.Size(), 0, 0, InterpolationFlags.Lanczos4);
Mat mask = Mat.Zeros(src0.Size(), MatType.CV_8UC3);
mask.Circle(200, 200, 100, Scalar.White, -1);
Mat blend1 = new Mat();
Mat blend2 = new Mat();
Mat blend3 = new Mat();
Cv2.SeamlessClone(
src0, dst, mask, new Point(260, 270), blend1,
SeamlessCloneMethods.NormalClone);
Cv2.SeamlessClone(
src0, dst, mask, new Point(260, 270), blend2,
SeamlessCloneMethods.MonochromeTransfer);
Cv2.SeamlessClone(
src0, dst, mask, new Point(260, 270), blend3,
SeamlessCloneMethods.MixedClone);
using (new Window("src", src0))
using (new Window("dst", dst))
using (new Window("mask", mask))
using (new Window("blend NormalClone", blend1))
using (new Window("blend MonochromeTransfer", blend2))
using (new Window("blend MixedClone", blend3))
{
Cv2.WaitKey();
}
}
private string OpenCVDeepLearningDetector(string path)
{
// uses emugu library
//https://medium.com/@vinuvish/face-detection-with-opencv-and-deep-learning-90bff9028fa8
string prototextPath = @"./Dnn/deploy.prototxt";
string caffeModelPath = @"./Dnn/res10_300x300_ssd_iter_140000.caffemodel";
// load the model;
var net = CvDnn.ReadNetFromCaffe(prototxt: prototextPath, caffeModel: caffeModelPath);
// get the image
OpenCvSharp.Mat image = Cv2.ImRead(path);
// get the original image size
OpenCvSharp.Size imageSize = image.Size();
// the dnn detector works on a 300x300 image;
// now resize the image for the Dnn dector;
OpenCvSharp.Size size = new OpenCvSharp.Size(299, 299);
image = image.Resize(size);
// set the scalar property to RGB colors, don't know what these values represent.
OpenCvSharp.Scalar mcvScalar = new OpenCvSharp.Scalar(104.0, 177.0, 123.0);
var blob = CvDnn.BlobFromImage(image: image, scaleFactor: 1, size: size, mean: mcvScalar, swapRB: true);
net.SetInput(blob);
OpenCvSharp.Mat detections = net.Forward();
// convert the detected values to a faces object that we can use to
// draw rectangles.
List <ConfidenceRect> Faces = new List <ConfidenceRect>();
//var rows = detections.SizeOfDimension[2];
//Array ans = detections.GetData();
//for (int n = 0; n < rows; n++)
//{
// object confidence = ans.GetValue(0, 0, n, 2);
// object x1 = ans.GetValue(0, 0, n, 3);
// object y1 = ans.GetValue(0, 0, n, 4);
// object x2 = ans.GetValue(0, 0, n, 5);
// object y2 = ans.GetValue(0, 0, n, 6);
// ConfidenceRect cr = new ConfidenceRect(confidence, x1, y1, x2, y2, imageSize);
// if (cr.Confidence > 0)
// {
// Debug.WriteLine($"Confidence {cr.Confidence}");
// }
// if (cr.Confidence > Confidence)
// {
// Faces.Add(cr);
// }
//}
//// convert to a writeableBitmap
//WriteableBitmap writeableBitmap = new WriteableBitmap(ImageSource);
//ImageSource = ConvertWriteableBitmapToBitmapImage(writeableBitmap);
//OnPropertyChanged("ImageSource");
//DrawDnnOnImage?.Invoke(Faces, imageSize);
//return Faces.Count.ToString();
return(null);
}
/// <summary>
/// Eye見て傾き検出
/// </summary>
/// <param name="srcMat"></param>
/// <param name="putMat"></param>
/// <returns></returns>
public Mat PutEllipseEyeMaskOnFace(Mat srcMat, Mat putMat)
{
var grayMat = new Mat();
Cv2.CvtColor(srcMat, grayMat, ColorConversionCodes.BGR2GRAY);
Cv2.EqualizeHist(grayMat, grayMat);
var faces = Cascade.DetectMultiScale(grayMat);
if (faces == null) return srcMat;
var polygons = new List<List<Point>>();
var faceCount = faces.Count(); // O(n)
for (int d = 0; d < faceCount; d++)
{
polygons = new List<List<Point>>();
int x1 = faces[d].X;
int y1 = faces[d].Y;
int width = faces[d].Width;
int height = faces[d].Height;
int x2 = x1 + width;
int y2 = y1 + height;
int pwidth = putMat.Width;
int pheight = putMat.Height;
int srcWidth = srcMat.Width;
int srcHeight = srcMat.Height;
polygons.Add(new List<Point>() {
new Point(x1,y1),
new Point(x2,y1),
new Point(x2,y2),
new Point(x1,y2),
});
var faceSize = new Size(width, height);
//重ねるファイルは少し拡大したほうが良いかな？
/* Mat put0 = putMat[(int)(pwidth * 0.1) ,
(int)(pwidth * 0.9),
(int)(pheight * 0.1),
(int)(pheight * 0.9)]
.Resize(new Size(width, heigh), 0, 0, InterpolationFlags.Lanczos4);
*/
Mat put0 = putMat.Resize(faceSize, 0, 0, InterpolationFlags.Lanczos4);
//真ん中編の色を適当に抽出
// 改良の余地あり（肌色領域の平均取ったり？）
MatOfByte3 mat3 = new MatOfByte3(put0); // cv::Mat_<cv::Vec3b>
var indexer = mat3.GetIndexer();
Vec3b color = indexer[(int)(put0.Width * 0.5), (int)(put0.Height * 0.5)];
//抽出した色で埋める
Mat put1 = new Mat(srcMat.Size(), MatType.CV_8UC3, new Scalar(color.Item0, color.Item1, color.Item2));
//重ねる範囲にコピー
put1[y1, y2, x1, x2] = put0;
Mat put1gray = Mat.Zeros(srcMat.Size(), MatType.CV_8UC1);
put1gray[y1, y2, x1, x2] = grayMat[y1, y2, x1, x2];
var eyes = EyeCascade.DetectMultiScale(put1gray);
/*
Debug.WriteLine(eyes.Count());
var cccc = new Point(eyes[0].X + eyes[0].Width * 0.5, eyes[0].Y + eyes[0].Height * 0.5);
put1gray.Circle(cccc,(int)(eyes[0].Width * 0.5), new Scalar(0, 255, 255));
return put1gray;*/
var eyeCount = eyes.Count();
if (eyeCount >= 2)
{
var eyePpints = new List<Point>();
var orderedEyes = eyes.OrderByDescending(x => x.Width * x.Height).ToArray();
while (true)
{
for (int i = 0; i < 2; i++)
{
eyePpints.Add(new Point(eyes[i].X + eyes[i].Width * 0.5, eyes[i].Y + eyes[i].Height * 0.5));
}
var wrapRect = Cv2.MinAreaRect(eyePpints);
if (Math.Abs(wrapRect.Angle % 180) < 20)
{
var scale = 1.0;
var angle = -wrapRect.Angle % 180;
var eyedx = (eyePpints[0].X + eyePpints[1].X) * 0.5 - wrapRect.Center.X;
var eyedy = (eyePpints[0].Y + eyePpints[1].Y) * 0.5 - wrapRect.Center.Y;
//中心はここ
var center = new Point(
(faces[d].X + faces[d].Width * 0.5) + eyedx,
(faces[d].Y + faces[d].Height * 0.5) + eyedy);
Mat matrix = Cv2.GetRotationMatrix2D(center, angle, scale);
//画像を回転させる
Cv2.WarpAffine(put1, put1, matrix, put1.Size());
var faceAvgWidth = (int)((wrapRect.Size.Width + faceSize.Width) * 0.6);
var rotateRect = new RotatedRect(center, new Size2f(faceAvgWidth, faceSize.Height * 0.9), angle);
Mat mask = Mat.Zeros(srcMat.Size(), MatType.CV_8UC3);
Cv2.Ellipse(mask, rotateRect, new Scalar(255, 255, 255), -1, LineTypes.AntiAlias);
// Cv2.FillPoly(mask, polygons, new Scalar(255, 255, 255));
Cv2.SeamlessClone(put1, srcMat, mask, center, srcMat, SeamlessCloneMethods.NormalClone);
break;
}
else
{
if (orderedEyes.Count() > 2)
{
orderedEyes = orderedEyes.Skip(1).ToArray();
}
else
{
var angle = 0;
//中心はここ
var center = new Point(faces[d].X + faces[d].Width * 0.5, faces[d].Y + faces[d].Height * 0.5);
var rotateRect = new RotatedRect(center, new Size2f(faceSize.Width * 0.8, faceSize.Height * 0.9), angle);
Mat mask = Mat.Zeros(srcMat.Size(), MatType.CV_8UC3);
Cv2.Ellipse(mask, rotateRect, new Scalar(255, 255, 255), -1, LineTypes.AntiAlias);
// Cv2.FillPoly(mask, polygons, new Scalar(255, 255, 255));
Cv2.SeamlessClone(put1, srcMat, mask, center, srcMat, SeamlessCloneMethods.NormalClone);
break;
}
}
}
}
else
{
var angle = 0;
//中心はここ
var center = new Point(faces[d].X + faces[d].Width * 0.5, faces[d].Y + faces[d].Height * 0.5);
var rotateRect = new RotatedRect(center, new Size2f(faceSize.Width * 0.8, faceSize.Height * 0.9), angle);
Mat mask = Mat.Zeros(srcMat.Size(), MatType.CV_8UC3);
Cv2.Ellipse(mask, rotateRect, new Scalar(255, 255, 255), -1, LineTypes.AntiAlias);
// Cv2.FillPoly(mask, polygons, new Scalar(255, 255, 255));
Cv2.SeamlessClone(put1, srcMat, mask, center, srcMat, SeamlessCloneMethods.NormalClone);
}
}
return srcMat;
}
/// <summary>
/// Poisson Image Editing
/// </summary>
/// <param name="srcMat">顔がある方</param>
/// <param name="putMat">重ねる顔</param>
/// <returns></returns>
public Mat PutMaskOnFace(Mat srcMat, Mat putMat)
{
var grayMat = new Mat();
Cv2.CvtColor(srcMat, grayMat, ColorConversionCodes.BGR2GRAY);
Cv2.EqualizeHist(grayMat, grayMat);
var faces = Cascade.DetectMultiScale(grayMat);
if (faces == null) return srcMat;
var binaryMat = new Mat();
int blockSize = 7;
double k = 0.15;
double R = 32;
Binarizer.Sauvola(grayMat, binaryMat, blockSize, k, R);
Cv2.BitwiseNot(binaryMat, binaryMat);
var polygons = new List<List<Point>>();
var faceCount = faces.Count(); // O(n)
for (int d = 0; d < faceCount; d++)
{
polygons = new List<List<Point>>();
int x1 = faces[d].X;
int y1 = faces[d].Y;
int width = faces[d].Width;
int heigh = faces[d].Height;
int x2 = x1 + width;
int y2 = y1 + heigh;
polygons.Add(new List<Point>() {
new Point(x1,y1),
new Point(x2,y1),
new Point(x2,y2),
new Point(x1,y2),
});
var pwidth = putMat.Width;
var pheight = putMat.Height;
//重ねるファイルは少し拡大したほうが良いかな？
/* Mat put0 = putMat[(int)(pwidth * 0.1) ,
(int)(pwidth * 0.9),
(int)(pheight * 0.1),
(int)(pheight * 0.9)]
.Resize(new Size(width, heigh), 0, 0, InterpolationFlags.Lanczos4);
*/
Mat put0 = putMat.Resize(new Size(width, heigh), 0, 0, InterpolationFlags.Lanczos4);
//真ん中編の色を適当に抽出
// 改良の余地あり（肌色領域の平均取ったり？）
MatOfByte3 mat3 = new MatOfByte3(put0); // cv::Mat_<cv::Vec3b>
var indexer = mat3.GetIndexer();
Vec3b color = indexer[(int)(put0.Width * 0.5), (int)(put0.Height * 0.5)];
//抽出した色で埋める
Mat put1 = new Mat(srcMat.Size(), MatType.CV_8UC3, new Scalar(color.Item0, color.Item1, color.Item2));
//重ねる範囲にコピー
put1[y1, y2, x1, x2] = put0;
Mat mask = Mat.Zeros(srcMat.Size(), MatType.CV_8UC3);
Cv2.FillPoly(mask, polygons, new Scalar(255, 255, 255));
//中心はここ
var center = new Point(faces[d].X + faces[d].Width * 0.5, faces[d].Y + faces[d].Height * 0.5);
Cv2.SeamlessClone(put1, srcMat, mask, center, srcMat, SeamlessCloneMethods.NormalClone);
}
return srcMat;
}
public Mat PutEllipseMaskOnFace2(Mat srcMat, Mat putMat)
{
var grayMat = new Mat();
Cv2.CvtColor(srcMat, grayMat, ColorConversionCodes.BGR2GRAY);
Cv2.EqualizeHist(grayMat, grayMat);
var faces = Cascade.DetectMultiScale(grayMat);
if (faces == null) return srcMat;
var binaryMat = new Mat();
// binaryMat = ColorExtractor.ExtractMask(srcMat,ColorConversionCodes.BGR2HSV,ColorVariation.Skin);
// return binaryMat;
int blockSize = 7;
double k = 1.5;
double R = 100;
Binarizer.Sauvola(grayMat, binaryMat, blockSize, k, R);
Cv2.BitwiseNot(binaryMat, binaryMat);
return binaryMat;
var polygons = new List<List<Point>>();
var faceCount = faces.Count(); // O(n)
for (int d = 0; d < faceCount; d++)
{
polygons = new List<List<Point>>();
int x1 = faces[d].X;
int y1 = faces[d].Y;
int width = faces[d].Width;
int height = faces[d].Height;
int x2 = x1 + width;
int y2 = y1 + height;
int pwidth = putMat.Width;
int pheight = putMat.Height;
int srcWidth = srcMat.Width;
int srcHeight = srcMat.Height;
polygons.Add(new List<Point>() {
new Point(x1,y1),
new Point(x2,y1),
new Point(x2,y2),
new Point(x1,y2),
});
// f = fixed
/* int fx1 = (int)(x1 - width * 0.01);
fx1 = fx1 > 0 ? fx1 : 0;
int fx2 = (int)(x2 + width * 0.01);
fx2 = fx2 < srcWidth ? fx2 : srcWidth;
int fy1 = (int)(y1 - height * 0.01);
fy1 = fy1 > 0 ? fy1 : 0;
int fy2 = (int)(y2 + height * 0.01);
fy2 = fy2 < srcHeight ? fy2 : srcHeight;
*/
int fx1 = (int)(x1 + width * 0.1);
int fx2 = (int)(x2 - width * 0.1);
int fy1 = (int)(y1 + height * 0.1);
int fy2 = (int)(y2 - height * 0.1);
int fwidth = x2 - x1;
int fheight = y2 - y1;
var faceSize = new Size(fwidth, fheight);
//重ねるファイルは少し拡大したほうが良いかな？
/* Mat put0 = putMat[(int)(pwidth * 0.1) ,
(int)(pwidth * 0.9),
(int)(pheight * 0.1),
(int)(pheight * 0.9)]
.Resize(new Size(width, heigh), 0, 0, InterpolationFlags.Lanczos4);
*/
Mat put0 = putMat.Resize(faceSize, 0, 0, InterpolationFlags.Lanczos4);
//真ん中編の色を適当に抽出
// 改良の余地あり（肌色領域の平均取ったり？）
MatOfByte3 mat3 = new MatOfByte3(put0); // cv::Mat_<cv::Vec3b>
var indexer = mat3.GetIndexer();
Vec3b color = indexer[(int)(put0.Width * 0.5), (int)(put0.Height * 0.5)];
//抽出した色で埋める
Mat put1 = new Mat(srcMat.Size(), MatType.CV_8UC3, new Scalar(color.Item0, color.Item1, color.Item2));
//重ねる範囲にコピー
put1[y1, y2, x1, x2] = put0;
Mat mask = Mat.Zeros(srcMat.Size(), MatType.CV_8UC3);
//中心はここ
var center = new Point(faces[d].X + faces[d].Width * 0.5, faces[d].Y + faces[d].Height * 0.5);
Mat faceAroundMat = Mat.Zeros(srcMat.Size(), MatType.CV_8UC1);
faceAroundMat[fy1, fy2, fx1, fx2] = binaryMat[fy1, fy2, fx1, fx2];
// faceAroundMat[y1, y2, x1, x2] = binaryMat[y1, y2, x1, x2];
//var countours = new
// 単純な輪郭抽出のみでは、傾きがわからない
// 元のAPIが破壊的な関数なので clone http://opencv.jp/opencv-2svn/cpp/imgproc_structural_analysis_and_shape_descriptors.html#cv-findcontours
var contours = faceAroundMat.Clone().FindContoursAsArray(RetrievalModes.List, ContourApproximationModes.ApproxNone);
//要素数が大きい輪郭だけ
var detectedContours = contours.Where(c =>
/*Cv2.ContourArea(c) > Cv2.ContourArea(polygons[0]) * 0.05 &&*/ Cv2.ContourArea(c) < Cv2.ContourArea(polygons[0]) * 0.1);
Mat conMat = Mat.Zeros(srcMat.Size(), MatType.CV_8UC1);
Cv2.DrawContours(conMat, detectedContours, -1, new Scalar(255, 255, 255));
return conMat;
var points = new List<Point>();
foreach (var dc in detectedContours)
{
points.Union(dc);
}
var detectedRotateRect = Cv2.MinAreaRect(points);
float angle =
detectedRotateRect.Angle =
Math.Abs(detectedRotateRect.Angle) > 20 ?
detectedRotateRect.Angle % 20 :
detectedRotateRect.Angle;
float scale = 1.0f;
// 回転
Mat matrix = Cv2.GetRotationMatrix2D(center, angle, scale);
Debug.WriteLine(detectedRotateRect.Angle);
//画像を回転させる
Cv2.WarpAffine(put1, put1, matrix, put1.Size());
var rotateRect = new RotatedRect(center, new Size2f(faceSize.Width, faceSize.Height), detectedRotateRect.Angle);
continue;
Cv2.Ellipse(mask, detectedRotateRect, new Scalar(255, 255, 255), -1, LineTypes.AntiAlias);
// Cv2.FillPoly(mask, polygons, new Scalar(255, 255, 255));
Cv2.SeamlessClone(put1, srcMat, mask, center, srcMat, SeamlessCloneMethods.NormalClone);
}
return srcMat;
}
