static void Main(string[] args)
{
using (var sourceMat = new Mat("source.jpg"))
using (var destinationMat = new Mat("destination.jpg"))
using (var hc = new CascadeClassifier("HaarCascade.xml"))
using (var facemark = FacemarkLBF.Create())
{
Console.WriteLine("Face detection starting..");
var sourceFaceRects = hc.DetectMultiScale(sourceMat);
if (sourceFaceRects == null || sourceFaceRects.Length == 0)
{
Console.WriteLine($"Source image: No faces detected.");
return;
}
Console.WriteLine($"Source image: detected {sourceFaceRects.Length} faces.");
var destFaceRects = hc.DetectMultiScale(destinationMat);
if (destFaceRects == null || destFaceRects.Length == 0)
{
Console.WriteLine($"Destination image: No faces detected.");
return;
}
Console.WriteLine($"Destination image: detected {destFaceRects.Length} faces.");
facemark.LoadModel("lbfmodel.yaml");
using (var sourceInput = InputArray.Create(sourceFaceRects))
using (var destInput = InputArray.Create(destFaceRects))
{
facemark.Fit(sourceMat, sourceInput, out Point2f[][] sourceLandmarks);
var sourcePoints = sourceLandmarks[0];
facemark.Fit(destinationMat, destInput, out Point2f[][] destLandmarks);
var destPoints = destLandmarks[0];
var triangles = destPoints.Take(60).GetDelaunayTriangles();
var warps = triangles.GetWarps(sourcePoints.Take(60), destPoints.Take(60));
using (var warpedMat = sourceMat.ApplyWarps(destinationMat.Width, destinationMat.Height, warps))
using (var mask = new Mat(destinationMat.Size(), MatType.CV_8UC3))
using (var result = new Mat(destinationMat.Size(), MatType.CV_8UC3))
{
mask.SetTo(0);
var convexHull = Cv2.ConvexHull(destPoints).Select(s => new Point(s.X, s.Y));
Cv2.FillConvexPoly(mask, convexHull, Scalar.White);
var rect = Cv2.BoundingRect(convexHull);
var center = new Point(rect.X + rect.Width / 2, rect.Y + rect.Height / 2);
Cv2.SeamlessClone(warpedMat, destinationMat, mask, center, result, SeamlessCloneMethods.NormalClone);
var blured = result.MedianBlur(5);
blured.SaveImage("result.png");
}
}
}
Console.WriteLine("Done");
}
static void Main(string[] args)
{
//prepare images for averaging
PrepareImages();
//load facemark model
_facemark = FacemarkLBF.Create();
_facemark.LoadModel("lbfmodel.yaml");
//collection for all found facemarks
var allFaceMarks = new List <List <Point2f> >();
//facemark search and save
foreach (var image in Directory.GetFiles(TempDirName))
{
using (var mat = new Mat(image))
{
var facesRects = _cascade.DetectMultiScale(mat);
using (var facesRectsArray = InputArray.Create(facesRects))
{
_facemark.Fit(mat, facesRectsArray, out Point2f[][] landmarks);
// only one face should be
allFaceMarks.Add(landmarks[0].ToList());
}
}
}
//add static points
foreach (var facemarks in allFaceMarks)
{
facemarks.Add(new Point2f(1, 1));
facemarks.Add(new Point2f(1, _outputSize.Height / 2));
facemarks.Add(new Point2f(1, _outputSize.Height - 1));
facemarks.Add(new Point2f(_outputSize.Width - 1, 1));
facemarks.Add(new Point2f(_outputSize.Width / 2, _outputSize.Height - 1));
facemarks.Add(new Point2f(_outputSize.Width - 1, _outputSize.Height / 2));
facemarks.Add(new Point2f(_outputSize.Width - 1, _outputSize.Height - 1));
}
//average Facemarks
var averagePoints = new List <Point2f>();
for (int i = 0; i < 75; i++)
{
float xSum = 0;
float ySum = 0;
for (int j = 0; j < allFaceMarks.Count; j++)
{
var point = allFaceMarks[j][i];
xSum += point.X;
ySum += point.Y;
}
averagePoints.Add(new Point2f(xSum / allFaceMarks.Count, ySum / allFaceMarks.Count));
}
//calculate delaunay triangles
var destinationTriangles = averagePoints.GetDelaunayTriangles();
//create result mat
var outputMat = new Mat(_outputSize, _matTypeDefault);
outputMat.SetTo(0);
// blending coeff
var delta = 1.0 / allFaceMarks.Count;
// warping and blending
var files = Directory.GetFiles(TempDirName);
for (int i = 0; i < files.Length; i++)
{
using (var mat = new Mat(files[i]))
{
var landmarks = allFaceMarks[i];
var warps = destinationTriangles.GetWarps(landmarks, averagePoints);
var warpedImg = mat.ApplyWarps(mat.Width, mat.Height, warps);
Cv2.AddWeighted(outputMat, 1, warpedImg, delta, 0, outputMat);
}
}
//save
outputMat.SaveImage("result.png");
Console.WriteLine("Done.");
}
