public static void Calibrate()
{
objectPoints = new MCvPoint3D32f[frames][];
imgPoints = new VectorOfPointF[frames];
rVecs = new Mat[frames];
tVecs = new Mat[frames];
width = 5;
height = 5;
patternSize = new Size(width, height);
var files = Directory.GetFiles(@"--location--");
for (int k = 0; k < frames; k++)
{
grayFrame = CvInvoke.Imread(files[k], ImreadModes.Grayscale);
found = CvInvoke.FindChessboardCorners(grayFrame, patternSize, cornerPoints, CalibCbType.AdaptiveThresh);
if (found)
{
//read more about its use and last 3 arguments
CvInvoke.CornerSubPix(grayFrame, cornerPoints, new Size(11, 11), new Size(-1, -1), new MCvTermCriteria(30, 0.1));
var objectList = new List <MCvPoint3D32f> ();
// populating real world coordinates of the chess board corners
for (int i = 0; i < patternSize.Height; i++)
{
for (int j = 0; j < patternSize.Width; j++)
{
objectList.Add(new MCvPoint3D32f(j * squareSize, i * squareSize, 0.0f));
}
}
objectPoints[k] = objectList.ToArray();
imgPoints[k] = cornerPoints;
}
}
// Calibrate Camera
double error = CalibrateCamera(objectPoints, imgPoints.Select(a => a.ToArray()).ToArray(), grayFrame.Size, cameraMatrix, distCoeffs, CalibType.RationalModel, new MCvTermCriteria(30, 0.1), out rVecs, out tVecs);
// Get Optimal new Camera Matrix
var imgSize = CvInvoke.Imread(files[4], ImreadModes.Grayscale).Size;
Rectangle ROI = new Rectangle();
newMatrix = CvInvoke.GetOptimalNewCameraMatrix(cameraMatrix, distCoeffs, imgSize, 1, imgSize, ref ROI);
Mat dupFrame = grayFrame.Clone();
// Undistort
CvInvoke.Undistort(grayFrame, dupFrame, newMatrix, distCoeffs);
var frame = dupFrame.Clone();
CvInvoke.Imwrite("undistorted.png", frame);
// Region of Interest
//var buffer_im = _frame.ToImage<Bgr, byte> ();
//buffer_im.ROI = ROI;
//Image<Bgr, byte> cropped_im = buffer_im.Copy ();
//cropped_im.Save ("cropped.png");
// Drawing detected chessboard corners
CvInvoke.DrawChessboardCorners(grayFrame, patternSize, cornerPoints, found);
//CvInvoke.Imwrite ("chessboard.png", _frame);
CvInvoke.Imwrite("distorted.png", grayFrame);
Console.WriteLine(MeanError());
}
