public void Do(IVideo video)
{
Mat frame = video.GetNextFrame();
while (frame != null)
{
Cv2.Subtract(frame, _histChessboardModel.BackgroundModel, difference, _histChessboardModel.SquaresMask);
diffWin.ShowImage(difference);
var classif = CalcSquareClassifications(frame);
squareStatesRenderer.Render(classif);
frame = video.GetNextFrame();
}
}
public void Do(IVideo video)
{
Mat frame = video.GetNextFrame();
while (frame != null)
{
frame.ConvertTo(frame, MatType.CV_16SC3);
Cv2.Subtract(frame, background, difference, _histChessboardModel.SquaresMask);
difference = difference.Abs().ToMat();
ShowDiff();
bool[,] squareState = EstimateSquareStates(difference);
stateRenderer.Render(squareState);
frame = video.GetNextFrame();
}
}
// TODO: Optional<Mat>
public HistChessboardModel Do(IVideo video)
{
HistChessboardModel model = null;
Mat frame;
Mat gray = new Mat();
Mat thresh = new Mat();
var corners = new Point2f[4];
var patternSize = new Size(7, 3);
var threshWin = new Window("Adaptive Threshold");
// TODO: each iteration, try different block sizes for the adaptive threshold (height / 4, height / 2, etc)
do
{
frame = video.GetNextFrame();
if (frame != null && frame.Width + frame.Height > 0)
{
Cv2.CvtColor(frame, gray, ColorConversionCodes.BGR2GRAY);
//Cv2.MedianBlur(gray, gray, 5); // Disallows chessboard to be found, because of how it opens/closes corners
Cv2.AdaptiveThreshold(gray, thresh,
maxValue: 255.0,
adaptiveMethod: AdaptiveThresholdTypes.GaussianC,
thresholdType: ThresholdTypes.Binary,
blockSize: (gray.Height / 4) | 1,
c: 0.0);
threshWin.ShowImage(thresh);
var found = Cv2.FindChessboardCorners(thresh, patternSize, out corners,
ChessboardFlags.None); //, ChessboardFlags.AdaptiveThresh | ChessboardFlags.NormalizeImage);
//frame.CopyTo(output);
//Cv2.DrawChessboardCorners(output, patternSize, corners, found);
//if (!found) Console.Out.WriteLine("Chessboard not found :( ");
if (found)
{
var boardPoints = new Point2d[21];
Point2d[] foundPoints = OCVUtil.Point2fTo2d(corners);
for (int c = 0; c < 7; c++)
{
for (int r = 0; r < 3; r++)
{
boardPoints[r * 7 + c] = new Point2d((c + 1.0), (r + 3.0));
}
}
var boardToImageTransform = Cv2.FindHomography(boardPoints, foundPoints);
var imageToBoardTransform =
boardToImageTransform.Inv(); //Cv2.FindHomography(foundPoints, boardPoints);
model = new HistChessboardModel(boardToImageTransform, imageToBoardTransform, frame);
}
}
} while (frame != null && model == null);
return(model);
}
