detectAsync method

Future<(VecVec4f, VecF64, VecF64, VecF64)> detectAsync(InputArray image, { VecVec4f? lines, VecF64? width, VecF64? prec, VecF64? nfa, })

Finds lines in the input image.

Parameters

• image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);
• lines A vector of Vec4f elements specifying the beginning and ending point of a line. Where Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly oriented depending on the gradient.
• width Vector of widths of the regions, where the lines are found. E.g. Width of line.
• prec Vector of precisions with which the lines are found.
• nfa Vector containing number of false alarms in the line region, with precision of 10%. The bigger the value, logarithmically better the detection.
  • -1 corresponds to 10 mean false alarms
  • 0 corresponds to 1 mean false alarm
  • 1 corresponds to 0.1 mean false alarms This vector will be calculated only when the objects type is LSD_REFINE_ADV.

https://docs.opencv.org/4.x/db/d73/classcv_1_1LineSegmentDetector.html#acb0cbd33bb3fbcd29a68309850da82fd

Implementation

Future<(VecVec4f lines, VecF64 width, VecF64 prec, VecF64 nfa)> detectAsync(
  InputArray image, {
  VecVec4f? lines,
  VecF64? width,
  VecF64? prec,
  VecF64? nfa,
}) async {
  lines ??= VecVec4f(); // caller is still responsible for dispose-ing these values
  width ??= VecF64();
  prec ??= VecF64();
  nfa ??= VecF64();

  return cvRunAsync0(
    (callback) => cimgproc.cv_LineSegmentDetector_detect(
      ref,
      image.ref,
      lines!.ref,
      width!.ref,
      prec!.ref,
      nfa!.ref,
      callback,
    ),
    (c) {
      final rval = (lines!, width!, prec!, nfa!);
      return c.complete(rval);
    },
  );
}