kmeansByPointsAsync function

Future<(double, Mat, Mat)> kmeansByPointsAsync(
  1. VecPoint2f pts,
  2. int K,
  3. InputOutputArray bestLabels,
  4. (int, int, double) criteria,
  5. int attempts,
  6. int flags, {
  7. OutputArray? centers,
})

KMeansPoints finds centers of clusters and groups input samples around the clusters.

For further details, please see: https://docs.opencv.org/master/d5/d38/group__core__cluster.html#ga9a34dc06c6ec9460e90860f15bcd2f88

Implementation

Future<(double rval, Mat bestLabels, Mat centers)> kmeansByPointsAsync(
  VecPoint2f pts,
  int K,
  InputOutputArray bestLabels,
  (int, int, double) criteria,
  int attempts,
  int flags, {
  OutputArray? centers,
}) async {
  centers ??= Mat.empty();
  final p = calloc<ffi.Double>();
  return cvRunAsync0(
    (callback) => ccore.cv_kmeans_points(
      pts.ref,
      K,
      bestLabels.ref,
      TermCriteria.fromRecord(criteria).ref,
      attempts,
      flags,
      centers!.ref,
      p,
      callback,
    ),
    (c) {
      final rval = p.value;
      calloc.free(p);
      return c.complete((rval, bestLabels, centers!));
    },
  );
}