def _bounding_quadrangle(self, vertices):
hull_points = cv2.convexHull(vertices, clockwise=False)
# The convex hull of a list of markers must have at least 4 corners, since a
# single marker already has 4 corners. If the convex hull has more than 4
# corners we reduce that number with approximations of the hull.
if len(hull_points) > 4:
new_hull = cv2.approxPolyDP(hull_points, epsilon=1, closed=True)
if new_hull.shape[0] >= 4:
hull_points = new_hull
if len(hull_points) > 4:
curvature = abs(methods.GetAnglesPolyline(hull_points,
closed=True))
most_acute_4_threshold = sorted(curvature)[3]
hull_points = hull_points[curvature <= most_acute_4_threshold]
# Vertices space is flipped in y. We need to change the order of the
# hull_points vertices
hull_points = hull_points[[1, 0, 3, 2], :, :]
# Roll the hull_points vertices until we have the right orientation:
# vertices space has its origin at the image center. Adding 1 to the
# coordinates puts the origin at the top left.
distance_to_top_left = np.sqrt((hull_points[:, :, 0] + 1)**2 +
(hull_points[:, :, 1] + 1)**2)
bot_left_idx = np.argmin(distance_to_top_left) + 1
hull_points = np.roll(hull_points, -bot_left_idx, axis=0)
return hull_points
def _bounding_quadrangle(self, vertices):
# According to OpenCV implementation, cv2.convexHull only accepts arrays with
# 32bit floats (CV_32F) or 32bit signed ints (CV_32S).
# See: https://github.com/opencv/opencv/blob/3.4/modules/imgproc/src/convhull.cpp#L137
# See: https://github.com/pupil-labs/pupil/issues/1544
vertices = np.asarray(vertices, dtype=np.float32)
hull_points = cv2.convexHull(vertices, clockwise=False)
# The convex hull of a list of markers must have at least 4 corners, since a
# single marker already has 4 corners. If the convex hull has more than 4
# corners we reduce that number with approximations of the hull.
if len(hull_points) > 4:
new_hull = cv2.approxPolyDP(hull_points, epsilon=1, closed=True)
if new_hull.shape[0] >= 4:
hull_points = new_hull
if len(hull_points) > 4:
curvature = abs(methods.GetAnglesPolyline(hull_points,
closed=True))
most_acute_4_threshold = sorted(curvature)[3]
hull_points = hull_points[curvature <= most_acute_4_threshold]
# Vertices space is flipped in y. We need to change the order of the
# hull_points vertices
hull_points = hull_points[[1, 0, 3, 2], :, :]
# Roll the hull_points vertices until we have the right orientation:
# vertices space has its origin at the image center. Adding 1 to the
# coordinates puts the origin at the top left.
distance_to_top_left = np.sqrt((hull_points[:, :, 0] + 1)**2 +
(hull_points[:, :, 1] + 1)**2)
bot_left_idx = np.argmin(distance_to_top_left) + 1
hull_points = np.roll(hull_points, -bot_left_idx, axis=0)
return hull_points