number_recognition.py 文件源码

def _estimate_current_anticlockwise_degrees_using_minarearect(self, spot_xy) -> float:
        # Find the minimum area rectangle around the number
        nearby_contour_groups = contour_tools.extract_contour_groups_close_to(
            self.contour_groups, target_point_xy=spot_xy, delta=self._min_pixels_between_contour_groups)
        nearby_contours = [c for grp in nearby_contour_groups for c in grp]
        box = cv2.minAreaRect(np.row_stack(nearby_contours))
        corners_xy = cv2.boxPoints(box).astype(np.int32)
        self._log_contours_on_current_image([corners_xy], name="Minimum area rectangle")

        # Construct a vector which, once correctly rotated, goes from the bottom right corner up & left at 135 degrees
        sorted_corners = sorted(corners_xy, key=lambda pt: np.linalg.norm(spot_xy - pt))
        bottom_right_corner = sorted_corners[0]  # The closest corner to the spot
        adjacent_corners = sorted_corners[1:3]  # The next two closest corners

        unit_vectors_along_box_edge = misc.normalised(adjacent_corners - bottom_right_corner)
        up_left_diagonal = unit_vectors_along_box_edge.sum(axis=0)

        degrees_of_up_left_diagonal = np.rad2deg(np.arctan2(-up_left_diagonal[1], up_left_diagonal[0]))
        return degrees_of_up_left_diagonal - 135