code: def optical_distortion(
      img: np.ndarray,
      k: int = 0,
      dx: int = 0,
      dy: int = 0,
      interpolation: int = cv2.INTER_LINEAR,
      border_mode: int = cv2.BORDER_REFLECT_101,
      value: Optional[ImageColorType] = None,
  ) -> np.ndarray:
      """Barrel / pincushion distortion. Unconventional augment.
  
      Reference:
          |  https://stackoverflow.com/questions/6199636/formulas-for-barrel-pincushion-distortion
          |  https://stackoverflow.com/questions/10364201/image-transformation-in-opencv
          |  https://stackoverflow.com/questions/2477774/correcting-fisheye-distortion-programmatically
          |  http://www.coldvision.io/2017/03/02/advanced-lane-finding-using-opencv/
      """
      height, width = img.shape[:2]
  
      fx = width
      fy = height
  
      cx = width * 0.5 + dx
      cy = height * 0.5 + dy
  
      camera_matrix = np.array(
          [[fx, 0, cx], [0, fy, cy], [0, 0, 1]], dtype=np.float32
      )
  
      distortion = np.array([k, k, 0, 0, 0], dtype=np.float32)
      map1, map2 = cv2.initUndistortRectifyMap(
          camera_matrix, distortion, None, None, (width, height), cv2.CV_32FC1  # type: ignore[attr-defined]
      )
      return cv2.remap(
          img,
          map1,
          map2,
          interpolation=interpolation,
          borderMode=border_mode,
          borderValue=value,
      )
  
imports: import math
  from typing import List, Optional, Sequence, Tuple, Union
  import cv2
  import numpy
  import skimage.transform
  from scipy.ndimage import gaussian_filter
  from albumentations.augmentations.utils import _maybe_process_in_chunks, angle_2pi_range, clipped, preserve_channel_dim, preserve_shape
  from ...None import random_utils
  from ...core.bbox_utils import denormalize_bbox, normalize_bbox
  from ...core.transforms_interface import BoxInternalType, FillValueType, ImageColorType, KeypointInternalType
label_desc: Use image node_id 49 for calling a global function with example usage: optical_distortion(img, k, dx, dy, interpolation, border_mode, value) and returns: cv2