code: def grid_distortion(
      img: np.ndarray,
      num_steps: int = 10,
      xsteps: Tuple = (),
      ysteps: Tuple = (),
      interpolation: int = cv2.INTER_LINEAR,
      border_mode: int = cv2.BORDER_REFLECT_101,
      value: Optional[ImageColorType] = None,
  ) -> np.ndarray:
      """Perform a grid distortion of an input image.
  
      Reference:
          http://pythology.blogspot.sg/2014/03/interpolation-on-regular-distorted-grid.html
      """
      height, width = img.shape[:2]
  
      x_step = width // num_steps
      xx = np.zeros(width, np.float32)
      prev = 0
      for idx in range(num_steps + 1):
          x = idx * x_step
          start = int(x)
          end = int(x) + x_step
          if end > width:
              end = width
              cur = width
          else:
              cur = prev + x_step * xsteps[idx]
  
          xx[start:end] = np.linspace(prev, cur, end - start)
          prev = cur
  
      y_step = height // num_steps
      yy = np.zeros(height, np.float32)
      prev = 0
      for idx in range(num_steps + 1):
          y = idx * y_step
          start = int(y)
          end = int(y) + y_step
          if end > height:
              end = height
              cur = height
          else:
              cur = prev + y_step * ysteps[idx]
  
          yy[start:end] = np.linspace(prev, cur, end - start)
          prev = cur
  
      map_x, map_y = np.meshgrid(xx, yy)
      map_x = map_x.astype(np.float32)
      map_y = map_y.astype(np.float32)
  
      remap_fn = _maybe_process_in_chunks(
          cv2.remap,
          map1=map_x,
          map2=map_y,
          interpolation=interpolation,
          borderMode=border_mode,
          borderValue=value,
      )
      return remap_fn(img)
  
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 50 for calling a global function with example usage: grid_distortion(img, num_steps, xsteps, ysteps, interpolation, border_mode, value) and returns: remap_fn