code: def make_random_superres_mask(
      shape, min_step=2, max_step=4, min_width=1, max_width=3
  ):
      height, width = shape
      mask = np.zeros((height, width), np.float32)
      step_x = np.random.randint(min_step, max_step + 1)
      width_x = np.random.randint(min_width, min(step_x, max_width + 1))
      offset_x = np.random.randint(0, step_x)
  
      step_y = np.random.randint(min_step, max_step + 1)
      width_y = np.random.randint(min_width, min(step_y, max_width + 1))
      offset_y = np.random.randint(0, step_y)
  
      for dy in range(width_y):
          mask[offset_y + dy :: step_y] = 1
      for dx in range(width_x):
          mask[:, offset_x + dx :: step_x] = 1
      return mask[..., None]
  
imports: import math
  import random
  import hashlib
  import logging
  from enum import Enum
  import cv2
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: make_random_superres_mask(shape, min_step, max_step, min_width, max_width) and returns: mask