code: def bounded_gaussian_noise(shape, sigma, maxdelta):
      n, m = shape[:2]
      deltas = np.random.rand(2, n, m)
      for n, d in enumerate(deltas):
          deltas[n] = cv.GaussianBlur(
              d, (0, 0), sigmaX=sigma, borderType=cv.BORDER_REFLECT
          )
      deltas -= np.amin(deltas)
      deltas /= np.amax(deltas)
      deltas = (2 * deltas - 1) * maxdelta
      return deltas
  
imports: import random
  from random import randint
  import numpy
  import cv2
label_desc: Use image node_id 5 for calling a global function with example usage: bounded_gaussian_noise(shape, sigma, maxdelta) and returns: deltas