code: def binary_blur(image, sigma, noise=0.0):
      p = percent_black(image)
      blurred = cv.GaussianBlur(
          image, (0, 0), sigmaX=sigma, borderType=cv.BORDER_REFLECT
      )
      if noise > 0:
          blurred += np.random.randn(*blurred.shape) * noise
      t = np.percentile(blurred, p)
      return np.array(blurred > t, "f")
  
imports: import random
  from random import randint
  import numpy
  import cv2
label_desc: Use image node_id 9 for calling a global function with example usage: binary_blur(image, sigma, noise) and returns: np