class_docstr: Random blur input image by Gaussian filter according to given probability.
  
  Args:
      prob(float): The probability to blur the image, default is 0.1.
class_docstr_tok: ["Random","blur","input","image","by","Gaussian","filter","according","to","given","probability",".","Args",":","prob","(","float",")",":","The","probability","to","blur","the","image",",","default","is","0.1","."]
code: def __call__(self, im: np.ndarray):
      if self.prob <= 0:
          n = 0
      elif self.prob >= 1:
          n = 1
      else:
          n = int(1.0 / self.prob)
      if n > 0:
          if np.random.randint(0, n) == 0:
              radius = np.random.randint(3, 10)
              if radius % 2 != 1:
                  radius = radius + 1
              if radius > 9:
                  radius = 9
              im = cv2.GaussianBlur(im, (radius, radius), 0, 0)
  
      return im
  
imports: import random
  from typing import Callable, Union, List, Tuple
  import cv2
  import PIL
  import numpy
  import paddlehub.vision.functional
label_desc: Use image node_id 2 for calling the RandomBlur obj's underlying member method code with example usage: obj.__call__(im) and returns: im