code: def example_probability_distributions_as_parameters():
      print("Example: Probability Distributions as Parameters")
      import numpy as np
      from imgaug import augmenters as iaa
      from imgaug import parameters as iap
  
      images = np.random.randint(
          0, 255, (16, 128, 128, 3), dtype=np.uint8
      )
  
      # Blur by a value sigma which is sampled from a uniform distribution
      # of range 10.1 <= x < 13.0.
      # The convenience shortcut for this is: GaussianBlur((10.1, 13.0))
      blurer = iaa.GaussianBlur(10 + iap.Uniform(0.1, 3.0))
      images_aug = blurer(images=images)
  
      # Blur by a value sigma which is sampled from a gaussian distribution
      # N(1.0, 0.1), i.e. sample a value that is usually around 1.0.
      # Clip the resulting value so that it never gets below 0.1 or above 3.0.
      blurer = iaa.GaussianBlur(
          iap.Clip(iap.Normal(1.0, 0.1), 0.1, 3.0)
      )
      images_aug = blurer(images=images)
  
file_path: imgaug/checks/check_readme_examples.py
imports: from __future__ import print_function, division
  import functools
label_desc: Use image node_id 15 for calling a global function with example usage: example_probability_distributions_as_parameters() without return types