code: def random_flip(flip_x_chance, flip_y_chance, prng=DEFAULT_PRNG):
      """Construct a transformation randomly containing X/Y flips (or not).
      Args
          flip_x_chance: The chance that the result will contain a flip along the X axis.
          flip_y_chance: The chance that the result will contain a flip along the Y axis.
          prng:          The pseudo-random number generator to use.
      Returns
          a homogeneous 3 by 3 transformation matrix
      """
      flip_x = prng.uniform(0, 1) < flip_x_chance
      flip_y = prng.uniform(0, 1) < flip_y_chance
      # 1 - 2 * bool gives 1 for False and -1 for True.
      return scaling((1 - 2 * flip_x, 1 - 2 * flip_y))
  
file_path: ImageAI/imageai_tf_deprecated/Detection/keras_retinanet/utils/transform.py
imports: import numpy
label_desc: Use image node_id 12 for calling a global function with example usage: random_flip(flip_x_chance, flip_y_chance, prng) and returns: scaling