class_docstr: Flip/mirror input images vertically.
  
  .. note::
  
      The default value for the probability is ``0.0``.
      So, to flip *all* input images use ``Flipud(1.0)`` and *not* just
      ``Flipud()``.
  
  **Supported dtypes**:
  
  See :func:`~imgaug.augmenters.flip.flipud`.
  
  Parameters
  ----------
  p : number or imgaug.parameters.StochasticParameter, optional
      Probability of each image to get flipped.
  
  seed : None or int or imgaug.random.RNG or numpy.random.Generator or numpy.random.BitGenerator or numpy.random.SeedSequence or numpy.random.RandomState, optional
      See :func:`~imgaug.augmenters.meta.Augmenter.__init__`.
  
  name : None or str, optional
      See :func:`~imgaug.augmenters.meta.Augmenter.__init__`.
  
  random_state : None or int or imgaug.random.RNG or numpy.random.Generator or numpy.random.BitGenerator or numpy.random.SeedSequence or numpy.random.RandomState, optional
      Old name for parameter `seed`.
      Its usage will not yet cause a deprecation warning,
      but it is still recommended to use `seed` now.
      Outdated since 0.4.0.
  
  deterministic : bool, optional
      Deprecated since 0.4.0.
      See method ``to_deterministic()`` for an alternative and for
      details about what the "deterministic mode" actually does.
  
  Examples
  --------
  >>> import imgaug.augmenters as iaa
  >>> aug = iaa.Flipud(0.5)
  
  Flip ``50`` percent of all images vertically.
  
  >>> aug = iaa.Flipud(1.0)
  
  Flip all images vertically.
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code: def __init__(
      self,
      p=1,
      seed=None,
      name=None,
      random_state="deprecated",
      deterministic="deprecated",
  ):
      super(Flipud, self).__init__(
          seed=seed,
          name=name,
          random_state=random_state,
          deterministic=deterministic,
      )
      self.p = iap.handle_probability_param(p, "p")
  
imports: from __future__ import print_function, division, absolute_import
  import numpy
  import cv2
  import six.moves
  from imgaug.imgaug import _normalize_cv2_input_arr_
  from .None import meta
  from ..None import parameters
  from ..None import dtypes
label_desc: Use image node_id 1 to create a new Flipud object from inherited base classes: meta with example: obj = Flipud(p, seed, name, random_state, deterministic)