class_docstr: The cutout augmentation, as described in https://arxiv.org/abs/1708.04552
class_docstr_tok: ["The","cutout","augmentation",",","as","described","in","https",":","\/\/arxiv.org\/abs\/1708.04552"]
docstr: Args:
      h_range (int or tuple): the height of rectangle to cut.
          If a tuple, will randomly sample from this range [low, high)
      w_range (int or tuple): similar to above
      fill (float): the fill value
docstr_tok: ["Args",":","h_range","(","int","or","tuple",")",":","the","height","of","rectangle","to","cut",".","If","a","tuple",",","will","randomly","sample","from","this","range","[","low",",","high",")","w_range","(","int","or","tuple",")",":","similar","to","above","fill","(","float",")",":","the","fill","value"]
code: def __init__(self, h_range, w_range, fill=0.0):
      """
      Args:
          h_range (int or tuple): the height of rectangle to cut.
              If a tuple, will randomly sample from this range [low, high)
          w_range (int or tuple): similar to above
          fill (float): the fill value
      """
      super(RandomCutout, self).__init__()
      self._init(locals())
  
imports: import numpy
  import cv2
  from ...utils.argtools import shape2d
  from ...utils.develop import log_deprecated
  from .base import ImageAugmentor, ImagePlaceholder
  from .transform import CropTransform, TransformList, ResizeTransform, PhotometricTransform
  from .misc import ResizeShortestEdge
label_desc: Use image node_id 1 to create a new RandomCutout object from inherited base classes: ImageAugmentor with example: obj = RandomCutout(h_range, w_range, fill)