class_docstr: Apply defocus transform. See https://arxiv.org/abs/1903.12261.
  
  Args:
      radius ((int, int) or int): range for radius of defocusing.
          If limit is a single int, the range will be [1, limit]. Default: (3, 10).
      alias_blur ((float, float) or float): range for alias_blur of defocusing (sigma of gaussian blur).
          If limit is a single float, the range will be (0, limit). Default: (0.1, 0.5).
      p (float): probability of applying the transform. Default: 0.5.
  
  Targets:
      image
  
  Image types:
      Any
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code: def __init__(
      self,
      radius: ScaleIntType = (3, 10),
      alias_blur: ScaleFloatType = (0.1, 0.5),
      always_apply: bool = False,
      p: float = 0.5,
  ):
      super().__init__(always_apply, p)
      self.radius = to_tuple(radius, low=1)
      self.alias_blur = to_tuple(alias_blur, low=0)
  
      if self.radius[0] <= 0:
          raise ValueError("Parameter radius must be positive")
  
      if self.alias_blur[0] < 0:
          raise ValueError("Parameter alias_blur must be non-negative")
  
imports: import random
  import warnings
  from typing import Any, Dict, List, Sequence, Tuple
  import cv2
  import numpy
  from albumentations import random_utils
  from albumentations.augmentations import functional
  from albumentations.augmentations.blur import functional
  from albumentations.core.transforms_interface import ImageOnlyTransform, ScaleFloatType, ScaleIntType, to_tuple
label_desc: Use image node_id 1 to create a new Defocus object from inherited base classes: ImageOnlyTransform with example: obj = Defocus(radius, alias_blur, always_apply, p)