class_docstr: Gaussian blur the image with random window size
class_docstr_tok: ["Gaussian","blur","the","image","with","random","window","size"]
docstr: Args:
      size_range (tuple[int]): Gaussian window size would be 2 * size +
          1, where size is randomly sampled from this [low, high) range.
      sigma_range (tuple[float]): min,max of the sigma value. 0 means
          opencv's default.
      symmetric (bool): whether to use the same size & sigma for x and y.
      max_size (int): deprecated
code: def __init__(
      self,
      size_range=(0, 3),
      sigma_range=(0, 0),
      symmetric=True,
      max_size=None,
  ):
      """
      Args:
          size_range (tuple[int]): Gaussian window size would be 2 * size +
              1, where size is randomly sampled from this [low, high) range.
          sigma_range (tuple[float]): min,max of the sigma value. 0 means
              opencv's default.
          symmetric (bool): whether to use the same size & sigma for x and y.
          max_size (int): deprecated
      """
      super(GaussianBlur, self).__init__()
      if not isinstance(size_range, (list, tuple)):
          size_range = (0, size_range)
      assert isinstance(sigma_range, (list, tuple)), sigma_range
      if max_size is not None:
          log_deprecated(
              "GaussianBlur(max_size=)",
              "Use size_range= instead!",
              "2020-09-01",
          )
          size_range = (0, max_size)
      self._init(locals())
  
imports: import numpy
  import cv2
  from ...utils.develop import log_deprecated
  from .base import PhotometricAugmentor
label_desc: Use image node_id 1 to create a new GaussianBlur object from inherited base classes: PhotometricAugmentor with example: obj = GaussianBlur(size_range, sigma_range, symmetric, max_size)