class_docstr: Randomly adjust saturation.
  Follows the implementation in `fb.resnet.torch
  <https://github.com/facebook/fb.resnet.torch/blob/master/datasets/transforms.lua#L218>`__.
class_docstr_tok: ["Randomly","adjust","saturation",".","Follows","the","implementation","in","`","fb.resnet.torch","<","https",":","\/\/github.com\/facebook\/fb.resnet.torch\/blob\/master\/datasets\/transforms.lua","#","L218",">","`","__","."]
docstr: Args:
      alpha(float): maximum saturation change.
      rgb (bool): whether input is RGB or BGR.
      clip (bool): clip results to [0,255] even when data type is not uint8.
code: def __init__(self, alpha=0.4, rgb=True, clip=True):
      """
      Args:
          alpha(float): maximum saturation change.
          rgb (bool): whether input is RGB or BGR.
          clip (bool): clip results to [0,255] even when data type is not uint8.
      """
      super().__init__()
      rgb = bool(rgb)
      assert alpha < 1
      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 Saturation object from inherited base classes: PhotometricAugmentor with example: obj = Saturation(alpha, rgb, clip)