class_docstr: Linearly scales the image to the range [min, max].
  
  This augmentor always returns float32 images.
class_docstr_tok: ["Linearly","scales","the","image","to","the","range","[","min",",","max","]",".","This","augmentor","always","returns","float32","images","."]
docstr: Args:
      max (float): The new maximum value
      min (float): The new minimum value
      all_channel (bool): if True, normalize all channels together. else separately.
code: def __init__(self, min=0, max=255, all_channel=True):
      """
      Args:
          max (float): The new maximum value
          min (float): The new minimum value
          all_channel (bool): if True, normalize all channels together. else separately.
      """
      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 MinMaxNormalize object from inherited base classes: PhotometricAugmentor with example: obj = MinMaxNormalize(min, max, all_channel)