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","."]
code: def _augment(self, img, _):
      img = img.astype("float32")
      if self.all_channel:
          minimum = np.min(img)
          maximum = np.max(img)
      else:
          minimum = np.min(img, axis=(0, 1), keepdims=True)
          maximum = np.max(img, axis=(0, 1), keepdims=True)
      img = (self.max - self.min) * (img - minimum) / (
          maximum - minimum
      ) + self.min
      return img
  
imports: import numpy
  import cv2
  from ...utils.develop import log_deprecated
  from .base import PhotometricAugmentor
label_desc: Use image node_id 2 for calling the MinMaxNormalize obj's underlying member method code with example usage: obj._augment(img, _) and returns: img