class_docstr: Randomly select a targeted size to resize the image according to given range.
  
  Args:
      min_value(int): The minimum value for targeted size.
      max_value(int): The maximum value for targeted size.
class_docstr_tok: ["Randomly","select","a","targeted","size","to","resize","the","image","according","to","given","range",".","Args",":","min_value","(","int",")",":","The","minimum","value","for","targeted","size",".","max_value","(","int",")",":","The","maximum","value","for","targeted","size","."]
code: def __init__(self, min_value: int = 400, max_value: int = 600):
      if min_value > max_value:
          raise ValueError(
              "min_value must be less than max_value, "
              "but they are {} and {}.".format(min_value, max_value)
          )
      self.min_value = min_value
      self.max_value = max_value
  
imports: import random
  from typing import Callable, Union, List, Tuple
  import cv2
  import PIL
  import numpy
  import paddlehub.vision.functional
label_desc: Use image node_id 1 to create a new ResizeRangeScaling object  with example: obj = ResizeRangeScaling(min_value, max_value)