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 __call__(self, im: np.ndarray):
      if self.min_value == self.max_value:
          random_size = self.max_value
      else:
          random_size = int(
              np.random.uniform(self.min_value, self.max_value) + 0.5
          )
      im = F.resize_long(im, random_size, cv2.INTER_LINEAR)
      return im
  
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 2 for calling the ResizeRangeScaling obj's underlying member method code with example usage: obj.__call__(im) and returns: im