class_docstr: Scale images by short size.
  Args:
      short_size(float | int): Short size of an image will be scaled to the short_size.
      fixed_ratio(bool): Set whether to zoom according to a fixed ratio. default: True
      do_round(bool): Whether to round up when calculating the zoom ratio. default: False
      backend(str): Choose pillow or cv2 as the graphics processing backend. default: 'pillow'
class_docstr_tok: ["Scale","images","by","short","size",".","Args",":","short_size","(","float","|","int",")",":","Short","size","of","an","image","will","be","scaled","to","the","short_size",".","fixed_ratio","(","bool",")",":","Set","whether","to","zoom","according","to","a","fixed","ratio",".","default",":","True","do_round","(","bool",")",":","Whether","to","round","up","when","calculating","the","zoom","ratio",".","default",":","False","backend","(","str",")",":","Choose","pillow","or","cv2","as","the","graphics","processing","backend",".","default",":","'pillow","'"]
code: def __init__(
      self,
      short_size,
      fixed_ratio=True,
      keep_ratio=None,
      do_round=False,
      backend="pillow",
  ):
      self.short_size = short_size
      assert (fixed_ratio and not keep_ratio) or (
          not fixed_ratio
      ), "fixed_ratio and keep_ratio cannot be true at the same time"
      self.fixed_ratio = fixed_ratio
      self.keep_ratio = keep_ratio
      self.do_round = do_round
  
      assert backend in [
          "pillow",
          "cv2",
      ], "Scale's backend must be pillow or cv2, but get {backend}"
  
      self.backend = backend
  
imports: import cv2
  import numpy
  import imgaug.augmenters
  from keypoint_preprocess import get_affine_transform
  from PIL import Image
label_desc: Use image node_id 1 to create a new ShortSizeScale object from inherited base classes: object with example: obj = ShortSizeScale(short_size, fixed_ratio, keep_ratio, do_round, backend)