code: def __call__(self, data):
      img = data["image"]
  
      h, w = img.shape[0:2]
      random_scale = np.array([0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3])
      scale = (np.random.choice(random_scale) * self.short_size) / min(
          h, w
      )
      img, factor_h, factor_w = self.scale_aligned(img, scale)
  
      data["scale_factor"] = (factor_w, factor_h)
      data["image"] = img
      return data
  
imports: import os
  import cv2
  import random
  import pyclipper
  import paddle
  import numpy
  from ppocr.utils.utility import check_install
  import scipy.io
  from PIL import Image
  import paddle.vision.transforms
label_desc: Use image node_id 3 for calling the RandomScale obj's underlying member method code with example usage: obj.__call__(data) and returns: data