docstr: Get the chinese texts in the predicted images.
  Args:
      images (list(numpy.ndarray)): images data, shape of each is [H, W, C]. If images not paths
      paths (list[str]): The paths of images. If paths not images
  Returns:
      res (list): The result of chinese texts and save path of images.
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code: def predict(self, images=[], paths=[]):
      """
      Get the chinese texts in the predicted images.
      Args:
          images (list(numpy.ndarray)): images data, shape of each is [H, W, C]. If images not paths
          paths (list[str]): The paths of images. If paths not images
      Returns:
          res (list): The result of chinese texts and save path of images.
      """
      if images != [] and isinstance(images, list) and paths == []:
          predicted_data = images
      elif images == [] and isinstance(paths, list) and paths != []:
          predicted_data = self.read_images(paths)
      else:
          raise TypeError(
              "The input data is inconsistent with expectations."
          )
  
      assert (
          predicted_data != []
      ), "There is not any image to be predicted. Please check the input data."
  
      all_results = []
      for img in predicted_data:
          if img is None:
              logger.info("error in loading image")
              all_results.append([])
              continue
          starttime = time.time()
          ser_res, _, elapse = self.ser_predictor(img)
          elapse = time.time() - starttime
          logger.info("Predict time: {}".format(elapse))
          all_results.append(ser_res)
      return all_results
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import sys
  import copy
  import time
  import paddlehub
  from paddlehub.common.logger import logger
  from paddlehub.module.module import moduleinfo, runnable, serving
  import cv2
  import numpy
  import paddlehub
  from tools.infer.utility import base64_to_cv2
  from ppstructure.kie.predict_kie_token_ser import SerPredictor
  from ppstructure.utility import parse_args
  from deploy.hubserving.kie_ser.params import read_params
label_desc: Use image node_id 4 for calling the KIESer obj's underlying member method code with example usage: obj.predict(images, paths) and returns: all_results