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 layout results 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 layout results 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()
          res, _ = self.layout_predictor(img)
          elapse = time.time() - starttime
          logger.info("Predict time: {}".format(elapse))
  
          for item in res:
              item["bbox"] = item["bbox"].tolist()
          all_results.append({"layout": 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 paddlehub
  from tools.infer.utility import base64_to_cv2
  from ppstructure.layout.predict_layout import LayoutPredictor
  from ppstructure.utility import parse_args
  from deploy.hubserving.structure_layout.params import read_params
label_desc: Use image node_id 4 for calling the LayoutPredictor obj's underlying member method code with example usage: obj.predict(images, paths) and returns: all_results