code: def __init__(self, args):
      pre_process_list = [
          {"Resize": {"size": [800, 608]}},
          {
              "NormalizeImage": {
                  "std": [0.229, 0.224, 0.225],
                  "mean": [0.485, 0.456, 0.406],
                  "scale": "1./255.",
                  "order": "hwc",
              }
          },
          {"ToCHWImage": None},
          {"KeepKeys": {"keep_keys": ["image"]}},
      ]
      postprocess_params = {
          "name": "PicoDetPostProcess",
          "layout_dict_path": args.layout_dict_path,
          "score_threshold": args.layout_score_threshold,
          "nms_threshold": args.layout_nms_threshold,
      }
  
      self.preprocess_op = create_operators(pre_process_list)
      self.postprocess_op = build_post_process(postprocess_params)
      (
          self.predictor,
          self.input_tensor,
          self.output_tensors,
          self.config,
      ) = utility.create_predictor(args, "layout", logger)
  
file_path: PaddleOCR/ppstructure/layout/predict_layout.py
imports: import os
  import sys
  import cv2
  import numpy
  import time
  import tools.infer.utility
  from ppocr.data import create_operators, transform
  from ppocr.postprocess import build_post_process
  from ppocr.utils.logging import get_logger
  from ppocr.utils.utility import get_image_file_list, check_and_read
  from ppstructure.utility import parse_args
  from picodet_postprocess import PicoDetPostProcess
label_desc: Use image node_id 1 to create a new LayoutPredictor object from inherited base classes: object with example: obj = LayoutPredictor(args)