code: def main():
      global_config = config["Global"]
  
      # build model
      model = build_model(config["Architecture"])
  
      load_model(config, model)
  
      # build post process
      post_process_class = build_post_process(
          config["PostProcess"], global_config
      )
  
      # create data ops
      transforms = []
      for op in config["Eval"]["dataset"]["transforms"]:
          op_name = list(op)[0]
          if "Label" in op_name:
              continue
          elif op_name == "KeepKeys":
              op[op_name]["keep_keys"] = ["image", "shape"]
          transforms.append(op)
  
      ops = create_operators(transforms, global_config)
  
      save_res_path = config["Global"]["save_res_path"]
      if not os.path.exists(os.path.dirname(save_res_path)):
          os.makedirs(os.path.dirname(save_res_path))
  
      model.eval()
      with open(save_res_path, "wb") as fout:
          for file in get_image_file_list(
              config["Global"]["infer_img"]
          ):
              logger.info("infer_img: {}".format(file))
              with open(file, "rb") as f:
                  img = f.read()
                  data = {"image": img}
              batch = transform(data, ops)
              images = np.expand_dims(batch[0], axis=0)
              shape_list = np.expand_dims(batch[1], axis=0)
              images = paddle.to_tensor(images)
              preds = model(images)
              post_result = post_process_class(preds, shape_list)
              points, strs = post_result["points"], post_result["texts"]
              # write result
              dt_boxes_json = []
              for poly, str in zip(points, strs):
                  tmp_json = {"transcription": str}
                  tmp_json["points"] = poly.tolist()
                  dt_boxes_json.append(tmp_json)
              otstr = file + "\t" + json.dumps(dt_boxes_json) + "\n"
              fout.write(otstr.encode())
              src_img = cv2.imread(file)
              if global_config["infer_visual_type"] == "EN":
                  draw_e2e_res(points, strs, config, src_img, file)
              elif global_config["infer_visual_type"] == "CN":
                  src_img = Image.fromarray(
                      cv2.cvtColor(src_img, cv2.COLOR_BGR2RGB)
                  )
                  draw_e2e_res_for_chinese(
                      src_img,
                      points,
                      strs,
                      config,
                      file,
                      font_path="./doc/fonts/simfang.ttf",
                  )
  
      logger.info("success!")
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import os
  import sys
  import cv2
  import json
  import paddle
  from ppocr.data import create_operators, transform
  from ppocr.modeling.architectures import build_model
  from ppocr.postprocess import build_post_process
  from ppocr.utils.save_load import load_model
  from ppocr.utils.utility import get_image_file_list
  import tools.program
  from PIL import Image, ImageDraw, ImageFont
  import math
label_desc: Use image node_id 3 for calling a global function with example usage: main() without return types