code: def main():
      global_config = config["Global"]
  
      # build post process
      post_process_class = build_post_process(
          config["PostProcess"], global_config
      )
  
      # sr transform
      config["Architecture"]["Transform"]["infer_mode"] = True
  
      model = build_model(config["Architecture"])
  
      load_model(config, model)
  
      # 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 in ["SRResize"]:
              op[op_name]["infer_mode"] = True
          elif op_name == "KeepKeys":
              op[op_name]["keep_keys"] = ["img_lr"]
          transforms.append(op)
      global_config["infer_mode"] = True
      ops = create_operators(transforms, global_config)
  
      save_visual_path = config["Global"].get(
          "save_visual", "infer_result/"
      )
      if not os.path.exists(os.path.dirname(save_visual_path)):
          os.makedirs(os.path.dirname(save_visual_path))
  
      model.eval()
      for file in get_image_file_list(config["Global"]["infer_img"]):
          logger.info("infer_img: {}".format(file))
          img = Image.open(file).convert("RGB")
          data = {"image_lr": img}
          batch = transform(data, ops)
          images = np.expand_dims(batch[0], axis=0)
          images = paddle.to_tensor(images)
  
          preds = model(images)
          sr_img = preds["sr_img"][0]
          lr_img = preds["lr_img"][0]
          fm_sr = (
              (sr_img.numpy() * 255).transpose(1, 2, 0).astype(np.uint8)
          )
          fm_lr = (
              (lr_img.numpy() * 255).transpose(1, 2, 0).astype(np.uint8)
          )
          img_name_pure = os.path.split(file)[-1]
          cv2.imwrite(
              "{}/sr_{}".format(save_visual_path, img_name_pure),
              fm_sr[:, :, ::-1],
          )
          logger.info(
              "The visualized image saved in infer_result/sr_{}".format(
                  img_name_pure
              )
          )
  
      logger.info("success!")
  
file_path: PaddleOCR/tools/infer_sr.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import os
  import sys
  import json
  from PIL import Image
  import cv2
  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
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types