code: def real_sr(
      self,
      image: Union[str, np.ndarray],
      visualization: bool = True,
      output_dir: str = "swinir_m_real_sr_x2_output",
  ) -> np.ndarray:
      if isinstance(image, str):
          _, file_name = os.path.split(image)
          save_name, _ = os.path.splitext(file_name)
          save_name = save_name + "_" + str(int(time.time())) + ".jpg"
          image = cv2.imdecode(
              np.fromfile(image, dtype=np.uint8), cv2.IMREAD_COLOR
          )
      elif isinstance(image, np.ndarray):
          save_name = str(int(time.time())) + ".jpg"
          image = image
      else:
          raise Exception("image should be a str / np.ndarray")
  
      with paddle.no_grad():
          img_input = self.preprocess(image)
          img_input = paddle.to_tensor(
              img_input[None, ...], dtype=paddle.float32
          )
  
          img_output = self.swinir(img_input)
          img_output = img_output.numpy()[0]
          img_output = self.postprocess(img_output)
  
      if visualization:
          if not os.path.isdir(output_dir):
              os.makedirs(output_dir)
          save_path = os.path.join(output_dir, save_name)
          cv2.imwrite(save_path, img_output)
  
      return img_output
  
imports: import argparse
  import base64
  import os
  import time
  from typing import Union
  import cv2
  import numpy
  import paddle
  import paddle.nn
  from .swinir import SwinIR
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
label_desc: Use image node_id 4 for calling the SwinIRMRealSR obj's underlying member method code with example usage: obj.real_sr(image, visualization, output_dir) and returns: img_output