text: import asyncio
  from argparse import ArgumentParser
  
  import numpy as np
  
  from mmdet.apis import (async_inference_detector, inference_detector,
                          init_detector, show_result_pyplot)
  
  
  def parse_args():
      parser = ArgumentParser()
      parser.add_argument('img', help='Image file')
      parser.add_argument('config', help='Config file')
      parser.add_argument('checkpoint', help='Checkpoint file')
      parser.add_argument('--device', default='cuda:0', help='Device used for inference')
      parser.add_argument(
          '--score-thr', type=float, default=0.3, help='bbox score threshold')
      parser.add_argument(
          '--async-test',
          action='store_true',
          help='whether to set async options for async inference.')
      args = parser.parse_args()
      return args
  
  
  def main(args):
      # build the model from a config file and a checkpoint file
      model = init_detector(args.config, args.checkpoint, device=args.device)
      # test a single image
      result = inference_detector(model, args.img)
      # show the results
      show_result_pyplot(model, args.img, result, score_thr=args.score_thr)
  
  
  async def async_main(args):
      # build the model from a config file and a checkpoint file
      model = init_detector(args.config, args.checkpoint, device=args.device)
      # test a single image
      tasks = asyncio.create_task(async_inference_detector(model, args.img))
      result = await asyncio.gather(tasks)
      # show the results
      show_result_pyplot(model, args.img, result[0], score_thr=args.score_thr)
  
  
  if __name__ == '__main__':
      args = parse_args()
      if args.async_test:
          asyncio.run(async_main(args))
      else:
          main(args)
  