content: import argparse
  import os
  import os.path as osp
  
  import mmcv
  import numpy as np
  
  from mmaction.core import ActivityNetDetection
  
  args = None
  
  
  def cuhk17_top1():
      """Assign label for each proposal with the cuhk17 result, which is the #2
      entry in http://activity-net.org/challenges/2017/evaluation.html."""
      if not osp.exists('cuhk_anet17_pred.json'):
          os.system('wget https://download.openmmlab.com/'
                    'mmaction/localization/cuhk_anet17_pred.json')
      proposal = mmcv.load(args.proposal)
      results = proposal['results']
      cuhk_pred = mmcv.load('cuhk_anet17_pred.json')['results']
  
      def get_topk(preds, k):
          preds.sort(key=lambda x: x['score'])
          return preds[-k:]
  
      for k, v in results.items():
          action_pred = cuhk_pred[k]
          top1 = get_topk(action_pred, 1)
          top1_label = top1[0]['label']
          new_value = []
          for item in v:
              x = dict(label=top1_label)
              x.update(item)
              new_value.append(x)
          results[k] = new_value
      proposal['results'] = results
      mmcv.dump(proposal, args.det_output)
  
  
  cls_funcs = {'cuhk17_top1': cuhk17_top1}
  
  
  def parse_args():
      parser = argparse.ArgumentParser(description='Report detection mAP for'
                                       'ActivityNet proposal file')
      parser.add_argument('--proposal', type=str, help='proposal file')
      parser.add_argument(
          '--gt',
          type=str,
          default='data/ActivityNet/'
          'anet_anno_val.json',
          help='groundtruth file')
      parser.add_argument(
          '--cls',
          type=str,
          default='cuhk17_top1',
          choices=['cuhk17_top1'],
          help='the way to assign label for each '
          'proposal')
      parser.add_argument(
          '--det-output',
          type=str,
          default='det_result.json',
          help='the path to store detection results')
      args = parser.parse_args()
      return args
  
  
  def main():
      global args, cls_funcs
      args = parse_args()
      func = cls_funcs[args.cls]
      func()
      anet_detection = ActivityNetDetection(
          args.gt,
          args.det_output,
          tiou_thresholds=np.linspace(0.5, 0.95, 10),
          verbose=True)
      mAP, average_mAP = anet_detection.evaluate()
      print('[RESULTS] Performance on ActivityNet detection task.\n'
            f'mAP: {mAP}\nAverage-mAP: {average_mAP}')
  
  
  if __name__ == '__main__':
      main()
  