text: import argparse
  
  def parse_opts():
      parser = argparse.ArgumentParser()
      parser.add_argument('--base_path', default='', type=str, help='Root path of input videos')
      parser.add_argument('--model', default='', type=str, help='Model file path')
      parser.add_argument('--output_dir', default='.', type=str, help='Output folder path')
      parser.add_argument('--mode', default='score', type=str, help='Mode (score | feature). score outputs class scores. feature outputs features (after global average pooling).')
      parser.add_argument('--model_name', default='resnet', type=str, help='Currently only support resnet')
      parser.add_argument('--model_depth', default=101, type=int, help='Depth of resnet (10 | 18 | 34 | 50 | 101)')
      parser.add_argument('--resnet_shortcut', default='A', type=str, help='Shortcut type of resnet (A | B)')
      parser.add_argument('--wide_resnet_k', default=2, type=int, help='Wide resnet k')
      parser.add_argument('--resnext_cardinality', default=32, type=int, help='ResNeXt cardinality')
      parser.add_argument('--no_cuda', action='store_true', help='If true, cuda is not used.')
      parser.add_argument('--file_list_mode', action='store_true', help='If file list mode is used')
      parser.add_argument("--file_list", type=str, default='')
      parser.add_argument('--no_norm', action='store_true', help='Features should not be normalized to 32 features.')
      parser.set_defaults(verbose=False)
      parser.add_argument('--verbose', action='store_true', help='')
      parser.set_defaults(verbose=False)
  
      args = parser.parse_args()
  
      return args
  
  class create_args():
      def __init__(self, input='input', video_root='./videos', model='', output='output.json',\
                   mode='feature', batch_size=32, n_threads=4, model_name='resnet', model_depth=101,\
                   resnet_shortcut='A', wide_resnet_k=2, resnext_cardinality=32, no_cuda=False, \
                   verbose=False, n_classes=10, sample_size=112, sample_duration=16):
          self.input = input
          self.video_root = video_root
          self.model = model
          self.output = output
          self.mode = mode
          self.batch_size = batch_size
          self.n_threads = n_threads
          self.model_name = model_name
          self.model_depth = model_depth
          self.resnet_shortcut = resnet_shortcut
          self.wide_resnet_k = wide_resnet_k
          self.resnext_cardinality = resnext_cardinality
          self.no_cuda = no_cuda
          self.verbose = verbose
          self.n_classes = n_classes
          self.sample_size=112
          self.sample_duration=16
  