text: #!/usr/bin/env python
  
  # --------------------------------------------------------
  # Fast R-CNN
  # Copyright (c) 2015 Microsoft
  # Licensed under The MIT License [see LICENSE for details]
  # Written by Ross Girshick
  # --------------------------------------------------------
  
  """Reval = re-eval. Re-evaluate saved detections."""
  
  import _init_paths
  #from fast_rcnn.test import apply_nms
  #from fast_rcnn.config import cfg
  #from datasets.factory import get_imdb
  from factory import get_imdb
  import cPickle
  import os, sys, argparse
  import numpy as np
  
  def parse_args():
      """
      Parse input arguments
      """
      parser = argparse.ArgumentParser(description='Re-evaluate results')
      parser.add_argument('output_dir', nargs=1, help='results directory',
                          type=str)
      parser.add_argument('--imdb', dest='imdb_name',
                          help='dataset to re-evaluate',
                          default='voc_2007_test', type=str)
      parser.add_argument('--matlab', dest='matlab_eval',
                          help='use matlab for evaluation',
                          action='store_true')
      parser.add_argument('--comp', dest='comp_mode', help='competition mode',
                          action='store_true')
      parser.add_argument('--nms', dest='apply_nms', help='apply nms',
                          action='store_true')
  
      if len(sys.argv) == 1:
          parser.print_help()
          sys.exit(1)
  
      args = parser.parse_args()
      return args
  
  def from_dets(imdb_name, output_dir, args):
      imdb = get_imdb(imdb_name)
      imdb.competition_mode(args.comp_mode)
      imdb.config['matlab_eval'] = args.matlab_eval
   ##   with open(os.path.join(output_dir, 'detections.pkl'), 'rb') as f:
   ##       dets = cPickle.load(f)
  
   ##   if args.apply_nms:
   ##       print 'Applying NMS to all detections'
   ##       nms_dets = apply_nms(dets, cfg.TEST.NMS)
   ##   else:
   ##       nms_dets = dets
  
      print 'Evaluating detections'
  ##imdb.evaluate_detections(nms_dets, output_dir)
      imdb._do_python_eval(output_dir)
  
  if __name__ == '__main__':
      args = parse_args()
  
      output_dir = os.path.abspath(args.output_dir[0])
      imdb_name = args.imdb_name
      from_dets(imdb_name, output_dir, args)