content: from __future__ import division, absolute_import
  from __future__ import print_function, unicode_literals
  import pandas as pd
  from transfer_features import *
  
  
  # process training data
  biz2label = pd.read_csv("rawdata/train.csv", index_col=0)
  photo2biz = pd.read_csv("rawdata/train_photo_to_biz_ids.csv", index_col=0)
  biz2label.sort_index(inplace=True)
  
  for biz_id, biz_label in biz2label.iterrows():
      photo_ids = photo2biz[photo2biz["business_id"] == biz_id].index
      batch_size = len(photo_ids)
      img_list = ['rawdata/train_photos/' + str(id) + '.jpg' for id in photo_ids]
      # pprint(img_list)
      out_file = 'features/inception-21k-global/' + str(biz_id) + '.npy'
      X = get_features(img_list, 'models/inception-21k/Inception', 9)
      np.save(out_file, X)
      print(out_file, 'finished!!')
  
  
  # process test data
  photo2biz = pd.read_csv("rawdata/test_photo_to_biz.csv")
  photo_ids = photo2biz["photo_id"]
  photo_ids = np.unique(photo_ids)
  
  f = open("features/inception-21k-global-test.csv", 'w')
  for photo_id in photo_ids:
      img_list = ['rawdata/test_photos/' + str(photo_id) + '.jpg']
      X = get_features(img_list, 'models/inception-21k/Inception', 9)[0, :]
      f.write(str(photo_id) + ',')
      f.write(",".join(X.astype(str)) + '\n')
      print(photo_id, 'finished!!')
  