new_contents: from dataset import PASCAL_VOC_2006
  from storage import datastore
  from extractor import SIFT_SIFT_Extractor
  from transforms import PCA_Transform, GMMUniversalVocabulary
  
  COMPLETE = True
  
  voc2006 = PASCAL_VOC_2006('/home/ipl/datasets/VOCdevkit/VOC2006')
  temp_storage = datastore('/home/ipl/datastores/exp-linux-voc2006-uni-vocab')
  feature_extractor = SIFT_SIFT_Extractor(temp_storage)
  
  if COMPLETE:
      for t, des in feature_extractor.extract(voc2006, 'train'):
          print t['img_id']
      for t, des in feature_extractor.extract(voc2006, 'test'):
          print t['img_id']
  
  pca_t = PCA_Transform(temp_storage, 50)
  pca_t.fit(feature_extractor.extract(voc2006, 'train'))
  
  if COMPLETE:
      for t, des in pca_t.transform(feature_extractor.extract(voc2006, 'train')):
          print t['img_id']
      for t, des in pca_t.transform(feature_extractor.extract(voc2006, 'test')):
          print t['img_id']
  
  uni_vocab = GMMUniversalVocabulary(temp_storage, n_components=128, covariance_type='diag')
  uni_vocab.fit(pca_t.transform(feature_extractor.extract(voc2006, 'train')), test=True)
  
subject: add linux sample version