text: import pandas as pd
  
  
  N_IDENTITY = 9131  # total number of identities in VGG Face2
  N_IDENTITY_PRETRAIN = 8631  # the number of identities used in training by Caffe
  
  class VGGFaceDatasetHelper(object):
  
      def __init__(self, meta_file):
  
          self.label_dict = self.identity_meta(meta_file)
          self.info_list = []
  
      def generate_dataset_dict_helper_file(self, file):
  
          with open(file, 'r') as f:
              for item, _file in enumerate(f):
                  _file = _file.strip()
                  id = _file.split("/")[1]
  
                  label = self.label_dict[id]
  
                  self.info_list.append({
                      'id': id,
                      'img': _file,
                      'label': label,
                  })
  
      @staticmethod
      def generate_dataset_dict_helper_path(dir):
          pass
  
      @staticmethod
      def identity_meta(file):
  
          df = pd.read_csv(file, sep=',\s+', quoting=csv.QUOTE_ALL, encoding="utf-8")
  
          df["class"] = -1
          df.loc[df["Flag"] == 1, "class"] = range(N_IDENTITY_PRETRAIN)
          df.loc[df["Flag"] == 0, "class"] = range(N_IDENTITY_PRETRAIN, N_IDENTITY)
  
          key = df["Class_ID"].values
          val = df["class"].values
  
          return dict(zip(key, val))
  
      @staticmethod
      def pose_templates(file):
          pass
  
      @staticmethod
      def age_templates(file):
          pass
  
      @staticmethod
      def bb_landmarks_loose(file):
          pass
  
      @staticmethod
      def bb_landmarks(file):
          pass
  
      def check_dataset(self):
          pass