generalize prediction averaging

inaFaceAnalyzer/face_classifier.py

@@ -56,6 +56,7 @@
 
 import numpy as np
 import pandas as pd
+import re
 import numbers
 from abc import ABC, abstractmethod
 import tensorflow
@@ -109,16 +110,22 @@ def output_cols(self):
  self._output_cols = list(self(fake_input, False).columns)
  return self._output_cols
 
- def average_results(self, df):
+ def average_results(self, df, groupcol='face_id'):
  if len(df) == 0:
  for c in self.output_cols:
  df[c] = []
 
+ # remove pre-existing averages (in case of re-clustering)
+ for k in df.columns:
+ if re.match('.*_avg$', k):
+ del df[k]
+
+ # columns to be averaged end with _decfunc (decision functions)
  cols = [e for e in df.columns if e.endswith('_decfunc')]
- gbm = df.groupby('face_id')[cols].mean()
+ gbm = df.groupby(groupcol)[cols].mean()
  gbm = self.decisionfunction2labels(gbm)
 
- return df.join(gbm, on='face_id', rsuffix='_avg')
+ return df.join(gbm, on=groupcol, rsuffix='_avg')
 
  # TODO : Keras trick for async READ ?
  # bench execution time : time spent in read/exce . CPU vs GPU