added score fusion script

bob/bio/base/script/fusion_llr.py

+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+# Laurent El Shafey <laurent.el-shafey@idiap.ch>
+# Elie El Khoury <elie.khoury@idiap.ch>
+#Mon 13 Jul 11:55:34 CEST 2015
+#
+# Copyright (C) 2011-2013 Idiap Research Institute, Martigny, Switzerland
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, version 3 of the License.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+"""This script fuses scores from various systems,
+from a score file in four or five column format.
+
+Note: The score file has to contain the exact probe file names as the 3rd (4column) or 4th (5column) column.
+"""
+
+
+
+import bob, os, sys
+import bob.learn.linear
+
+def parse_command_line(command_line_options):
+  """Parse the program options"""
+
+  usage = 'usage: %s [arguments]' % os.path.basename(sys.argv[0])
+
+  import argparse
+  parser = argparse.ArgumentParser(usage=usage, description=__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+
+  # This option is not normally shown to the user...
+  parser.add_argument('--self-test', action = 'store_true', help = argparse.SUPPRESS)
+  parser.add_argument('-s', '--score-development', nargs='*', required = True, help = 'The score file in 4 or 5 column format to train the fusion parameters.')
+  parser.add_argument('-t', '--score-evaluation', nargs='*', required = True, help = 'The score file in 4 or 5 column format to calibrate.')
+  parser.add_argument('-f', '--score-fused-development-file', required = True, help = 'The calibrated development score file in 4 or 5 column format to calibrate.')
+  parser.add_argument('-g', '--score-fused-evaluation-file', required = True, help = 'The calibrated evaluation score file in 4 or 5 column format to calibrate.')
+  parser.add_argument('-p', '--parser', default = '4column', choices = ('4column', '5column'), help = 'The type of the score file.')
+
+  args = parser.parse_args(command_line_options)
+
+  return args
+
+def main(command_line_options = None):
+  """Score Fusion using logistic regresssion"""
+  args = parse_command_line(command_line_options)
+
+  # read data
+  n_systems = len(args.score_development)
+  for i in range(n_systems):
+    if not os.path.isfile(args.score_development[i]): raise IOError("The given score file does not exist")
+  # pythonic way: create inline dictionary "{...}", index with desired value "[...]", execute function "(...)"
+  data = []
+  for i in range(n_systems):
+    data.append({'4column' : bob.measure.load.split_four_column, '5column' : bob.measure.load.split_five_column}[args.parser](args.score_development[i]))
+  import numpy
+
+  data_neg = numpy.vstack([data[k][0] for k in range(n_systems)]).T.copy()
+  data_pos = numpy.vstack([data[k][1] for k in range(n_systems)]).T.copy()
+  trainer = bob.learn.linear.CGLogRegTrainer(0.5, 1e-10, 10000)
+  machine = trainer.train(data_neg, data_pos)
+
+  # fuse development scores
+  data_dev = []
+  for i in range(n_systems):
+    data_dev.append({'4column' : bob.measure.load.four_column, '5column' : bob.measure.load.five_column}[args.parser](args.score_development[i]))
+
+  data_dev2 = []
+  for i in range(n_systems):
+    data_sys = []
+    for (client_id, probe_id, file_id, score) in data_dev[i]:
+      data_sys.append([client_id, probe_id, file_id, score])
+    data_dev2.append(data_sys)
+  data_dev = data_dev2
+  
+  ndata = len(data_dev[0])
+  outf = open(args.score_fused_development_file, 'w')
+  for k in range(ndata):
+    scores = numpy.array([[v[k][-1] for v in data_dev]], dtype=numpy.float64)
+    s_fused = machine.forward(scores)[0,0]  
+    line = " ".join(data_dev[0][k][0:-1]) + " " + str(s_fused) + "\n"
+    outf.write(line)
+
+  # fuse evaluation scores
+  data_eval = []
+  for i in range(n_systems):
+    data_eval.append({'4column' : bob.measure.load.four_column, '5column' : bob.measure.load.five_column}[args.parser](args.score_evaluation[i]))
+    
+  data_eval2 = []
+  for i in range(n_systems):
+    data_sys = []
+    for (client_id, probe_id, file_id, score) in data_eval[i]:
+      data_sys.append([client_id, probe_id, file_id, score])
+    data_eval2.append(data_sys)
+  data_eval = data_eval2
+    
+  ndata = len(data_eval[0])
+  outf = open(args.score_fused_evaluation_file, 'w')
+  for k in range(ndata):
+    scores = numpy.array([[v[k][-1] for v in data_eval]], dtype=numpy.float64)
+    s_fused = machine.forward(scores)[0,0]
+    line = " ".join(data_eval[0][k][0:-1]) + " " + str(s_fused) + "\n"
+    outf.write(line)
+
+  return 0
+
+if __name__ == '__main__':
+  main(sys.argv[1:])

setup.py

@@ -113,6 +113,7 @@ setup(
         'extract.py        = bob.bio.base.script.extract:main',
         'enroll.py         = bob.bio.base.script.enroll:main',
         'score.py          = bob.bio.base.script.score:main',
+        'fusion_llr.py   = bob.bio.base.script.fusion_llr:main',
       ],
 
       'bob.bio.database': [