diff --git a/bob/bio/base/script/evaluate.py b/bob/bio/base/script/evaluate.py
index b85f6138b6645d171d9545599d066d7ae18aa068..ddaa01d88574f9f1d5cf9190116f01f7cf3c53a0 100644
--- a/bob/bio/base/script/evaluate.py
+++ b/bob/bio/base/script/evaluate.py
@@ -67,7 +67,7 @@ def command_line_arguments(command_line_parameters):
parser.add_argument('-R', '--roc', help = "If given, ROC curves will be plotted into the given pdf file.")
parser.add_argument('-D', '--det', help = "If given, DET curves will be plotted into the given pdf file.")
parser.add_argument('-C', '--cmc', help = "If given, CMC curves will be plotted into the given pdf file.")
- parser.add_argument('--parser', default = '4column', choices = ('4column', '5column'), help="The style of the resulting score files. The default fits to the usual output of FaceRecLib score files.")
+ parser.add_argument('--parser', default = '4column', choices = ('4column', '5column'), help="The style of the resulting score files. The default fits to the usual output of score files.")
# add verbose option
bob.core.log.add_command_line_option(parser)
diff --git a/bob/bio/base/script/fusion_llr.py b/bob/bio/base/script/fusion_llr.py
index 66c5d2a0c2c93f137fcea1686f37b92666e73e05..5e51ced0337925da64ee1bba825bb6bcf861f7ad 100755
--- a/bob/bio/base/script/fusion_llr.py
+++ b/bob/bio/base/script/fusion_llr.py
@@ -39,11 +39,11 @@ def parse_command_line(command_line_options):
# 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.')
+ parser.add_argument('-d', '--dev-files', required=True, nargs='+', help = "A list of score files of the development set.")
+ parser.add_argument('-e', '--eval-files', nargs='+', help = "A list of score files of the evaluation set; if given it must be the same number of files as the --dev-files.")
+ parser.add_argument('-f', '--score-fused-dev-file', required = True, help = 'The calibrated development score file in 4 or 5 column format to calibrate.')
+ parser.add_argument('-g', '--score-fused-eval-file', 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 style of the resulting score files. The default fits to the usual output of score files.")
args = parser.parse_args(command_line_options)
@@ -54,13 +54,13 @@ def main(command_line_options = None):
args = parse_command_line(command_line_options)
# read data
- n_systems = len(args.score_development)
+ n_systems = len(args.dev_files)
for i in range(n_systems):
- if not os.path.isfile(args.score_development[i]): raise IOError("The given score file does not exist")
+ if not os.path.isfile(args.dev_files[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]))
+ data.append({'4column' : bob.measure.load.split_four_column, '5column' : bob.measure.load.split_five_column}[args.parser](args.dev_files[i]))
import numpy
data_neg = numpy.vstack([data[k][0] for k in range(n_systems)]).T.copy()
@@ -69,20 +69,19 @@ def main(command_line_options = None):
machine = trainer.train(data_neg, data_pos)
# fuse development scores
- data_dev = []
+ gen_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]))
+ gen_data_dev.append({'4column' : bob.measure.load.four_column, '5column' : bob.measure.load.five_column}[args.parser](args.dev_files[i]))
- data_dev2 = []
+ data_dev = []
for i in range(n_systems):
data_sys = []
- for (client_id, probe_id, file_id, score) in data_dev[i]:
+ for (client_id, probe_id, file_id, score) in gen_data_dev[i]:
data_sys.append([client_id, probe_id, file_id, score])
- data_dev2.append(data_sys)
- data_dev = data_dev2
+ data_dev.append(data_sys)
ndata = len(data_dev[0])
- outf = open(args.score_fused_development_file, 'w')
+ outf = open(args.score_fused_dev_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]
@@ -90,25 +89,28 @@ def main(command_line_options = None):
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]))
+ if args.eval_files is not None:
+ if len(args.dev_files) != len(args.eval_files):
+ logger.error("The number of --dev-files (%d) and --eval-files (%d) are not identical", len(args.dev_files), len(args.eval_files))
- 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)
+ gen_data_eval = []
+ for i in range(n_systems):
+ gen_data_eval.append({'4column' : bob.measure.load.four_column, '5column' : bob.measure.load.five_column}[args.parser](args.eval_files[i]))
+
+ data_eval = []
+ for i in range(n_systems):
+ data_sys = []
+ for (client_id, probe_id, file_id, score) in gen_data_eval[i]:
+ data_sys.append([client_id, probe_id, file_id, score])
+ data_eval.append(data_sys)
+
+ ndata = len(data_eval[0])
+ outf = open(args.score_fused_eval_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