diff --git a/bob/bio/base/script/verify.py b/bob/bio/base/script/verify.py
index 23e672f7de4375a9f0a2a46a682cc486f0209a6d..d27c2d35e80928e4d431087ff32a364b0541a28a 100644
--- a/bob/bio/base/script/verify.py
+++ b/bob/bio/base/script/verify.py
@@ -206,7 +206,7 @@ def add_jobs(args, submitter):
dependencies = score_deps[group])
concat_deps[group].extend([job_ids['score-%s-B'%group], job_ids['score-%s-C'%group], job_ids['score-%s-D'%group], job_ids['score-%s-Z'%group]])
else:
- concat_deps[group] = []
+ concat_deps[group] = deps[:]
# concatenate results
if not args.skip_concatenation:
@@ -309,48 +309,26 @@ def execute(args):
# enroll the models
elif args.sub_task == 'enroll':
- if args.model_type == 'N':
- tools.enroll(
- args.algorithm,
- args.extractor,
- args.zt_norm,
- indices = tools.indices(fs.model_ids(args.group), None if args.grid is None else args.grid.number_of_enrollment_jobs),
- groups = [args.group],
- types = ['N'],
- allow_missing_files = args.allow_missing_files,
- force = args.force)
-
- else:
- tools.enroll(
- args.algorithm,
- args.extractor,
- args.zt_norm,
- indices = tools.indices(fs.t_model_ids(args.group), None if args.grid is None else args.grid.number_of_enrollment_jobs),
- groups = [args.group],
- types = ['T'],
- allow_missing_files = args.allow_missing_files,
- force = args.force)
+ model_ids = fs.model_ids(args.group) if args.model_type == 'N' else fs.t_model_ids(args.group)
+ tools.enroll(
+ args.algorithm,
+ args.extractor,
+ args.zt_norm,
+ indices = tools.indices(model_ids, None if args.grid is None else args.grid.number_of_enrollment_jobs),
+ groups = [args.group],
+ types = [args.model_type],
+ allow_missing_files = args.allow_missing_files,
+ force = args.force)
# compute scores
elif args.sub_task == 'compute-scores':
- if args.score_type in ['A', 'B']:
- tools.compute_scores(
- args.algorithm,
- args.extractor,
- args.zt_norm,
- indices = tools.indices(fs.model_ids(args.group), None if args.grid is None else args.grid.number_of_scoring_jobs),
- groups = [args.group],
- types = [args.score_type],
- force = args.force,
- allow_missing_files = args.allow_missing_files,
- write_compressed = args.write_compressed_score_files)
-
- elif args.score_type in ['C', 'D']:
+ if args.score_type != 'Z':
+ model_ids = fs.model_ids(args.group) if args.score_type in ('A', 'B') else fs.t_model_ids(args.group)
tools.compute_scores(
args.algorithm,
args.extractor,
args.zt_norm,
- indices = tools.indices(fs.t_model_ids(args.group), None if args.grid is None else args.grid.number_of_scoring_jobs),
+ indices = tools.indices(model_ids, None if args.grid is None else args.grid.number_of_scoring_jobs),
groups = [args.group],
types = [args.score_type],
force = args.force,
diff --git a/bob/bio/base/tools/scoring.py b/bob/bio/base/tools/scoring.py
index 5c249ad09d63acd66cf7d2113bb2ae5da71e1758..faf09422340c54b4dd14bfd1dc8788024427c046 100644
--- a/bob/bio/base/tools/scoring.py
+++ b/bob/bio/base/tools/scoring.py
@@ -13,11 +13,13 @@ from .FileSelector import FileSelector
from .extractor import read_features
from .. import utils
-def _scores(algorithm, reader, model, probes, allow_missing_files):
+def _scores(algorithm, reader, model, probe_objects, allow_missing_files):
"""Compute scores for the given model and a list of probes.
"""
# the file selector object
fs = FileSelector.instance()
+ # get probe files
+ probes = fs.get_paths(probe_objects, 'projected' if algorithm.performs_projection else 'extracted')
# the scores to be computed; initialized with NaN
scores = numpy.ones((1,len(probes)), numpy.float64) * numpy.nan
@@ -135,10 +137,8 @@ def _scores_a(algorithm, reader, model_ids, group, compute_zt_norm, force, write
model = None
else:
model = algorithm.read_model(model_file)
- # get the probe files
- current_probe_files = fs.get_paths(current_probe_objects, 'projected' if algorithm.performs_projection else 'extracted')
# compute scores
- a = _scores(algorithm, reader, model, current_probe_files, allow_missing_files)
+ a = _scores(algorithm, reader, model, current_probe_objects, allow_missing_files)
if compute_zt_norm:
# write A matrix only when you want to compute zt norm afterwards
@@ -155,7 +155,6 @@ def _scores_b(algorithm, reader, model_ids, group, force, allow_missing_files):
# probe files:
z_probe_objects = fs.z_probe_objects(group)
- z_probe_files = fs.get_paths(z_probe_objects, 'projected' if algorithm.performs_projection else 'extracted')
logger.info("- Scoring: computing score matrix B for group '%s'", group)
@@ -171,7 +170,7 @@ def _scores_b(algorithm, reader, model_ids, group, force, allow_missing_files):
model = None
else:
model = algorithm.read_model(model_file)
- b = _scores(algorithm, reader, model, z_probe_files, allow_missing_files)
+ b = _scores(algorithm, reader, model, z_probe_objects, allow_missing_files)
bob.io.base.save(b, score_file, True)
def _scores_c(algorithm, reader, t_model_ids, group, force, allow_missing_files):
@@ -181,7 +180,6 @@ def _scores_c(algorithm, reader, t_model_ids, group, force, allow_missing_files)
# probe files:
probe_objects = fs.probe_objects(group)
- probe_files = fs.get_paths(probe_objects, 'projected' if algorithm.performs_projection else 'extracted')
logger.info("- Scoring: computing score matrix C for group '%s'", group)
@@ -197,7 +195,7 @@ def _scores_c(algorithm, reader, t_model_ids, group, force, allow_missing_files)
t_model = None
else:
t_model = algorithm.read_model(t_model_file)
- c = _scores(algorithm, reader, t_model, probe_files, allow_missing_files)
+ c = _scores(algorithm, reader, t_model, probe_objects, allow_missing_files)
bob.io.base.save(c, score_file, True)
def _scores_d(algorithm, reader, t_model_ids, group, force, allow_missing_files):
@@ -207,7 +205,6 @@ def _scores_d(algorithm, reader, t_model_ids, group, force, allow_missing_files)
# probe files:
z_probe_objects = fs.z_probe_objects(group)
- z_probe_files = fs.get_paths(z_probe_objects, 'projected' if algorithm.performs_projection else 'extracted')
logger.info("- Scoring: computing score matrix D for group '%s'", group)
@@ -227,7 +224,7 @@ def _scores_d(algorithm, reader, t_model_ids, group, force, allow_missing_files)
t_model = None
else:
t_model = algorithm.read_model(t_model_file)
- d = _scores(algorithm, reader, t_model, z_probe_files, allow_missing_files)
+ d = _scores(algorithm, reader, t_model, z_probe_objects, allow_missing_files)
bob.io.base.save(d, score_file, True)
t_client_id = [fs.client_id(t_model_id, group, True)]