diff --git a/bob/fusion/base/algorithm/Algorithm.py b/bob/fusion/base/algorithm/Algorithm.py
index f08ab93265b30545ecf0c7742c6e05d2b43d88e4..ac7819735164c14c9d3319bb0a8a0c710c443cd9 100644
--- a/bob/fusion/base/algorithm/Algorithm.py
+++ b/bob/fusion/base/algorithm/Algorithm.py
@@ -112,10 +112,11 @@ class Algorithm(object):
extensions such as model_file and model_file[:-3]+'hdf5'.
"""
# support for bob machines
- if hasattr(self, "machine"):
- self.save_bob(model_file)
+ if hasattr(self, "custom_save"):
+ self.custom_save(model_file)
else:
with open(model_file, "wb") as f:
+ pickle.dump(type(self), f)
pickle.dump(self, f)
def load(self, model_file):
@@ -128,46 +129,8 @@ class Algorithm(object):
A new instance of the loaded algorithm.
"""
with open(model_file, "rb") as f:
- temp = pickle.load(f)
- if isinstance(temp, Algorithm):
- return temp
- else:
- return self.load_bob(model_file)
-
- def _get_hdf5_file(self, model_file):
- return model_file[:-3] + 'hdf5'
-
- def save_bob(self, model_file):
- # dump preprocessors in a pickle file because
- # we don't know how they look like
- # saves the class to create it later.
- with open(model_file, 'wb') as f:
- pickle.dump(self.preprocessors, f)
- pickle.dump(type(self), f)
- # just for consistent string representation
- pickle.dump(self._kwargs, f)
-
- d5 = bob.io.base.HDF5File(self._get_hdf5_file(model_file), "w")
- try:
- self.machine.save(d5)
- finally:
- d5.close()
-
- def load_bob(self, model_file):
- # load preprocessors and the class
- with open(model_file, "rb") as f:
- preprocessors = pickle.load(f)
- myclass = pickle.load(f)
- _kwargs = pickle.load(f)
-
- myinstance = myclass(preprocessors=preprocessors)
- # just for consistent string representation
- myinstance._kwargs.update(_kwargs)
-
- d5 = bob.io.base.HDF5File(self._get_hdf5_file(model_file))
- try:
- myinstance.machine.load(d5)
- finally:
- d5.close()
-
- return myinstance
+ algo_class = pickle.load(f)
+ algo = algo_class()
+ if not hasattr(algo, 'custom_save'):
+ return pickle.load(f)
+ return algo.load(model_file)
diff --git a/bob/fusion/base/algorithm/AlgorithmBob.py b/bob/fusion/base/algorithm/AlgorithmBob.py
new file mode 100644
index 0000000000000000000000000000000000000000..ed5c3eb6af51f054a8ed45c4fa3569bb6647a1fa
--- /dev/null
+++ b/bob/fusion/base/algorithm/AlgorithmBob.py
@@ -0,0 +1,52 @@
+#!/usr/bin/env python
+
+from __future__ import division
+from __future__ import absolute_import
+
+import pickle
+from .Algorithm import Algorithm
+
+import bob.core
+logger = bob.core.log.setup("bob.fusion.base")
+
+
+class AlgorithmBob(Algorithm):
+ """A class to be used in score fusion using bob machines."""
+
+ def _get_hdf5_file(self, model_file):
+ return model_file[:-3] + 'hdf5'
+
+ def custom_save(self, model_file):
+ # dump preprocessors in a pickle file because
+ # we don't know how they look like
+ # saves the class to create it later.
+ with open(model_file, 'wb') as f:
+ pickle.dump(type(self), f)
+ pickle.dump(self.preprocessors, f)
+ # just for consistent string representation
+ pickle.dump(self._kwargs, f)
+
+ d5 = bob.io.base.HDF5File(self._get_hdf5_file(model_file), "w")
+ try:
+ self.machine.save(d5)
+ finally:
+ d5.close()
+
+ def load(self, model_file):
+ # load preprocessors and the class
+ with open(model_file, "rb") as f:
+ myclass = pickle.load(f)
+ preprocessors = pickle.load(f)
+ _kwargs = pickle.load(f)
+
+ myinstance = myclass(preprocessors=preprocessors)
+ # just for consistent string representation
+ myinstance._kwargs.update(_kwargs)
+
+ d5 = bob.io.base.HDF5File(self._get_hdf5_file(model_file))
+ try:
+ myinstance.machine.load(d5)
+ finally:
+ d5.close()
+
+ return myinstance
diff --git a/bob/fusion/base/algorithm/LLR.py b/bob/fusion/base/algorithm/LLR.py
index e6373449d52fa1e529b344246f2244bf0b4dd943..fa4fcac961c7b2bb74339b17d342876207918eb3 100644
--- a/bob/fusion/base/algorithm/LLR.py
+++ b/bob/fusion/base/algorithm/LLR.py
@@ -5,13 +5,13 @@ from __future__ import absolute_import
import bob.learn.linear
-from .Algorithm import Algorithm
+from .AlgorithmBob import AlgorithmBob
import logging
logger = logging.getLogger("bob.fusion.base")
-class LLR(Algorithm):
+class LLR(AlgorithmBob):
"""LLR Score fusion using Bob"""
def __init__(self,
diff --git a/bob/fusion/base/algorithm/MLP.py b/bob/fusion/base/algorithm/MLP.py
index f707761d84b5bd9553a11f5a1d8a80d31a41076f..e3898e88ebbb5453cadea42b14039e78e4be08aa 100644
--- a/bob/fusion/base/algorithm/MLP.py
+++ b/bob/fusion/base/algorithm/MLP.py
@@ -6,16 +6,15 @@ from __future__ import absolute_import
import bob.learn.mlp
import bob.core.random
import bob.io.base
-import pickle
-from .Algorithm import Algorithm
+from .AlgorithmBob import AlgorithmBob
from .mlp_train_helper import MLPTrainer
import bob.core
logger = bob.core.log.setup("bob.fusion.base")
-class MLP(Algorithm):
+class MLP(AlgorithmBob):
"""This MLP is implemented using the bob tools.
The preprocessors used with this class should be pickleable.
"""
diff --git a/bob/fusion/base/algorithm/__init__.py b/bob/fusion/base/algorithm/__init__.py
index 25f3fc12a4df60c9fcd68cdf3622472347ef47e4..0927c2906fa6757fca376384443715d82e1353a3 100644
--- a/bob/fusion/base/algorithm/__init__.py
+++ b/bob/fusion/base/algorithm/__init__.py
@@ -1,4 +1,5 @@
from .Algorithm import Algorithm
+from .AlgorithmBob import AlgorithmBob
from .Weighted_Sum import Weighted_Sum
from .MLP import MLP
from .LLR import LLR
diff --git a/bob/fusion/base/data/scores-dev-1 b/bob/fusion/base/data/scores-dev-1
new file mode 100644
index 0000000000000000000000000000000000000000..b414412f959fb9f9d9f9e3a25c58d076c6b3d234
--- /dev/null
+++ b/bob/fusion/base/data/scores-dev-1
@@ -0,0 +1,120 @@
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diff --git a/bob/fusion/base/data/scores-dev-2 b/bob/fusion/base/data/scores-dev-2
new file mode 100644
index 0000000000000000000000000000000000000000..e8d6076caa4fcd4570d9af9f52b480e70fd165db
--- /dev/null
+++ b/bob/fusion/base/data/scores-dev-2
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diff --git a/bob/fusion/base/data/scores-eval-1 b/bob/fusion/base/data/scores-eval-1
new file mode 100644
index 0000000000000000000000000000000000000000..e15151e6f71891c9d4d7059db2a2ceb7b446b99a
--- /dev/null
+++ b/bob/fusion/base/data/scores-eval-1
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diff --git a/bob/fusion/base/data/scores-eval-2 b/bob/fusion/base/data/scores-eval-2
new file mode 100644
index 0000000000000000000000000000000000000000..f0dd275c6b4a7fea4f83ba23aa99f412567929e6
--- /dev/null
+++ b/bob/fusion/base/data/scores-eval-2
@@ -0,0 +1,160 @@
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+102 21 020/test/real/client021_session01_webcam_authenticate_controlled_1 0.29585259108
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+102 117 020/test/real/client117_session01_webcam_authenticate_controlled_1 -0.0778756699388
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diff --git a/bob/fusion/base/script/bob_fuse.py b/bob/fusion/base/script/bob_fuse.py
index f14dc75eb423965d264acb37f47c6d9d7f34af94..435ce6844211955946612c6cf4b9798d8f7db170 100755
--- a/bob/fusion/base/script/bob_fuse.py
+++ b/bob/fusion/base/script/bob_fuse.py
@@ -33,9 +33,6 @@ def fuse(args, command_line_parameters):
score_lines_list_eval = [load_score(path, ncolumns=args.score_type)
for path in args.eval_files]
scores_eval = get_all_scores(score_lines_list_eval)
- else:
- score_lines_list_eval = []
- scores_eval = []
# check if score lines are consistent
if not args.skip_check:
@@ -54,7 +51,8 @@ def fuse(args, command_line_parameters):
# preprocess data
scores_dev = algorithm.preprocess(scores_dev)
- scores_eval = algorithm.preprocess(scores_eval)
+ if args.eval_files:
+ scores_eval = algorithm.preprocess(scores_eval)
neg, pos = algorithm.preprocess(neg), algorithm.preprocess(pos)
# train the model
diff --git a/bob/fusion/base/script/plot_fusion_decision_boundary.py b/bob/fusion/base/script/plot_fusion_decision_boundary.py
index 9452d91510db54e489346d692800907e511e4a53..346d3c1e66cab46275813954853c9bbd0fe2470f 100644
--- a/bob/fusion/base/script/plot_fusion_decision_boundary.py
+++ b/bob/fusion/base/script/plot_fusion_decision_boundary.py
@@ -15,12 +15,8 @@ Options:
messages) to 1 (warnings), 2 (log messages), 3 (debug
information) by adding the --verbose option as often
as desired (e.g. '-vvv' for debug). [default: 0]
- -a, --algorithm Algorithm The fusion that was used during fusion if they
- implement a different load method e.g.
- bob.fusion.base.algorithm.MLP.
- [default: bob.fusion.base.algorithm.Algorithm]
-g, --group N If given scores will be grouped into N samples.
- [default: 500]
+ Give -1 for no grouping. [default: -1]
--grouping {random, kmeans} The gouping algorithm used. [default: kmeans]
-h --help Show this screen.
-V, --version Show version.
@@ -110,6 +106,7 @@ def plot_boundary_decision(algorithm, scores, score_labels, threshold,
plt.xlim([x_min, x_max])
plt.ylim([y_min, y_max])
+ plt.grid('on')
return contourf
@@ -117,11 +114,10 @@ def plot_boundary_decision(algorithm, scores, score_labels, threshold,
def main(command_line_parameters=None):
args = docopt(__doc__, argv=command_line_parameters,
version=bob.fusion.base.get_config())
- print(args)
bob.core.log.set_verbosity_level(logger, args['--verbose'])
# load the algorithm
- algorithm = eval('{}()'.format(args['--algorithm']))
+ algorithm = bob.fusion.base.algorithm.Algorithm()
algorithm = algorithm.load(args['MODEL_FILE'])
# load the scores
@@ -135,9 +131,13 @@ def main(command_line_parameters=None):
score_labels = score_lines['claimed_id'] == score_lines['real_id']
# plot the decision boundary
+ do_grouping = True
+ if int(args['--group']) == -1:
+ do_grouping = False
+
plot_boundary_decision(
algorithm, scores, score_labels, threshold,
- do_grouping=True,
+ do_grouping=do_grouping,
npoints=int(args['--group']),
seed=0,
gformat=args['--grouping']
diff --git a/bob/fusion/base/test/test_scripts.py b/bob/fusion/base/test/test_scripts.py
index 4265cc3e6c16c09774190fa55d609cd9fe0808e4..9bfe632cea8b505f27e91742c4b6c9460fe5d286 100644
--- a/bob/fusion/base/test/test_scripts.py
+++ b/bob/fusion/base/test/test_scripts.py
@@ -1 +1,59 @@
#!/usr/bin/env python
+
+import os
+import shutil
+import tempfile
+
+from bob.fusion.base.script.bob_fuse import main as bob_fuse
+from bob.fusion.base.script.plot_fusion_decision_boundary import main as plot_fusion_decision_boundary
+from bob.io.base.test_utils import datafile
+
+dev_files = [datafile("scores-dev-1", 'bob.fusion.base'),
+ datafile("scores-dev-2", 'bob.fusion.base')]
+eval_files = [datafile("scores-eval-1", 'bob.fusion.base'),
+ datafile("scores-eval-2", 'bob.fusion.base')]
+
+
+def test_scripts():
+
+ tmpdir = tempfile.mkdtemp()
+ try:
+ fused_dev_file = os.path.join(tmpdir, 'scores-dev')
+ fused_eval_file = os.path.join(tmpdir, 'scores-eval')
+
+ # test normally
+ cmd = ['-i'] + dev_files + ['-o', fused_dev_file, '-a', 'llr']
+ bob_fuse(cmd)
+
+ cmd = ['-i'] + dev_files + ['-I'] + eval_files + ['-o', fused_dev_file, '-O', fused_eval_file, '-a', 'llr']
+ bob_fuse(cmd)
+
+ # make inconsistency
+ wrong_dev2 = os.path.join(tmpdir, 'scores-dev-2')
+ with open(wrong_dev2, 'w') as f1, open(dev_files[1]) as f2:
+ lines = f2.readlines()
+ temp = lines[0].split()
+ temp = (temp[0], 'temp1_id', temp[2], temp[3])
+ lines[0] = ' '.join(temp) + '\n'
+ f1.writelines(lines)
+
+ cmd = ['-i'] + dev_files[0:1] + [wrong_dev2] + ['-o', fused_dev_file, '-a', 'llr']
+ try:
+ bob_fuse(cmd)
+ except AssertionError:
+ pass
+ else:
+ raise Exception('An AssertionError should have been raised.')
+
+ # this should not raise an error
+ cmd = ['-i'] + dev_files[0:1] + [wrong_dev2] + ['-o', fused_dev_file, '-a', 'llr', '--skip-check']
+ bob_fuse(cmd)
+
+ # test plot
+ model_file = os.path.join(tmpdir, 'Model.pkl')
+ output = os.path.join(tmpdir, 'scatter.pdf')
+ cmd = dev_files + [model_file, '-o', output]
+ plot_fusion_decision_boundary(cmd)
+
+ finally:
+ shutil.rmtree(tmpdir)