diff --git a/bob/bio/base/pipelines/vanilla_biometrics/__init__.py b/bob/bio/base/pipelines/vanilla_biometrics/__init__.py
index 02c9a2a0a09f1521ac0964989c556f6b153057d8..0c04f2b34156259d3e297f8c611b6e626c873ca7 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/__init__.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/__init__.py
@@ -2,7 +2,7 @@ from .pipelines import VanillaBiometricsPipeline
from .biometric_algorithms import Distance
from .score_writers import FourColumnsScoreWriter, CSVScoreWriter
-from .wrappers import BioAlgorithmCheckpointWrapper, BioAlgorithmDaskWrapper, dask_vanilla_biometrics
+from .wrappers import BioAlgorithmCheckpointWrapper, BioAlgorithmDaskWrapper, dask_vanilla_biometrics, checkpoint_vanilla_biometrics
from .zt_norm import ZTNormPipeline, ZTNormDaskWrapper, ZTNormCheckpointWrapper
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/legacy.py b/bob/bio/base/pipelines/vanilla_biometrics/legacy.py
index 2a218b7ab1f3ab964a7fefa1ddbcbc5a7126a1f7..339c06d13e6ad8b97ef2dd89e4d2e9d8426d3aa2 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/legacy.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/legacy.py
@@ -54,10 +54,33 @@ class DatabaseConnector(Database):
The name of the protocol to generate samples from.
To be plugged at :py:method:`bob.db.base.Database.objects`.
+ allow_scoring_with_all_biometric_references: bool
+ If True will allow the scoring function to be performed in one shot with multiple probes.
+ This optimization is useful when all probes needs to be compared with all biometric references AND
+ your scoring function allows this broadcast computation.
+
+ annotation_type: str
+ Type of the annotations that the database provide.
+ Allowed types are: `eyes-center` and `bounding-box`
+
+ fixed_positions: dict
+ In case database contains one single annotation for all samples.
+ This is useful for registered databases.
"""
- def __init__(self, database, **kwargs):
+ def __init__(
+ self,
+ database,
+ allow_scoring_with_all_biometric_references=True,
+ annotation_type="eyes-center",
+ fixed_positions=None,
+ ** kwargs,
+ ):
self.database = database
+ self.allow_scoring_with_all_biometric_references = allow_scoring_with_all_biometric_references
+ self.annotation_type = annotation_type
+ self.fixed_positions=fixed_positions
+
def background_model_samples(self):
"""Returns :py:class:`Sample`'s to train a background model (group
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/wrappers.py b/bob/bio/base/pipelines/vanilla_biometrics/wrappers.py
index fed15da90ea07dfff467b338e193da49378eeec5..29ef62f3de67423448cecb164508ed9760a22741 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/wrappers.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/wrappers.py
@@ -5,11 +5,12 @@ import dask
import functools
from .score_writers import FourColumnsScoreWriter
from .abstract_classes import BioAlgorithm
-import bob.pipelines as mario
+import bob.pipelines
import numpy as np
import h5py
import cloudpickle
from .zt_norm import ZTNormPipeline, ZTNormDaskWrapper
+from .legacy import BioAlgorithmLegacy
class BioAlgorithmCheckpointWrapper(BioAlgorithm):
@@ -38,7 +39,9 @@ class BioAlgorithmCheckpointWrapper(BioAlgorithm):
"""
- def __init__(self, biometric_algorithm, base_dir, group=None, force=False, **kwargs):
+ def __init__(
+ self, biometric_algorithm, base_dir, group=None, force=False, **kwargs
+ ):
super().__init__(**kwargs)
self.base_dir = base_dir
@@ -47,14 +50,18 @@ class BioAlgorithmCheckpointWrapper(BioAlgorithm):
self.biometric_algorithm = biometric_algorithm
self.force = force
self._biometric_reference_extension = ".hdf5"
- self._score_extension = ".pkl"
+ self._score_extension = ".pkl"
def set_score_references_path(self, group):
if group is None:
- self.biometric_reference_dir = os.path.join(self.base_dir, "biometric_references")
+ self.biometric_reference_dir = os.path.join(
+ self.base_dir, "biometric_references"
+ )
self.score_dir = os.path.join(self.base_dir, "scores")
else:
- self.biometric_reference_dir = os.path.join(self.base_dir, group, "biometric_references")
+ self.biometric_reference_dir = os.path.join(
+ self.base_dir, group, "biometric_references"
+ )
self.score_dir = os.path.join(self.base_dir, group, "scores")
def enroll(self, enroll_features):
@@ -113,7 +120,7 @@ class BioAlgorithmCheckpointWrapper(BioAlgorithm):
def _load(path):
return cloudpickle.loads(open(path, "rb").read())
- #with h5py.File(path) as hdf5:
+ # with h5py.File(path) as hdf5:
# return hdf5_to_sample(hdf5)
def _make_name(sampleset, biometric_references):
@@ -125,7 +132,8 @@ class BioAlgorithmCheckpointWrapper(BioAlgorithm):
return os.path.join(subject, name + suffix)
path = os.path.join(
- self.score_dir, _make_name(sampleset, biometric_references) + self._score_extension
+ self.score_dir,
+ _make_name(sampleset, biometric_references) + self._score_extension,
)
if self.force or not os.path.exists(path):
@@ -221,7 +229,7 @@ def dask_vanilla_biometrics(pipeline, npartitions=None, partition_size=None):
"""
if isinstance(pipeline, ZTNormPipeline):
- # Dasking the first part of the pipelines
+ # Dasking the first part of the pipelines
pipeline.vanilla_biometrics_pipeline = dask_vanilla_biometrics(
pipeline.vanilla_biometrics_pipeline, npartitions
)
@@ -231,11 +239,11 @@ def dask_vanilla_biometrics(pipeline, npartitions=None, partition_size=None):
else:
if partition_size is None:
- pipeline.transformer = mario.wrap(
+ pipeline.transformer = bob.pipelines.wrap(
["dask"], pipeline.transformer, npartitions=npartitions
)
else:
- pipeline.transformer = mario.wrap(
+ pipeline.transformer = bob.pipelines.wrap(
["dask"], pipeline.transformer, partition_size=partition_size
)
pipeline.biometric_algorithm = BioAlgorithmDaskWrapper(
@@ -249,3 +257,38 @@ def dask_vanilla_biometrics(pipeline, npartitions=None, partition_size=None):
pipeline.write_scores = _write_scores
return pipeline
+
+
+def checkpoint_vanilla_biometrics(pipeline, base_dir):
+ """
+ Given a :any:`VanillaBiometrics`, wraps :any:`VanillaBiometrics.transformer` and
+ :any:`VanillaBiometrics.biometric_algorithm` to be checkpointed
+
+ Parameters
+ ----------
+
+ pipeline: :any:`VanillaBiometrics`
+ Vanilla Biometrics based pipeline to be dasked
+
+ base_dir: str
+ Path to store biometric references and scores
+
+ """
+
+ sk_pipeline = pipeline.transformer
+ for i, name, estimator in sk_pipeline._iter():
+
+ wraped_estimator = bob.pipelines.wrap(
+ ["checkpoint"], estimator, features_dir=os.path.join(base_dir, name)
+ )
+
+ sk_pipeline.steps[i] = (name, wraped_estimator)
+
+ if isinstance(pipeline.biometric_algorithm, BioAlgorithmLegacy):
+ pipeline.biometric_algorithm.base_dir = base_dir
+ else:
+ pipeline.biometric_algorithm = BioAlgorithmCheckpointWrapper(
+ pipeline.biometric_algorithm, base_dir=base_dir
+ )
+
+ return pipeline