diff --git a/bob/bio/base/__init__.py b/bob/bio/base/__init__.py
index 82ce2a09e27b49c5572bda388b25b6cdb1934df5..f55d534a0d2717a10b2fd14f8a6788097737b350 100644
--- a/bob/bio/base/__init__.py
+++ b/bob/bio/base/__init__.py
@@ -4,16 +4,19 @@ from . import preprocessor
from . import extractor
from . import algorithm
from . import annotator
+from . import pipelines
from . import script
from . import test
+
def get_config():
- """Returns a string containing the configuration information.
+ """Returns a string containing the configuration information.
"""
- import bob.extension
- return bob.extension.get_config(__name__)
+ import bob.extension
+
+ return bob.extension.get_config(__name__)
# gets sphinx autodoc done right - don't remove it
-__all__ = [_ for _ in dir() if not _.startswith('_')]
+__all__ = [_ for _ in dir() if not _.startswith("_")]
diff --git a/bob/bio/base/database/__init__.py b/bob/bio/base/database/__init__.py
index 8e071c9f60a94bae2b09a8e4b2709e7835752425..f893a1a77c0a60954a628798448632866879e3bc 100644
--- a/bob/bio/base/database/__init__.py
+++ b/bob/bio/base/database/__init__.py
@@ -1,4 +1,9 @@
-from .csv_dataset import CSVDatasetDevEval, CSVToSampleLoader, CSVDatasetCrossValidation
+from .csv_dataset import (
+ CSVDatasetDevEval,
+ CSVToSampleLoader,
+ CSVDatasetCrossValidation,
+ CSVBaseSampleLoader,
+)
from .file import BioFile
from .file import BioFileSet
from .database import BioDatabase
@@ -9,7 +14,7 @@ from . import filelist
# gets sphinx autodoc done right - don't remove it
def __appropriate__(*args):
- """Says object was actually declared here, and not in the import module.
+ """Says object was actually declared here, and not in the import module.
Fixing sphinx warnings of not being able to find classes, when path is shortened.
Parameters:
@@ -19,17 +24,18 @@ def __appropriate__(*args):
<https://github.com/sphinx-doc/sphinx/issues/3048>`
"""
- for obj in args:
- obj.__module__ = __name__
+ for obj in args:
+ obj.__module__ = __name__
__appropriate__(
BioFile,
BioFileSet,
BioDatabase,
- ZTBioDatabase,
- CSVDatasetDevEval,
+ ZTBioDatabase,
+ CSVBaseSampleLoader,
+ CSVDatasetDevEval,
CSVToSampleLoader,
- CSVDatasetCrossValidation
+ CSVDatasetCrossValidation,
)
-__all__ = [_ for _ in dir() if not _.startswith('_')]
+__all__ = [_ for _ in dir() if not _.startswith("_")]
diff --git a/bob/bio/base/database/csv_dataset.py b/bob/bio/base/database/csv_dataset.py
index bafb21a73aa7333aaa2ee7790ab4d7c29cab7e60..23dfbae7bef89ab238a71c8b91e6d21b0900eddf 100644
--- a/bob/bio/base/database/csv_dataset.py
+++ b/bob/bio/base/database/csv_dataset.py
@@ -67,25 +67,24 @@ class CSVToSampleLoader(CSVBaseSampleLoader):
:any:`bob.pipelines.DelayedSample` or :any:`bob.pipelines.SampleSet`
"""
- def __call__(self, filename):
- def check_header(header):
- """
- A header should have at least "SUBJECT" AND "PATH"
- """
- header = [h.lower() for h in header]
- if not "subject" in header:
- raise ValueError(
- "The field `subject` is not available in your dataset."
- )
+ def check_header(self, header):
+ """
+ A header should have at least "SUBJECT" AND "PATH"
+ """
+ header = [h.lower() for h in header]
+ if not "subject" in header:
+ raise ValueError("The field `subject` is not available in your dataset.")
- if not "path" in header:
- raise ValueError("The field `path` is not available in your dataset.")
+ if not "path" in header:
+ raise ValueError("The field `path` is not available in your dataset.")
+
+ def __call__(self, filename):
with open(filename) as cf:
reader = csv.reader(cf)
header = next(reader)
- check_header(header)
+ self.check_header(header)
return [self.convert_row_to_sample(row, header) for row in reader]
def convert_row_to_sample(self, row, header):
@@ -136,8 +135,8 @@ class CSVToSampleLoader(CSVBaseSampleLoader):
class CSVDatasetDevEval:
"""
- Generic filelist dataset for :any:`bob.bio.base.pipelines.VanillaBiometrics` pipeline.
- Check :ref:`vanilla_biometrics_features` for more details about the Vanilla Biometrics Dataset
+ Generic filelist dataset for :any:` bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline` pipeline.
+ Check :any:`vanilla_biometrics_features` for more details about the Vanilla Biometrics Dataset
interface.
To create a new dataset, you need to provide a directory structure similar to the one below:
@@ -163,8 +162,8 @@ class CSVDatasetDevEval:
Those csv files should contain in each row i-) the path to raw data and ii-) the subject label
- for enrollment (:ref:`bob.bio.base.pipelines.vanilla_biometrics.abstract_classes.Database.references`) and
- probing (:ref:`bob.bio.base.pipelines.vanilla_biometrics.abstract_classes.Database.probes`).
+ for enrollment (:any:`bob.bio.base.pipelines.vanilla_biometrics.Database.references`) and
+ probing (:any:`bob.bio.base.pipelines.vanilla_biometrics.Database.probes`).
The structure of each CSV file should be as below:
.. code-block:: text
@@ -192,7 +191,7 @@ class CSVDatasetDevEval:
are optional and it is used in case a protocol contains data for evaluation.
Finally, the content of the file `my_dataset/my_protocol/train.csv` is used in the case a protocol
- contains data for training (:ref:`bob.bio.base.pipelines.vanilla_biometrics.abstract_classes.Database.background_model_samples`)
+ contains data for training (`bob.bio.base.pipelines.vanilla_biometrics.Database.background_model_samples`)
Parameters
----------
@@ -203,8 +202,8 @@ class CSVDatasetDevEval:
protocol_na,e: str
The name of the protocol
- csv_to_sample_loader: :any:`CSVBaseSampleLoader`
- Base class that whose objective is to generate :any:`bob.pipelines.Samples`
+ csv_to_sample_loader: :any:`bob.bio.base.database.CSVBaseSampleLoader`
+ Base class that whose objective is to generate :any:`bob.pipelines.Sample`
and/or :any:`bob.pipelines.SampleSet` from csv rows
"""
@@ -330,10 +329,10 @@ class CSVDatasetDevEval:
class CSVDatasetCrossValidation:
"""
- Generic filelist dataset for :any:`bob.bio.base.pipelines.VanillaBiometrics` pipeline that
+ Generic filelist dataset for :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline` pipeline that
handles **CROSS VALIDATION**.
- Check :ref:`vanilla_biometrics_features` for more details about the Vanilla Biometrics Dataset
+ Check :any:`vanilla_biometrics_features` for more details about the Vanilla Biometrics Dataset
interface.
@@ -365,8 +364,8 @@ class CSVDatasetCrossValidation:
samples_for_enrollment: float
Number of samples used for enrollment
- csv_to_sample_loader: :any:`CSVBaseSampleLoader`
- Base class that whose objective is to generate :any:`bob.pipelines.Samples`
+ csv_to_sample_loader: :any:`bob.bio.base.database.CSVBaseSampleLoader`
+ Base class that whose objective is to generate :any:`bob.pipelines.Sample`
and/or :any:`bob.pipelines.SampleSet` from csv rows
"""
diff --git a/bob/bio/base/database/file.py b/bob/bio/base/database/file.py
index 675373625d6a39219346e8786750606a4199627b..8f23b2f428d315b5c67be10922fbc457677ba653 100644
--- a/bob/bio/base/database/file.py
+++ b/bob/bio/base/database/file.py
@@ -2,6 +2,7 @@ import bob.db.base
from bob.db.base.annotations import read_annotation_file
from bob.pipelines.sample import _ReprMixin
+
class BioFile(bob.db.base.File, _ReprMixin):
"""
A simple base class that defines basic properties of File object for the use
@@ -29,7 +30,7 @@ class BioFile(bob.db.base.File, _ReprMixin):
The extension of annotation files. Default is ``.json``
annotation_type : str or None
The type of the annotation file, see
- :any:`bob.db.base.annotations.read_annotation_file`. Default is
+ :`bob.db.base.annotations.read_annotation_file`. Default is
``json``.
"""
@@ -82,14 +83,14 @@ class BioFile(bob.db.base.File, _ReprMixin):
if original_extension is None:
original_extension = self.original_extension
# get the path
- path = self.make_path(
- original_directory or "", original_extension or ""
- )
+ path = self.make_path(original_directory or "", original_extension or "")
return bob.io.base.load(path)
@property
def annotations(self):
- path = self.make_path(self.annotation_directory or "", self.annotation_extension or "")
+ path = self.make_path(
+ self.annotation_directory or "", self.annotation_extension or ""
+ )
return read_annotation_file(path, annotation_type=self.annotation_type)
diff --git a/bob/bio/base/pipelines/__init__.py b/bob/bio/base/pipelines/__init__.py
index edbb4090fca046b19d22d3982711084621bff3be..4b3de5c27ff1de35709b7e3943e0d6422092a079 100644
--- a/bob/bio/base/pipelines/__init__.py
+++ b/bob/bio/base/pipelines/__init__.py
@@ -1,4 +1,7 @@
# see https://docs.python.org/3/library/pkgutil.html
from pkgutil import extend_path
+
+from . import vanilla_biometrics
+
__path__ = extend_path(__path__, __name__)
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/__init__.py b/bob/bio/base/pipelines/vanilla_biometrics/__init__.py
index 1554539476490058f2057022e5cacc98dda6aa57..96e784a441054acf58578bd35ce9ec75c94bf2f2 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/__init__.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/__init__.py
@@ -8,11 +8,59 @@ from .wrappers import (
dask_vanilla_biometrics,
checkpoint_vanilla_biometrics,
dask_get_partition_size,
- is_checkpointed
+ is_checkpointed,
)
-from .zt_norm import ZTNormPipeline, ZTNormDaskWrapper, ZTNormCheckpointWrapper
+from .abstract_classes import BioAlgorithm, Database, ScoreWriter
+
+from .zt_norm import ZTNormPipeline, ZTNormDaskWrapper, ZTNormCheckpointWrapper, ZTNorm
from .legacy import BioAlgorithmLegacy, DatabaseConnector
from .vanilla_biometrics import execute_vanilla_biometrics
+
+
+# gets sphinx autodoc done right - don't remove it
+def __appropriate__(*args):
+ """Says object was actually declared here, and not in the import module.
+ Fixing sphinx warnings of not being able to find classes, when path is
+ shortened.
+
+ Parameters
+ ----------
+ *args
+ An iterable of objects to modify
+
+ Resolves `Sphinx referencing issues
+ <https://github.com/sphinx-doc/sphinx/issues/3048>`
+ """
+
+ for obj in args:
+ obj.__module__ = __name__
+
+
+__appropriate__(
+ VanillaBiometricsPipeline,
+ Distance,
+ FourColumnsScoreWriter,
+ CSVScoreWriter,
+ BioAlgorithmCheckpointWrapper,
+ BioAlgorithmDaskWrapper,
+ dask_vanilla_biometrics,
+ checkpoint_vanilla_biometrics,
+ dask_get_partition_size,
+ is_checkpointed,
+ ZTNormPipeline,
+ ZTNormDaskWrapper,
+ ZTNormCheckpointWrapper,
+ BioAlgorithmLegacy,
+ DatabaseConnector,
+ execute_vanilla_biometrics,
+ BioAlgorithm,
+ Database,
+ ScoreWriter,
+ ZTNorm,
+)
+
+__all__ = [_ for _ in dir() if not _.startswith("_")]
+
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/biometric_algorithms.py b/bob/bio/base/pipelines/vanilla_biometrics/biometric_algorithms.py
index 233c9863d7b07c98216f068922cfc45be3acf58a..16eeee6f17b75633ced2eea079f6560c24e340d2 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/biometric_algorithms.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/biometric_algorithms.py
@@ -21,14 +21,14 @@ class Distance(BioAlgorithm):
Enrolls the model by storing all given input vectors.
- Parameters:
- -----------
+ Parameters
+ ----------
``enroll_features`` : [:py:class:`numpy.ndarray`]
The list of projected features to enroll the model from.
- Returns:
- --------
+ Returns
+ -------
``model`` : 2D :py:class:`numpy.ndarray`
The enrolled model.
@@ -43,8 +43,8 @@ class Distance(BioAlgorithm):
Computes the distance of the model to the probe using the distance function specified in the constructor.
- Parameters:
- -----------
+ Parameters
+ ----------
``model`` : 2D :py:class:`numpy.ndarray`
The model storing all enrollment features
@@ -52,8 +52,8 @@ class Distance(BioAlgorithm):
``probe`` : :py:class:`numpy.ndarray`
The probe feature vector
- Returns:
- --------
+ Returns
+ -------
``score`` : float
A similarity value between ``model`` and ``probe``
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/legacy.py b/bob/bio/base/pipelines/vanilla_biometrics/legacy.py
index aac7afc3e260e976079c45e65edf76ca784e28bb..d0f49582cbff6a6a3d2b946bdcd5dcf928f25ae6 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/legacy.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/legacy.py
@@ -52,7 +52,7 @@ class DatabaseConnector(Database):
protocol : str
The name of the protocol to generate samples from.
- To be plugged at :py:method:`bob.db.base.Database.objects`.
+ To be plugged at `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.
@@ -294,7 +294,7 @@ class BioAlgorithmLegacy(BioAlgorithm):
def write_scores(self, samples, path):
os.makedirs(os.path.dirname(path), exist_ok=True)
- #open(path, "wb").write(pickle.dumps(samples))
+ # open(path, "wb").write(pickle.dumps(samples))
joblib.dump(samples, path, compress=4)
def _score_sample_set(
@@ -304,7 +304,7 @@ class BioAlgorithmLegacy(BioAlgorithm):
allow_scoring_with_all_biometric_references=False,
):
def _load(path):
- #return pickle.loads(open(path, "rb").read())
+ # return pickle.loads(open(path, "rb").read())
return joblib.load(path)
def _make_name(sampleset, biometric_references):
@@ -315,7 +315,8 @@ class BioAlgorithmLegacy(BioAlgorithm):
return 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):
@@ -329,8 +330,9 @@ class BioAlgorithmLegacy(BioAlgorithm):
self.write_scores(scored_sample_set.samples, path)
- scored_sample_set = DelayedSampleSet(functools.partial(_load, path),
- parent=scored_sample_set)
+ scored_sample_set = DelayedSampleSet(
+ functools.partial(_load, path), parent=scored_sample_set
+ )
else:
scored_sample_set = SampleSet(_load(path), parent=sampleset)
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/pipelines.py b/bob/bio/base/pipelines/vanilla_biometrics/pipelines.py
index b0ec77bfc6b8052b90f35bfef6ce727eeeae824c..a26353ffd47e476a269ddd1bf854910841c66b12 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/pipelines.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/pipelines.py
@@ -60,8 +60,8 @@ class VanillaBiometricsPipeline(object):
>>> pipeline(samples_for_training_back_ground_model, samplesets_for_enroll, samplesets_for_scoring).compute()
- Parameters:
- -----------
+ Parameters
+ ----------
transformer: :py:class`sklearn.pipeline.Pipeline` or a `sklearn.base.BaseEstimator`
Transformer that will preprocess your data
@@ -69,8 +69,8 @@ class VanillaBiometricsPipeline(object):
biometric_algorithm: :py:class:`bob.bio.base.pipelines.vanilla_biometrics.abstract_classes.BioAlgorithm`
Biometrics algorithm object that implements the methods `enroll` and `score` methods
- score_writer: :any:`bob.bio.base.pipelines.vanilla_biometrics.abstract_classe.ScoreWriter`
- Format to write scores. Default to :any:`FourColumnsScoreWriter`
+ score_writer: :any:`bob.bio.base.pipelines.vanilla_biometrics.ScoreWriter`
+ Format to write scores. Default to :any:`bob.bio.base.pipelines.vanilla_biometrics.FourColumnsScoreWriter`
"""
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/vanilla_biometrics.py b/bob/bio/base/pipelines/vanilla_biometrics/vanilla_biometrics.py
index ffcc645310ecf60728a5ddf7c5e9573018d2c0c3..29f07d57e84abbe95316426f4a2f29daf672e04f 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/vanilla_biometrics.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/vanilla_biometrics.py
@@ -17,7 +17,6 @@ from bob.pipelines.utils import isinstance_nested
logger = logging.getLogger(__name__)
-
def compute_scores(result, dask_client):
if isinstance(result, Delayed) or isinstance(result, dask.bag.Bag):
if dask_client is not None:
@@ -33,7 +32,6 @@ def post_process_scores(pipeline, scores, path):
return pipeline.post_process(written_scores, path)
-
def execute_vanilla_biometrics(
pipeline,
database,
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/wrappers.py b/bob/bio/base/pipelines/vanilla_biometrics/wrappers.py
index 31d0b7b5160f9c9b5081106c45e7ec73ce2c99b3..c9e6da050bdaa0fb37be7bb252ac40b10a6b6442 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/wrappers.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/wrappers.py
@@ -31,8 +31,8 @@ class BioAlgorithmCheckpointWrapper(BioAlgorithm):
Parameters
----------
- biometric_algorithm: :any:`BioAlgorithm`
- An implemented :any:`BioAlgorithm`
+ biometric_algorithm: :any:`bob.bio.base.pipelines.vanilla_biometrics.BioAlgorithm`
+ An implemented :any:`bob.bio.base.pipelines.vanilla_biometrics.BioAlgorithm`
base_dir: str
Path to store biometric references and scores
@@ -182,7 +182,7 @@ class BioAlgorithmCheckpointWrapper(BioAlgorithm):
class BioAlgorithmDaskWrapper(BioAlgorithm):
"""
- Wrap :any:`BioAlgorithm` to work with DASK
+ Wrap :any:`bob.bio.base.pipelines.vanilla_biometrics.BioAlgorithm` to work with DASK
"""
def __init__(self, biometric_algorithm, **kwargs):
@@ -235,20 +235,20 @@ class BioAlgorithmDaskWrapper(BioAlgorithm):
def dask_vanilla_biometrics(pipeline, npartitions=None, partition_size=None):
"""
- Given a :any:`VanillaBiometrics`, wraps :any:`VanillaBiometrics.transformer` and
- :any:`VanillaBiometrics.biometric_algorithm` to be executed with dask
+ Given a :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline`, wraps :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline` and
+ :any:`bob.bio.base.pipelines.vanilla_biometrics.BioAlgorithm` to be executed with dask
Parameters
----------
- pipeline: :any:`VanillaBiometrics`
+ pipeline: :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline`
Vanilla Biometrics based pipeline to be dasked
npartitions: int
- Number of partitions for the initial :any:`dask.bag`
+ Number of partitions for the initial `dask.bag`
partition_size: int
- Size of the partition for the initial :any:`dask.bag`
+ Size of the partition for the initial `dask.bag`
"""
if isinstance(pipeline, ZTNormPipeline):
@@ -294,11 +294,11 @@ def dask_get_partition_size(cluster, n_objects):
The heuristics is pretty simple, given the max number of possible workers to be run
in a queue (not the number of current workers running) and a total number objects to be processed do n_objects/n_max_workers:
- Parameters:
- -----------
+ Parameters
+ ----------
- cluster: :any:`bob.pipelines.distributed.SGEMultipleQueuesCluster`
- Cluster of the type :any:`bob.pipelines.distributed.SGEMultipleQueuesCluster`
+ cluster: :any:`bob.pipelines.distributed.sge.SGEMultipleQueuesCluster`
+ Cluster of the type :any:`bob.pipelines.distributed.sge.SGEMultipleQueuesCluster`
n_objects: int
Number of objects to be processed
@@ -313,13 +313,13 @@ def dask_get_partition_size(cluster, n_objects):
def checkpoint_vanilla_biometrics(pipeline, base_dir, biometric_algorithm_dir=None):
"""
- Given a :any:`VanillaBiometrics`, wraps :any:`VanillaBiometrics.transformer` and
- :any:`VanillaBiometrics.biometric_algorithm` to be checkpointed
+ Given a :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline`, wraps :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline` and
+ :any:`bob.bio.base.pipelines.vanilla_biometrics.BioAlgorithm` to be checkpointed
Parameters
----------
- pipeline: :any:`VanillaBiometrics`
+ pipeline: :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline`
Vanilla Biometrics based pipeline to be checkpointed
base_dir: str
@@ -362,7 +362,9 @@ def checkpoint_vanilla_biometrics(pipeline, base_dir, biometric_algorithm_dir=No
):
save_func = estimator.estimator.instance.write_feature
load_func = estimator.estimator.instance.read_feature
- estimator.estimator.projector_file = os.path.join(bio_ref_scores_dir,"Projector.hdf5")
+ estimator.estimator.projector_file = os.path.join(
+ bio_ref_scores_dir, "Projector.hdf5"
+ )
wraped_estimator = bob.pipelines.wrap(
["checkpoint"],
@@ -374,7 +376,6 @@ def checkpoint_vanilla_biometrics(pipeline, base_dir, biometric_algorithm_dir=No
sk_pipeline.steps[i] = (name, wraped_estimator)
-
if isinstance(pipeline.biometric_algorithm, BioAlgorithmLegacy):
pipeline.biometric_algorithm.base_dir = bio_ref_scores_dir
else:
@@ -387,13 +388,13 @@ def checkpoint_vanilla_biometrics(pipeline, base_dir, biometric_algorithm_dir=No
def is_checkpointed(pipeline):
"""
- Check if :any:`VanillaBiometrics` is checkpointed
+ Check if :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline` is checkpointed
Parameters
----------
- pipeline: :any:`VanillaBiometrics`
+ pipeline: :any:`bob.bio.base.pipelines.vanilla_biometrics.VanillaBiometricsPipeline`
Vanilla Biometrics based pipeline to be checkpointed
"""
@@ -402,7 +403,7 @@ def is_checkpointed(pipeline):
# If it BioAlgorithmLegacy and the transformer of BioAlgorithmLegacy is also checkpointable
return isinstance_nested(
pipeline, "biometric_algorithm", BioAlgorithmCheckpointWrapper
- ) or \
- ( isinstance_nested(pipeline, "biometric_algorithm", BioAlgorithmLegacy) and \
- isinstance_nested(pipeline, "transformer", CheckpointWrapper)
+ ) or (
+ isinstance_nested(pipeline, "biometric_algorithm", BioAlgorithmLegacy)
+ and isinstance_nested(pipeline, "transformer", CheckpointWrapper)
)
diff --git a/bob/bio/base/pipelines/vanilla_biometrics/zt_norm.py b/bob/bio/base/pipelines/vanilla_biometrics/zt_norm.py
index fbdfaba935b1f326b354c5e87946e30d833f3a6a..10c049d62aca3f51804ea928ac490d693a546793 100644
--- a/bob/bio/base/pipelines/vanilla_biometrics/zt_norm.py
+++ b/bob/bio/base/pipelines/vanilla_biometrics/zt_norm.py
@@ -3,7 +3,7 @@
# vim: set fileencoding=utf-8 :
Implementation of a pipeline and an algorithm that
-computes Z, T and ZT Score Normalization of a :any:`BioAlgorithm`
+computes Z, T and ZT Score Normalization of a :any:`bob.bio.base.pipelines.vanilla_biometrics.BioAlgorithm`
"""
from bob.pipelines import DelayedSample, Sample, SampleSet, DelayedSampleSet
@@ -17,6 +17,7 @@ import copy
import joblib
import logging
from .pipelines import check_valid_pipeline
+
logger = logging.getLogger(__name__)
@@ -265,7 +266,7 @@ class ZTNormPipeline(object):
class ZTNorm(object):
"""
- Computes Z, T and ZT Score Normalization of a :any:`BioAlgorithm`
+ Computes Z, T and ZT Score Normalization of a `:any:`bob.bio.base.pipelines.vanilla_biometrics.BioAlgorithm`
Reference bibliography from: A Generative Model for Score Normalization in Speaker Recognition
https://arxiv.org/pdf/1709.09868.pdf
@@ -496,12 +497,12 @@ class ZTNorm(object):
class ZTNormDaskWrapper(object):
"""
- Wrap :any:`ZTNorm` to work with DASK
+ Wrap `:any:`bob.bio.base.pipelines.vanilla_biometrics.ZTNorm` to work with DASK
Parameters
----------
- ztnorm: :any:`ZTNorm`
+ ztnorm: :any:`bob.bio.base.pipelines.vanilla_biometrics.ZTNormPipeline`
ZTNorm Pipeline
"""
@@ -558,12 +559,12 @@ class ZTNormDaskWrapper(object):
class ZTNormCheckpointWrapper(object):
"""
- Wrap :any:`ZTNorm` to work with DASK
+ Wrap :any:`bob.bio.base.pipelines.vanilla_biometrics.ZTNormPipeline` to work with DASK
Parameters
----------
- ztnorm: :any:`ZTNorm`
+ ztnorm: :any:`bob.bio.base.pipelines.vanilla_biometrics.ZTNorm`
ZTNorm Pipeline
"""
@@ -584,11 +585,11 @@ class ZTNormCheckpointWrapper(object):
def write_scores(self, samples, path):
os.makedirs(os.path.dirname(path), exist_ok=True)
- #open(path, "wb").write(cloudpickle.dumps(samples))
+ # open(path, "wb").write(cloudpickle.dumps(samples))
joblib.dump(samples, path, compress=4)
def _load(self, path):
- #return cloudpickle.loads(open(path, "rb").read())
+ # return cloudpickle.loads(open(path, "rb").read())
return joblib.load(path)
def _make_name(self, sampleset, biometric_references, for_zt=False):
@@ -613,8 +614,8 @@ class ZTNormCheckpointWrapper(object):
self.write_scores(z_normed_score.samples, path)
z_normed_score = DelayedSampleSet(
- functools.partial(self._load, path),
- parent=probe_score)
+ functools.partial(self._load, path), parent=probe_score
+ )
return z_normed_score
@@ -630,8 +631,9 @@ class ZTNormCheckpointWrapper(object):
self.write_scores(t_normed_score.samples, path)
- t_normed_score = DelayedSampleSet(functools.partial(self._load, path),
- parent=probe_score)
+ t_normed_score = DelayedSampleSet(
+ functools.partial(self._load, path), parent=probe_score
+ )
return t_normed_score
def compute_znorm_scores(
diff --git a/bob/bio/base/test/test_filelist.py b/bob/bio/base/test/test_filelist.py
index dc6ded053d175e3dd6fd7b4d518c72ea1f3efdc2..f91f9da2adfe9f0ce2a7fb1a8bc1eb372141c4a9 100644
--- a/bob/bio/base/test/test_filelist.py
+++ b/bob/bio/base/test/test_filelist.py
@@ -188,6 +188,7 @@ def test_atnt_experiment_cross_validation():
# Testing the Legacy file list
####
+
def test_query():
db = FileListBioDatabase(
legacy_example_dir, "test", use_dense_probe_file_list=False
diff --git a/doc/extra-intersphinx.txt b/doc/extra-intersphinx.txt
index 06dcf5f4e801ce70b13529c61503a191a1c1a713..afa9ff94c2127b4d753171100464d4840b5ce6b2 100644
--- a/doc/extra-intersphinx.txt
+++ b/doc/extra-intersphinx.txt
@@ -9,3 +9,4 @@ bob.learn.linear
gridtk
bob.db.youtube
bob.pipelines
+dask
\ No newline at end of file
diff --git a/doc/index.rst b/doc/index.rst
index 420cb1e3ef077cf83e3fad645452d9382c60f594..40d49998c3aa71b86ccbc3e56b0ab474842f26ad 100644
--- a/doc/index.rst
+++ b/doc/index.rst
@@ -97,6 +97,16 @@ Reference Manual
py_api
+References
+==========
+
+.. [TP91] *M. Turk and A. Pentland*. **Eigenfaces for recognition**. Journal of Cognitive Neuroscience, 3(1):71-86, 1991.
+.. [ZKC+98] *W. Zhao, A. Krishnaswamy, R. Chellappa, D. Swets and J. Weng*. **Discriminant analysis of principal components for face recognition**, pages 73-85. Springer Verlag Berlin, 1998.
+.. [MWP98] *B. Moghaddam, W. Wahid and A. Pentland*. **Beyond eigenfaces: probabilistic matching for face recognition**. IEEE International Conference on Automatic Face and Gesture Recognition, pages 30-35. 1998.
+.. [GW09] *M. Günther and R.P. Würtz*. **Face detection and recognition using maximum likelihood classifiers on Gabor graphs**. International Journal of Pattern Recognition and Artificial Intelligence, 23(3):433-461, 2009.
+
+
+
Indices and tables
==================
diff --git a/doc/py_api.rst b/doc/py_api.rst
index b0fb15d08173ffbec91bd1be26b4cbbd5e7e25b8..1b1b4f65ad53c8c5a9d245f3b24fb81a2f951b3b 100644
--- a/doc/py_api.rst
+++ b/doc/py_api.rst
@@ -181,6 +181,14 @@ Details
.. automodule:: bob.bio.base
+.. automodule:: bob.bio.base.annotator
+.. automodule:: bob.bio.base.pipelines
+.. automodule:: bob.bio.base.pipelines.vanilla_biometrics
+.. automodule:: bob.bio.base.database
+.. automodule:: bob.bio.base.preprocessor
+.. automodule:: bob.bio.base.extractor
+.. automodule:: bob.bio.base.transformers
+.. automodule:: bob.bio.base.algorithm
.. automodule:: bob.bio.base.score.load
.. automodule:: bob.bio.base.script.figure
.. automodule:: bob.bio.base.script.commands