Reorganized the examples

bob/bio/base/config/examples/lda_atnt_legacy.py

 # from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector, AlgorithmAdaptor
 
-import bob.db.atnt
+import bob.bio.base
+import bob.bio.face
+
+## DATABASE
+
 from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector
+database = DatabaseConnector(bob.bio.face.database.AtntBioDatabase(original_directory="./atnt"), protocol="Default")
 
-database = DatabaseConnector(bob.db.atnt.Database(), protocol="Default")
 
 from sklearn.pipeline import Pipeline, make_pipeline
-from sklearn.decomposition import PCA
-
 from bob.pipelines.mixins import CheckpointMixin, SampleMixin
-from bob.bio.base.mixins import CheckpointSampleLinearize
 from bob.bio.base.mixins.legacy import LegacyProcessorMixin, LegacyAlgorithmMixin
-
-
-class CheckpointSamplePCA(CheckpointMixin, SampleMixin, PCA):
-    """
-    Enables SAMPLE and CHECKPOINTIN handling for https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html
-    """
-
-    pass
+from bob.bio.base.transformers import CheckpointSampleLinearize, CheckpointSamplePCA
 
 
 #### PREPROCESSOR LEGACY ###
@@ -68,7 +62,7 @@ extractor = Pipeline(
     ]
 )
 
-extractor = dask_it(extractor)
+#extractor = dask_it(extractor)
 
 from bob.bio.base.pipelines.vanilla_biometrics.biometric_algorithm import (
     Distance,

bob/bio/base/config/examples/lda_atnt_legacy_all_legacy.py

 # from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector, AlgorithmAdaptor
 
-import bob.db.atnt
+import bob.bio.base
+import bob.bio.face
+
+## DATABASE
+
 from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector
+database = DatabaseConnector(bob.bio.face.database.AtntBioDatabase(original_directory="./atnt"), protocol="Default")
 
-database = DatabaseConnector(bob.db.atnt.Database(), protocol="Default")
 
 from sklearn.pipeline import Pipeline, make_pipeline
-from sklearn.decomposition import PCA
-
 from bob.pipelines.mixins import CheckpointMixin, SampleMixin
-from bob.bio.base.mixins import CheckpointSampleLinearize
 from bob.bio.base.mixins.legacy import LegacyProcessorMixin, LegacyAlgorithmMixin
+from bob.bio.base.transformers import CheckpointSampleLinearize, CheckpointSamplePCA
 from bob.bio.base.pipelines.vanilla_biometrics.legacy import LegacyBiometricAlgorithm
 
 
-class CheckpointSamplePCA(CheckpointMixin, SampleMixin, PCA):
-    """
-    Enables SAMPLE and CHECKPOINTIN handling for https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html
-    """
-
-    pass
-
-
 #### PREPROCESSOR LEGACY ###
 import functools
 

bob/bio/base/config/examples/pca_atnt.py

 #from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector, AlgorithmAdaptor
 
-import bob.db.atnt
+import bob.bio.face
 from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector
-database = DatabaseConnector(bob.db.atnt.Database(), protocol="Default")
+database = DatabaseConnector(bob.bio.face.database.AtntBioDatabase(original_directory="./atnt"), protocol="Default")
 
 from sklearn.pipeline import Pipeline, make_pipeline
-from sklearn.decomposition import PCA
-
 from bob.pipelines.mixins import CheckpointMixin, SampleMixin
-from bob.bio.base.mixins import CheckpointSampleLinearize
+from bob.bio.base.transformers import CheckpointSampleLinearize, CheckpointSamplePCA
 
-class CheckpointSamplePCA(CheckpointMixin, SampleMixin, PCA):
-    """
-    Enables SAMPLE and CHECKPOINTIN handling for https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html
-    """
-    pass
 
-#extractor = make_pipeline([CheckpointSampleLinearize(), CheckpointSamplePCA()])
 from bob.pipelines.mixins import dask_it
 extractor = Pipeline(steps=[('0',CheckpointSampleLinearize(features_dir="./example/extractor0")), 
 	                        ('1',CheckpointSamplePCA(features_dir="./example/extractor1", model_path="./example/pca.pkl"))])

bob/bio/base/config/examples/pca_atnt_legacy.py

 # from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector, AlgorithmAdaptor
 
-import bob.db.atnt
+
+### DATABASE
+import bob.bio.face
 from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector
+database = DatabaseConnector(bob.bio.face.database.AtntBioDatabase(original_directory="./atnt"), protocol="Default")
 
-database = DatabaseConnector(bob.db.atnt.Database(), protocol="Default")
 
 from sklearn.pipeline import Pipeline, make_pipeline
-from sklearn.decomposition import PCA
-
 from bob.pipelines.mixins import CheckpointMixin, SampleMixin
-from bob.bio.base.mixins import CheckpointSampleLinearize
-from bob.bio.base.mixins.legacy import LegacyProcessorMixin
-
-
-class CheckpointSamplePCA(CheckpointMixin, SampleMixin, PCA):
-    """
-    Enables SAMPLE and CHECKPOINTIN handling for https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html
-    """
-
-    pass
+from bob.bio.base.mixins.legacy import LegacyProcessorMixin, LegacyAlgorithmMixin
+from bob.bio.base.transformers import CheckpointSampleLinearize, CheckpointSamplePCA
 
 
 #### PREPROCESSOR LEGACY ###
@@ -48,7 +40,6 @@ face_cropper = functools.partial(
 
 
 from bob.pipelines.mixins import mix_me_up
-
 preprocessor = mix_me_up((CheckpointMixin, SampleMixin), LegacyProcessorMixin)
 
 from bob.pipelines.mixins import dask_it
@@ -75,7 +66,5 @@ from bob.bio.base.pipelines.vanilla_biometrics.biometric_algorithm import (
 
 class CheckpointDistance(BiometricAlgorithmCheckpointMixin, Distance):
     pass
-
-
 algorithm = CheckpointDistance(features_dir="./example/")
 # algorithm = Distance()

bob/bio/base/config/examples/pca_mobio-male.py

@@ -7,12 +7,15 @@ import bob.bio.face
 
 from bob.bio.base.mixins.legacy import LegacyProcessorMixin, LegacyAlgorithmMixin
 from bob.bio.base.pipelines.vanilla_biometrics.legacy import LegacyBiometricAlgorithm
+from bob.bio.base.transformers import CheckpointSamplePCA
 
 import os
-base_dir = "/idiap/temp/tpereira/mobio/pca"
-#base_dir = "./example"
+#base_dir = "/idiap/temp/tpereira/mobio/pca"
+base_dir = "./example"
 
 
+### DATABASE
+
 original_directory=rc['bob.db.mobio.directory']
 annotation_directory=rc['bob.db.mobio.annotation_directory']
 database = DatabaseConnectorAnnotated(bob.bio.face.database.mobio.MobioBioDatabase(
@@ -26,13 +29,8 @@ from sklearn.pipeline import Pipeline, make_pipeline
 from sklearn.decomposition import PCA
 
 from bob.pipelines.mixins import CheckpointMixin, SampleMixin
-from bob.bio.base.mixins import CheckpointSampleLinearize
+from bob.bio.base.transformers import CheckpointSampleLinearize
 
-class CheckpointSamplePCA(CheckpointMixin, SampleMixin, PCA):
-    """
-    Enables SAMPLE and CHECKPOINTIN handling for https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html
-    """
-    pass
 
 
 
@@ -63,10 +61,9 @@ extractor = Pipeline(steps=[
                             ('1',CheckpointSampleLinearize(features_dir=os.path.join(base_dir,"extractor1"))), 
 	                        ('2',CheckpointSamplePCA(features_dir=os.path.join(base_dir,"extractor2"), model_path=os.path.join(base_dir,"pca.pkl")))
 	                       ])
-extractor = dask_it(extractor, npartitions=48)
+#extractor = dask_it(extractor, npartitions=48)
 
 from bob.bio.base.pipelines.vanilla_biometrics.biometric_algorithm import Distance, BiometricAlgorithmCheckpointMixin
 
 class CheckpointDistance(BiometricAlgorithmCheckpointMixin, Distance):  pass
 algorithm = CheckpointDistance(features_dir=base_dir)
-#algorithm = Distance()

bob/bio/base/pipelines/vanilla_biometrics/biometric_algorithm.py

@@ -135,7 +135,6 @@ class BiometricAlgorithm(object):
         for subprobe_id, (s, parent) in enumerate(zip(data, sampleset.samples)):
             # Creating one sample per comparison
             subprobe_scores = []
-
             for ref in [
                 r for r in biometric_references if r.key in sampleset.references
             ]:

bob/bio/base/pipelines/vanilla_biometrics/legacy.py

@@ -186,7 +186,7 @@ class DatabaseConnector:
                         references=[str(m)],
                     )
                 else:
-                    probes[o.id].references.append(m)
+                    probes[o.id].references.append(str(m))
 
         return list(probes.values())