diff --git a/bob/bio/face/config/baseline/arcface_insightface.py b/bob/bio/face/config/baseline/arcface_insightface.py
index b2de000f4d30dbbbdc7c34592f19b249e69b976c..db164c301c785c23be4be2710351d9436b84f18b 100644
--- a/bob/bio/face/config/baseline/arcface_insightface.py
+++ b/bob/bio/face/config/baseline/arcface_insightface.py
@@ -1,7 +1,8 @@
from bob.bio.face.embeddings.mxnet_models import ArcFaceInsightFace
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_112x112,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
@@ -12,10 +13,22 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- transformer = embedding_transformer_112x112(
- ArcFaceInsightFace(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # DEFINE CROPPING
+ cropped_image_size = (112, 112)
+ if annotation_type == "eyes-center":
+ # Hard coding eye positions for backward consistency
+ cropped_positions = {
+ "leye": (55, 81),
+ "reye": (55, 42),
+ }
+ else:
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=ArcFaceInsightFace(memory_demanding=memory_demanding),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
color_channel="rgb",
)
diff --git a/bob/bio/face/config/baseline/facenet_sanderberg.py b/bob/bio/face/config/baseline/facenet_sanderberg.py
index 20e3651aab7a2701e5b670481beb46e6126e4b79..bdefacb8c1c1ea1167c86c8077fc17c8555aa35c 100644
--- a/bob/bio/face/config/baseline/facenet_sanderberg.py
+++ b/bob/bio/face/config/baseline/facenet_sanderberg.py
@@ -2,9 +2,11 @@ from bob.bio.face.embeddings.tf2_inception_resnet import (
FaceNetSanderberg_20170512_110547,
)
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_160x160,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
+
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
VanillaBiometricsPipeline,
@@ -14,12 +16,20 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
+ # DEFINE CROPPING
+ cropped_image_size = (160, 160)
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
- transformer = embedding_transformer_160x160(
- FaceNetSanderberg_20170512_110547(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # ASSEMBLE TRANSFORMER
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=FaceNetSanderberg_20170512_110547(memory_demanding=memory_demanding),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
+ annotator="mtcnn",
)
+
algorithm = Distance()
return VanillaBiometricsPipeline(transformer, algorithm)
diff --git a/bob/bio/face/config/baseline/helpers.py b/bob/bio/face/config/baseline/helpers.py
index 070ac4ddeb1a3daa0f6d750c55fd074af0d80e36..0e0aefecd11d7f325fc390e1fb19bcebe1ce7340 100644
--- a/bob/bio/face/config/baseline/helpers.py
+++ b/bob/bio/face/config/baseline/helpers.py
@@ -27,10 +27,10 @@ def lookup_config_from_database():
return annotation_type, fixed_positions, memory_demanding
-def embedding_transformer_default_cropping(cropped_image_size, annotation_type):
+def dnn_default_cropping(cropped_image_size, annotation_type):
"""
- Computes the default cropped positions for the FaceCropper used with Facenet-like
- Embedding extractors, proportionally to the target image size
+ Computes the default cropped positions for the FaceCropper used with Neural-Net based
+ extractors, proportionally to the target image size
Parameters
@@ -51,8 +51,7 @@ def embedding_transformer_default_cropping(cropped_image_size, annotation_type):
"""
if isinstance(annotation_type, list):
return [
- embedding_transformer_default_cropping(cropped_image_size, item)
- for item in annotation_type
+ dnn_default_cropping(cropped_image_size, item) for item in annotation_type
]
CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH = cropped_image_size
@@ -175,7 +174,6 @@ def legacy_default_cropping(cropped_image_size, annotation_type):
def make_cropper(
cropped_image_size,
- annotation_type,
cropped_positions,
fixed_positions=None,
color_channel="rgb",
@@ -183,12 +181,12 @@ def make_cropper(
):
face_cropper = face_crop_solver(
- cropped_image_size,
- color_channel=color_channel,
+ cropped_image_size=cropped_image_size,
cropped_positions=cropped_positions,
fixed_positions=fixed_positions,
- dtype="float64",
annotator=annotator,
+ color_channel=color_channel,
+ dtype="float64",
)
transform_extra_arguments = (
@@ -203,10 +201,10 @@ def make_cropper(
def embedding_transformer(
cropped_image_size,
embedding,
- annotation_type,
cropped_positions,
fixed_positions=None,
color_channel="rgb",
+ annotator=None,
):
"""
Creates a pipeline composed by and FaceCropper and an Embedding extractor.
@@ -216,18 +214,12 @@ def embedding_transformer(
This will resize images to the requested `image_size`
"""
- face_cropper = face_crop_solver(
- cropped_image_size,
- color_channel=color_channel,
+ face_cropper, transform_extra_arguments = make_cropper(
+ cropped_image_size=cropped_image_size,
cropped_positions=cropped_positions,
fixed_positions=fixed_positions,
- dtype="float64",
- )
-
- transform_extra_arguments = (
- None
- if (cropped_positions is None or fixed_positions is not None)
- else (("annotations", "annotations"),)
+ color_channel=color_channel,
+ annotator=annotator,
)
transformer = make_pipeline(
@@ -242,66 +234,6 @@ def embedding_transformer(
return transformer
-def embedding_transformer_160x160(
- embedding, annotation_type, fixed_positions, color_channel="rgb"
-):
- """
- Creates a pipeline composed by and FaceCropper and an Embedding extractor.
- This transformer is suited for Facenet based architectures
-
- .. warning::
- This will resize images to :math:`160 \times 160`
-
- """
- cropped_positions = embedding_transformer_default_cropping(
- (160, 160), annotation_type
- )
-
- return embedding_transformer(
- (160, 160),
- embedding,
- annotation_type,
- cropped_positions,
- fixed_positions,
- color_channel=color_channel,
- )
-
-
-def embedding_transformer_112x112(
- embedding, annotation_type, fixed_positions, color_channel="rgb"
-):
- """
- Creates a pipeline composed by and FaceCropper and an Embedding extractor.
- This transformer is suited for Facenet based architectures
-
- .. warning::
- This will resize images to :math:`112 \times 112`
-
- """
- cropped_image_size = (112, 112)
- if annotation_type == "eyes-center":
- # Hard coding eye positions for backward consistency
- cropped_positions = {
- "leye": (55, 81),
- "reye": (55, 42),
- }
-
- else:
- # Will use default
- cropped_positions = embedding_transformer_default_cropping(
- cropped_image_size, annotation_type
- )
-
- return embedding_transformer(
- cropped_image_size,
- embedding,
- annotation_type,
- cropped_positions,
- fixed_positions,
- color_channel=color_channel,
- )
-
-
def embedding_transformer_224x224(
embedding, annotation_type, fixed_positions, color_channel="rgb"
):
@@ -319,15 +251,12 @@ def embedding_transformer_224x224(
cropped_positions = {"leye": (65, 150), "reye": (65, 77)}
else:
# Will use default
- cropped_positions = embedding_transformer_default_cropping(
- cropped_image_size, annotation_type
- )
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
return embedding_transformer(
- cropped_image_size,
- embedding,
- annotation_type,
- cropped_positions,
- fixed_positions,
+ cropped_image_size=cropped_image_size,
+ embedding=embedding,
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
color_channel=color_channel,
)
diff --git a/bob/bio/face/config/baseline/inception_resnetv1_casiawebface.py b/bob/bio/face/config/baseline/inception_resnetv1_casiawebface.py
index 90bd0111248cfd6ebd07bb7f9eb7642b44f41c11..b532c815b07fe09cf307a8f267569585273fec10 100644
--- a/bob/bio/face/config/baseline/inception_resnetv1_casiawebface.py
+++ b/bob/bio/face/config/baseline/inception_resnetv1_casiawebface.py
@@ -2,8 +2,9 @@ from bob.bio.face.embeddings.tf2_inception_resnet import (
InceptionResnetv1_Casia_CenterLoss_2018,
)
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_160x160,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
@@ -14,10 +15,20 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- transformer = embedding_transformer_160x160(
- InceptionResnetv1_Casia_CenterLoss_2018(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # DEFINE CROPPING
+ cropped_image_size = (160, 160)
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ # ASSEMBLE TRANSFORMER
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=InceptionResnetv1_Casia_CenterLoss_2018(
+ memory_demanding=memory_demanding
+ ),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
+ annotator="mtcnn",
)
algorithm = Distance()
diff --git a/bob/bio/face/config/baseline/inception_resnetv1_msceleb.py b/bob/bio/face/config/baseline/inception_resnetv1_msceleb.py
index c459709626a019701667d3276ad06e1f8873d6a8..db94eddd46344b6b48f569fc51c2ee375fdb6996 100644
--- a/bob/bio/face/config/baseline/inception_resnetv1_msceleb.py
+++ b/bob/bio/face/config/baseline/inception_resnetv1_msceleb.py
@@ -2,8 +2,9 @@ from bob.bio.face.embeddings.tf2_inception_resnet import (
InceptionResnetv1_MsCeleb_CenterLoss_2018,
)
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_160x160,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
@@ -14,10 +15,20 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- transformer = embedding_transformer_160x160(
- InceptionResnetv1_MsCeleb_CenterLoss_2018(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # DEFINE CROPPING
+ cropped_image_size = (160, 160)
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ # ASSEMBLE TRANSFORMER
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=InceptionResnetv1_MsCeleb_CenterLoss_2018(
+ memory_demanding=memory_demanding
+ ),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
+ annotator="mtcnn",
)
algorithm = Distance()
diff --git a/bob/bio/face/config/baseline/inception_resnetv2_casiawebface.py b/bob/bio/face/config/baseline/inception_resnetv2_casiawebface.py
index cb82dee8f8e1f4a516721fd33f06a984a30b65f5..c20d856c366f263634eecf7987e66db8aeb737f5 100644
--- a/bob/bio/face/config/baseline/inception_resnetv2_casiawebface.py
+++ b/bob/bio/face/config/baseline/inception_resnetv2_casiawebface.py
@@ -2,8 +2,9 @@ from bob.bio.face.embeddings.tf2_inception_resnet import (
InceptionResnetv2_Casia_CenterLoss_2018,
)
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_160x160,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
@@ -14,10 +15,20 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- transformer = embedding_transformer_160x160(
- InceptionResnetv2_Casia_CenterLoss_2018(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # DEFINE CROPPING
+ cropped_image_size = (160, 160)
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ # ASSEMBLE TRANSFORMER
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=InceptionResnetv2_Casia_CenterLoss_2018(
+ memory_demanding=memory_demanding
+ ),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
+ annotator="mtcnn",
)
algorithm = Distance()
diff --git a/bob/bio/face/config/baseline/inception_resnetv2_msceleb.py b/bob/bio/face/config/baseline/inception_resnetv2_msceleb.py
index fa502308c7629ba3d2d8487582cce6428603c4eb..d44585ebe97b16a075dcf194143eb92c02c6d5fa 100644
--- a/bob/bio/face/config/baseline/inception_resnetv2_msceleb.py
+++ b/bob/bio/face/config/baseline/inception_resnetv2_msceleb.py
@@ -2,8 +2,9 @@ from bob.bio.face.embeddings.tf2_inception_resnet import (
InceptionResnetv2_MsCeleb_CenterLoss_2018,
)
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_160x160,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
@@ -14,10 +15,20 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- transformer = embedding_transformer_160x160(
- InceptionResnetv2_MsCeleb_CenterLoss_2018(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # DEFINE CROPPING
+ cropped_image_size = (160, 160)
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ # ASSEMBLE TRANSFORMER
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=InceptionResnetv2_MsCeleb_CenterLoss_2018(
+ memory_demanding=memory_demanding
+ ),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
+ annotator="mtcnn",
)
algorithm = Distance()
diff --git a/bob/bio/face/config/baseline/mobilenetv2_msceleb_arcface_2021.py b/bob/bio/face/config/baseline/mobilenetv2_msceleb_arcface_2021.py
index aae95a2a7d5aed639dba7c308b1d54cbb89e99b8..2ca17ebeda8e954ffb45e85beb36911d673aeb92 100644
--- a/bob/bio/face/config/baseline/mobilenetv2_msceleb_arcface_2021.py
+++ b/bob/bio/face/config/baseline/mobilenetv2_msceleb_arcface_2021.py
@@ -1,7 +1,8 @@
from bob.bio.face.embeddings.mobilenet_v2 import MobileNetv2_MsCeleb_ArcFace_2021
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_112x112,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
@@ -12,10 +13,23 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- transformer = embedding_transformer_112x112(
- MobileNetv2_MsCeleb_ArcFace_2021(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # DEFINE CROPPING
+ cropped_image_size = (112, 112)
+ if annotation_type == "eyes-center":
+ # Hard coding eye positions for backward consistency
+ cropped_positions = {
+ "leye": (55, 81),
+ "reye": (55, 42),
+ }
+ else:
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=MobileNetv2_MsCeleb_ArcFace_2021(memory_demanding=memory_demanding),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
)
algorithm = Distance()
diff --git a/bob/bio/face/config/baseline/resnet50_msceleb_arcface_2021.py b/bob/bio/face/config/baseline/resnet50_msceleb_arcface_2021.py
index f60903ace50188014553d8a6d25ebc06ef0cdbd4..c505666297de735a746dc362388d4946ee1bd398 100644
--- a/bob/bio/face/config/baseline/resnet50_msceleb_arcface_2021.py
+++ b/bob/bio/face/config/baseline/resnet50_msceleb_arcface_2021.py
@@ -1,8 +1,10 @@
from bob.bio.face.embeddings.resnet50 import Resnet50_MsCeleb_ArcFace_2021
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_112x112,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
+
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
VanillaBiometricsPipeline,
@@ -12,10 +14,23 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- transformer = embedding_transformer_112x112(
- Resnet50_MsCeleb_ArcFace_2021(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # DEFINE CROPPING
+ cropped_image_size = (112, 112)
+ if annotation_type == "eyes-center":
+ # Hard coding eye positions for backward consistency
+ cropped_positions = {
+ "leye": (55, 81),
+ "reye": (55, 42),
+ }
+ else:
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=Resnet50_MsCeleb_ArcFace_2021(memory_demanding=memory_demanding),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
)
algorithm = Distance()
diff --git a/bob/bio/face/config/baseline/resnet50_vgg2_arcface_2021.py b/bob/bio/face/config/baseline/resnet50_vgg2_arcface_2021.py
index 0a6941d0e9c670a65dc7605dac0c5f38bc5b1788..05eaa49bc610ad3fc5aecbcc6a23977897e96890 100644
--- a/bob/bio/face/config/baseline/resnet50_vgg2_arcface_2021.py
+++ b/bob/bio/face/config/baseline/resnet50_vgg2_arcface_2021.py
@@ -1,7 +1,8 @@
from bob.bio.face.embeddings.resnet50 import Resnet50_VGG2_ArcFace_2021
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_112x112,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
from bob.bio.base.pipelines.vanilla_biometrics import (
Distance,
@@ -12,10 +13,23 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- transformer = embedding_transformer_112x112(
- Resnet50_VGG2_ArcFace_2021(memory_demanding=memory_demanding),
- annotation_type,
- fixed_positions,
+ # DEFINE CROPPING
+ cropped_image_size = (112, 112)
+ if annotation_type == "eyes-center":
+ # Hard coding eye positions for backward consistency
+ cropped_positions = {
+ "leye": (55, 81),
+ "reye": (55, 42),
+ }
+ else:
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=Resnet50_VGG2_ArcFace_2021(memory_demanding=memory_demanding),
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
)
algorithm = Distance()
diff --git a/bob/bio/face/config/baseline/tf2_inception_resnet.py b/bob/bio/face/config/baseline/tf2_inception_resnet.py
index f71e0a78bdd43a141028687b0e7acd70ee70cabb..619bcf82a093dfa60fb7bc2364ada55d5c983f65 100644
--- a/bob/bio/face/config/baseline/tf2_inception_resnet.py
+++ b/bob/bio/face/config/baseline/tf2_inception_resnet.py
@@ -2,9 +2,9 @@ from bob.extension import rc
from bob.bio.face.embeddings.tf2_inception_resnet import InceptionResnetv2
from bob.bio.face.preprocessor import FaceCrop
from bob.bio.face.config.baseline.helpers import (
- embedding_transformer_default_cropping,
- embedding_transformer,
lookup_config_from_database,
+ dnn_default_cropping,
+ embedding_transformer,
)
from sklearn.pipeline import make_pipeline
@@ -18,23 +18,22 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
def load(annotation_type, fixed_positions=None):
- CROPPED_IMAGE_SIZE = (160, 160)
- CROPPED_POSITIONS = embedding_transformer_default_cropping(
- CROPPED_IMAGE_SIZE, annotation_type=annotation_type
- )
+ # DEFINE CROPPING
+ cropped_image_size = (160, 160)
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
extractor_path = rc["bob.bio.face.tf2.casia-webface-inception-v2"]
-
embedding = InceptionResnetv2(
checkpoint_path=extractor_path, memory_demanding=memory_demanding
)
-
+ # ASSEMBLE TRANSFORMER
transformer = embedding_transformer(
- CROPPED_IMAGE_SIZE,
- embedding,
- annotation_type,
- CROPPED_POSITIONS,
- fixed_positions,
+ cropped_image_size=cropped_image_size,
+ embedding=embedding,
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
+ annotator="mtcnn",
)
algorithm = Distance()