diff --git a/bob/bio/face/config/baseline/gabor_graph.py b/bob/bio/face/config/baseline/gabor_graph.py
index 6c79bffd407e26b327ca22574ba9f5c08b84b7a8..777f4ab1eac8c1931b5924c4f22cf9bee8790e88 100644
--- a/bob/bio/face/config/baseline/gabor_graph.py
+++ b/bob/bio/face/config/baseline/gabor_graph.py
@@ -3,7 +3,11 @@ from bob.bio.base.pipelines.vanilla_biometrics import (
VanillaBiometricsPipeline,
BioAlgorithmLegacy,
)
-from bob.bio.face.config.baseline.helpers import crop_80x64, lookup_config_from_database
+from bob.bio.face.config.baseline.helpers import (
+ lookup_config_from_database,
+ legacy_default_cropping,
+ make_cropper,
+)
import math
import numpy as np
import bob.bio.face
@@ -20,14 +24,6 @@ logger = logging.getLogger(__name__)
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
-def get_cropper(annotation_type, fixed_positions=None):
- # Cropping
- face_cropper, transform_extra_arguments = crop_80x64(
- annotation_type, fixed_positions, color_channel="gray"
- )
- return face_cropper, transform_extra_arguments
-
-
def get_pipeline(face_cropper, transform_extra_arguments):
preprocessor = bob.bio.face.preprocessor.INormLBP(
face_cropper=face_cropper, dtype=np.float64
@@ -75,9 +71,22 @@ def get_pipeline(face_cropper, transform_extra_arguments):
def load(annotation_type, fixed_positions=None):
####### SOLVING THE FACE CROPPER TO BE USED ##########
- face_cropper, transform_extra_arguments = get_cropper(
- annotation_type, fixed_positions
+
+ # Define cropped positions
+ CROPPED_IMAGE_HEIGHT = 80
+ CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
+ cropped_image_size = (CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH)
+ cropped_positions = legacy_default_cropping(cropped_image_size, annotation_type)
+
+ # Cropping
+ face_cropper, transform_extra_arguments = make_cropper(
+ cropped_image_size=cropped_image_size,
+ annotation_type=annotation_type,
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="gray",
)
+
return get_pipeline(face_cropper, transform_extra_arguments)
diff --git a/bob/bio/face/config/baseline/helpers.py b/bob/bio/face/config/baseline/helpers.py
index 41f3e837841dfc6716e3ca82b07d7eb6983dea76..070ac4ddeb1a3daa0f6d750c55fd074af0d80e36 100644
--- a/bob/bio/face/config/baseline/helpers.py
+++ b/bob/bio/face/config/baseline/helpers.py
@@ -173,6 +173,33 @@ def legacy_default_cropping(cropped_image_size, annotation_type):
return cropped_positions
+def make_cropper(
+ cropped_image_size,
+ annotation_type,
+ cropped_positions,
+ fixed_positions=None,
+ color_channel="rgb",
+ annotator=None,
+):
+
+ face_cropper = face_crop_solver(
+ cropped_image_size,
+ color_channel=color_channel,
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ dtype="float64",
+ annotator=annotator,
+ )
+
+ transform_extra_arguments = (
+ None
+ if (cropped_positions is None or fixed_positions is not None)
+ else (("annotations", "annotations"),)
+ )
+
+ return face_cropper, transform_extra_arguments
+
+
def embedding_transformer(
cropped_image_size,
embedding,
@@ -304,58 +331,3 @@ def embedding_transformer_224x224(
fixed_positions,
color_channel=color_channel,
)
-
-
-def crop_80x64(annotation_type, fixed_positions=None, color_channel="gray"):
- """
- Crops a face to :math:`80 \times 64`
-
-
- Parameters
- ----------
-
- annotation_type: str
- Type of annotations. Possible values are: `bounding-box`, `eyes-center` and None
-
- fixed_positions: tuple
- A tuple containing the annotations. This is used in case your input is already registered
- with fixed positions (eyes or bounding box)
-
- color_channel: str
-
-
- Returns
- -------
-
- face_cropper:
- A face cropper to be used
-
- transform_extra_arguments:
- The parameters to the transformer
-
- """
- color_channel = color_channel
- dtype = np.float64
-
- # Cropping
- CROPPED_IMAGE_HEIGHT = 80
- CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
- cropped_image_size = (CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH)
-
- cropped_positions = legacy_default_cropping(cropped_image_size, annotation_type)
-
- face_cropper = face_crop_solver(
- cropped_image_size,
- color_channel=color_channel,
- cropped_positions=cropped_positions,
- fixed_positions=fixed_positions,
- dtype=dtype,
- )
-
- transform_extra_arguments = (
- None
- if (cropped_positions is None or fixed_positions is not None)
- else (("annotations", "annotations"),)
- )
-
- return face_cropper, transform_extra_arguments
diff --git a/bob/bio/face/config/baseline/lda.py b/bob/bio/face/config/baseline/lda.py
index 062f18f6423734e9e4d7fa4dcbc881a8ec4a093a..ee8877b2b4d841bc48a15ed6c787c2aad9a609c6 100644
--- a/bob/bio/face/config/baseline/lda.py
+++ b/bob/bio/face/config/baseline/lda.py
@@ -3,7 +3,11 @@ from bob.bio.base.pipelines.vanilla_biometrics import (
VanillaBiometricsPipeline,
BioAlgorithmLegacy,
)
-from bob.bio.face.config.baseline.helpers import crop_80x64, lookup_config_from_database
+from bob.bio.face.config.baseline.helpers import (
+ lookup_config_from_database,
+ legacy_default_cropping,
+ make_cropper,
+)
import numpy as np
import bob.bio.face
from sklearn.pipeline import make_pipeline
@@ -24,9 +28,19 @@ annotation_type, fixed_positions, memory_demanding = lookup_config_from_database
####### SOLVING THE FACE CROPPER TO BE USED ##########
def load(annotation_type, fixed_positions=None):
+ # Define cropped positions
+ CROPPED_IMAGE_HEIGHT = 80
+ CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
+ cropped_image_size = (CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH)
+ cropped_positions = legacy_default_cropping(cropped_image_size, annotation_type)
+
# Cropping
- face_cropper, transform_extra_arguments = crop_80x64(
- annotation_type, fixed_positions, color_channel="gray"
+ face_cropper, transform_extra_arguments = make_cropper(
+ cropped_image_size=cropped_image_size,
+ annotation_type=annotation_type,
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="gray",
)
preprocessor = bob.bio.face.preprocessor.TanTriggs(
@@ -57,7 +71,9 @@ def load(annotation_type, fixed_positions=None):
### BIOMETRIC ALGORITHM
algorithm = BioAlgorithmLegacy(
- lda, base_dir=tempdir, projector_file=os.path.join(tempdir, "Projector.hdf5"),
+ lda,
+ base_dir=tempdir,
+ projector_file=os.path.join(tempdir, "Projector.hdf5"),
)
return VanillaBiometricsPipeline(transformer, algorithm)
diff --git a/bob/bio/face/config/baseline/lgbphs.py b/bob/bio/face/config/baseline/lgbphs.py
index 902f43cfd55d3de77ce14f426bce118d1e5ae98d..353bb05413d79ba066b3a9b626c70837497d6532 100644
--- a/bob/bio/face/config/baseline/lgbphs.py
+++ b/bob/bio/face/config/baseline/lgbphs.py
@@ -3,7 +3,11 @@ from bob.bio.base.pipelines.vanilla_biometrics import (
VanillaBiometricsPipeline,
BioAlgorithmLegacy,
)
-from bob.bio.face.config.baseline.helpers import crop_80x64, lookup_config_from_database
+from bob.bio.face.config.baseline.helpers import (
+ lookup_config_from_database,
+ legacy_default_cropping,
+ make_cropper,
+)
import math
import numpy as np
import bob.bio.face
@@ -16,14 +20,6 @@ import bob.math
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
-def get_cropper(annotation_type, fixed_positions=None):
- # Cropping
- face_cropper, transform_extra_arguments = crop_80x64(
- annotation_type, fixed_positions, color_channel="gray"
- )
- return face_cropper, transform_extra_arguments
-
-
def get_pipeline(face_cropper, transform_extra_arguments):
preprocessor = bob.bio.face.preprocessor.TanTriggs(
face_cropper=face_cropper, dtype=np.float64
@@ -65,10 +61,22 @@ def get_pipeline(face_cropper, transform_extra_arguments):
def load(annotation_type, fixed_positions=None):
+ # Define cropped positions
+ CROPPED_IMAGE_HEIGHT = 80
+ CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
+ cropped_image_size = (CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH)
+ cropped_positions = legacy_default_cropping(cropped_image_size, annotation_type)
+
####### SOLVING THE FACE CROPPER TO BE USED ##########
- face_cropper, transform_extra_arguments = get_cropper(
- annotation_type, fixed_positions
+ # Cropping
+ face_cropper, transform_extra_arguments = make_cropper(
+ cropped_image_size=cropped_image_size,
+ annotation_type=annotation_type,
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="gray",
)
+
return get_pipeline(face_cropper, transform_extra_arguments)