diff --git a/bob/bio/face/config/baseline/pytorch_pipe_v2.py b/bob/bio/face/config/baseline/pytorch_pipe_v2.py
index 8cb2af0f71f2453e6b5631fb95c226edd5292c8b..630609e6fb22085783fa8c977ddc9702615d3364 100644
--- a/bob/bio/face/config/baseline/pytorch_pipe_v2.py
+++ b/bob/bio/face/config/baseline/pytorch_pipe_v2.py
@@ -24,28 +24,38 @@ else:
fixed_positions = None
+cropped_positions = {"leye": (49, 72), "reye": (49, 38)}
-cropped_positions={'leye':(49,72), 'reye':(49,38)}
-
-preprocessor_transformer = FaceCrop(cropped_image_size=(224,224), cropped_positions={'leye':(49,72), 'reye':(49,38)}, color_channel='rgb',fixed_positions=fixed_positions)
-
-transform_extra_arguments = (None if (cropped_positions is None or fixed_positions is not None) else (("annotations", "annotations"),))
-
+preprocessor_transformer = FaceCrop(
+ cropped_image_size=(224, 224),
+ cropped_positions={"leye": (49, 72), "reye": (49, 38)},
+ color_channel="rgb",
+ fixed_positions=fixed_positions,
+)
+transform_extra_arguments = (
+ None
+ if (cropped_positions is None or fixed_positions is not None)
+ else (("annotations", "annotations"),)
+)
-model = InceptionResnetV1(pretrained='vggface2').eval()
+model = InceptionResnetV1(pretrained="vggface2").eval()
extractor_transformer = pytorch_library_model(model=model)
-
-
-algorithm = Distance(distance_function = scipy.spatial.distance.cosine,is_distance_function = True)
+algorithm = Distance(
+ distance_function=scipy.spatial.distance.cosine, is_distance_function=True
+)
# Chain the Transformers together
transformer = make_pipeline(
- wrap(["sample"], preprocessor_transformer,transform_extra_arguments=transform_extra_arguments),
+ wrap(
+ ["sample"],
+ preprocessor_transformer,
+ transform_extra_arguments=transform_extra_arguments,
+ ),
wrap(["sample"], extractor_transformer)
# Add more transformers here if needed
)
@@ -54,63 +64,3 @@ transformer = make_pipeline(
# Assemble the Vanilla Biometric pipeline and execute
pipeline = VanillaBiometricsPipeline(transformer, algorithm)
transformer = pipeline.transformer
-<<<<<<< HEAD
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-=======
->>>>>>> â€newâ€
diff --git a/bob/bio/face/extractor/opencv_caffe.py b/bob/bio/face/extractor/opencv_caffe.py
index d816e0421b514e8623972b5375df7036fe91c039..7634e4c13a870d297119515ae219678372759916 100644
--- a/bob/bio/face/extractor/opencv_caffe.py
+++ b/bob/bio/face/extractor/opencv_caffe.py
@@ -84,6 +84,7 @@ class opencv_model(TransformerMixin, BaseEstimator):
"""
if self.model is None:
+
self._load_model()
img = np.array(X)
@@ -100,4 +101,5 @@ class opencv_model(TransformerMixin, BaseEstimator):
return d
def _more_tags(self):
+
return {"stateless": True, "requires_fit": False}
diff --git a/bob/bio/face/extractor/pytorch_model.py b/bob/bio/face/extractor/pytorch_model.py
index 96a57cb9e1f45cd2a85a643146e69b3d873e787a..d784d7f48e6cd9c6eae1607b2a103940a01edfb7 100644
--- a/bob/bio/face/extractor/pytorch_model.py
+++ b/bob/bio/face/extractor/pytorch_model.py
@@ -80,7 +80,7 @@ class pytorch_loaded_model(TransformerMixin, BaseEstimator):
"""
if self.model is None:
- self.load_model()
+ self._load_model()
X = torch.Tensor(X)
@@ -94,6 +94,7 @@ class pytorch_loaded_model(TransformerMixin, BaseEstimator):
return d
def _more_tags(self):
+
return {"stateless": True, "requires_fit": False}
diff --git a/bob/bio/face/extractor/tf_model.py b/bob/bio/face/extractor/tf_model.py
index 001410786ae28278fea055c212bd9d5bd6a31972..ae39ebb45f65cd8601715f2de88e890c727df245 100644
--- a/bob/bio/face/extractor/tf_model.py
+++ b/bob/bio/face/extractor/tf_model.py
@@ -74,7 +74,7 @@ class tf_model(TransformerMixin, BaseEstimator):
"""
if self.model is None:
- self.load_model()
+ self._load_model()
X = check_array(X, allow_nd=True)
X = tf.convert_to_tensor(X)
diff --git a/doc/references.rst b/doc/references.rst
index 28b98d5f0cbb37e59bfb9f9623b31b966493ed85..bbb5417a0b6d3bf20a07c65c115921c57437ff0f 100644
--- a/doc/references.rst
+++ b/doc/references.rst
@@ -17,4 +17,4 @@ References
.. [ZSQ09] *W. Zhang, S. Shan, L. Qing, X. Chen and W. Gao*. **Are Gabor phases really useless for face recognition?** Pattern Analysis & Applications, 12:301-307, 2009.
.. [TFP18] de Freitas Pereira, Tiago, André Anjos, and Sébastien Marcel. "Heterogeneous face recognition using domain specific units." IEEE Transactions on Information Forensics and Security 14.7 (2018): 1803-1816.
.. [HRM06] *G. Heusch, Y. Rodriguez, and S. Marcel*. **Local Binary Patterns as an Image Preprocessing for Face Authentication**. In IEEE International Conference on Automatic Face and Gesture Recognition (AFGR), 2006.
-.. [LGB18] *C. Li, M. Gunther and T. E. Boult*. **ECLIPSE: Ensembles of Centroids Leveraging Iteratively Processed Spatial Eclipse Clustering**. 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe, NV, USA, 2018, pp. 131-140, doi: 10.1109/WACV.2018.00021.
+.. [LGB18] *C. Li, M. Gunther and T. E. Boult*. **ECLIPSE: Ensembles of Centroids Leveraging Iteratively Processed Spatial Eclipse Clustering**. 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe, NV, USA, 2018, pp. 131-140, doi: 10.1109/WACV.2018.00021.
\ No newline at end of file