From 79e11f301fe0334ba2b23605b965a018e0eaebe4 Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Tue, 22 Dec 2020 15:27:21 +0100
Subject: [PATCH] Fixing the temp directory path for legacy algorithms IF
checkpointing is off
---
bob/bio/face/config/baseline/gabor_graph.py | 11 ++----
bob/bio/face/config/baseline/lda.py | 21 ++++--------
bob/bio/face/config/baseline/lgbphs.py | 37 ++++++++++++---------
3 files changed, 29 insertions(+), 40 deletions(-)
diff --git a/bob/bio/face/config/baseline/gabor_graph.py b/bob/bio/face/config/baseline/gabor_graph.py
index 847ae7a9..1f1a7860 100644
--- a/bob/bio/face/config/baseline/gabor_graph.py
+++ b/bob/bio/face/config/baseline/gabor_graph.py
@@ -70,16 +70,9 @@ def get_pipeline(face_cropper, transform_extra_arguments):
)
# Set default temporary directory
- default_temp = (
- os.path.join("/idiap", "temp", os.environ["USER"])
- if "USER" in os.environ
- else "~/temp"
+ tempdir = bob.bio.base.pipelines.vanilla_biometrics.legacy.get_temp_directory(
+ "gabor_graph"
)
- if os.path.exists(default_temp):
- tempdir = os.path.join(default_temp, "bob_bio_base_tmp")
- else:
- # if /idiap/temp/<USER> does not exist, use /tmp/tmpxxxxxxxx
- tempdir = tempfile.TemporaryDirectory().name
algorithm = BioAlgorithmLegacy(gabor_jet, base_dir=tempdir)
return VanillaBiometricsPipeline(transformer, algorithm)
diff --git a/bob/bio/face/config/baseline/lda.py b/bob/bio/face/config/baseline/lda.py
index 4c45fcc3..1343f51a 100644
--- a/bob/bio/face/config/baseline/lda.py
+++ b/bob/bio/face/config/baseline/lda.py
@@ -38,18 +38,10 @@ def load(annotation_type, fixed_positions=None):
face_cropper=face_cropper, dtype=np.float64
)
-
#### FEATURE EXTRACTOR ######
# Set default temporary directory
- user_env_var = os.getenv("USER", None)
- if user_env_var:
- default_temp = os.path.join("/idiap","temp",user_env_var)
- if user_env_var and os.path.exists(default_temp):
- tempdir = os.path.join(default_temp, "bob_bio_base_tmp", "lda")
- else:
- # if /idiap/temp/<USER> does not exist, use /tmp/tmpxxxxxxxx
- tempdir = tempfile.TemporaryDirectory().name
+ tempdir = bob.bio.base.pipelines.vanilla_biometrics.legacy.get_temp_directory("lda")
lda = bob.bio.base.algorithm.LDA(use_pinv=True, pca_subspace_dimension=0.90)
@@ -57,26 +49,25 @@ def load(annotation_type, fixed_positions=None):
lda, projector_file=os.path.join(tempdir, "Projector.hdf5")
)
-
transformer = make_pipeline(
wrap(
- ["sample"], preprocessor, transform_extra_arguments=transform_extra_arguments,
+ ["sample"],
+ preprocessor,
+ transform_extra_arguments=transform_extra_arguments,
),
SampleLinearize(),
wrap(["sample"], lda_transformer),
)
-
### 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)
+
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/lgbphs.py b/bob/bio/face/config/baseline/lgbphs.py
index 8b2ee181..eebcbba5 100644
--- a/bob/bio/face/config/baseline/lgbphs.py
+++ b/bob/bio/face/config/baseline/lgbphs.py
@@ -9,7 +9,6 @@ import numpy as np
import bob.bio.face
from sklearn.pipeline import make_pipeline
from bob.pipelines import wrap
-import tempfile
import bob.math
@@ -21,6 +20,7 @@ else:
annotation_type = None
fixed_positions = None
+
def get_cropper(annotation_type, fixed_positions=None):
# Cropping
face_cropper, transform_extra_arguments = crop_80x64(
@@ -28,6 +28,7 @@ def get_cropper(annotation_type, fixed_positions=None):
)
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
@@ -37,40 +38,44 @@ def get_pipeline(face_cropper, transform_extra_arguments):
lgbphs = bob.bio.face.extractor.LGBPHS(
# block setup
- block_size = 8,
- block_overlap = 0,
+ block_size=8,
+ block_overlap=0,
# Gabor parameters
- gabor_sigma = math.sqrt(2.) * math.pi,
+ gabor_sigma=math.sqrt(2.0) * math.pi,
# LBP setup (we use the defaults)
-
# histogram setup
- sparse_histogram = True
+ sparse_histogram=True,
)
transformer = make_pipeline(
wrap(
- ["sample"], preprocessor, transform_extra_arguments=transform_extra_arguments,
+ ["sample"],
+ preprocessor,
+ transform_extra_arguments=transform_extra_arguments,
),
wrap(["sample"], lgbphs),
)
-
### BIOMETRIC ALGORITHM
histogram = bob.bio.face.algorithm.Histogram(
- distance_function = bob.math.histogram_intersection,
- is_distance_function = False
+ distance_function=bob.math.histogram_intersection, is_distance_function=False
)
-
- tempdir = tempfile.TemporaryDirectory()
- algorithm = BioAlgorithmLegacy(histogram, base_dir=tempdir.name)
+ tempdir = bob.bio.base.pipelines.vanilla_biometrics.legacy.get_temp_directory(
+ "LGBPHS"
+ )
+ algorithm = BioAlgorithmLegacy(histogram, base_dir=tempdir)
return VanillaBiometricsPipeline(transformer, algorithm)
+
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)
+ face_cropper, transform_extra_arguments = get_cropper(
+ annotation_type, fixed_positions
+ )
return get_pipeline(face_cropper, transform_extra_arguments)
-
+
+
pipeline = load(annotation_type, fixed_positions)
-transformer = pipeline.transformer
\ No newline at end of file
+transformer = pipeline.transformer
--
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