From 0e3d6af0dab3d474c7ab9501deb7c5ac007362b9 Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Sat, 2 May 2020 16:37:28 +0200
Subject: [PATCH] Removed examples
---
.../base/config/examples/gabor_mobio-male.py | 76 -------------------
.../examples/isv_atnt_legacy_all_legacy.py | 75 ------------------
.../base/config/examples/lda_atnt_legacy.py | 65 ----------------
.../examples/lda_atnt_legacy_all_legacy.py | 64 ----------------
bob/bio/base/config/examples/pca_atnt.py | 33 --------
.../base/config/examples/pca_mobio-male.py | 50 ------------
6 files changed, 363 deletions(-)
delete mode 100644 bob/bio/base/config/examples/gabor_mobio-male.py
delete mode 100644 bob/bio/base/config/examples/isv_atnt_legacy_all_legacy.py
delete mode 100644 bob/bio/base/config/examples/lda_atnt_legacy.py
delete mode 100644 bob/bio/base/config/examples/lda_atnt_legacy_all_legacy.py
delete mode 100644 bob/bio/base/config/examples/pca_atnt.py
delete mode 100644 bob/bio/base/config/examples/pca_mobio-male.py
diff --git a/bob/bio/base/config/examples/gabor_mobio-male.py b/bob/bio/base/config/examples/gabor_mobio-male.py
deleted file mode 100644
index 6f224e39..00000000
--- a/bob/bio/base/config/examples/gabor_mobio-male.py
+++ /dev/null
@@ -1,76 +0,0 @@
-from bob.bio.base.pipelines.vanilla_biometrics.implemented import CheckpointDistance
-from bob.bio.base.pipelines.vanilla_biometrics.legacy import (
- DatabaseConnector,
- Preprocessor,
- Extractor,
- AlgorithmAsBioAlg,
-)
-from bob.bio.face.database.mobio import MobioBioDatabase
-from bob.bio.face.preprocessor import FaceCrop
-from bob.extension import rc
-from bob.pipelines.transformers import CheckpointSampleLinearize, CheckpointSamplePCA
-from sklearn.pipeline import make_pipeline
-import functools
-import os
-import bob.bio.face
-import math
-
-base_dir = "example"
-
-
-database = DatabaseConnector(
- MobioBioDatabase(
- original_directory=rc["bob.db.mobio.directory"],
- annotation_directory=rc["bob.db.mobio.annotation_directory"],
- original_extension=".png",
- protocol="mobile0-male",
- )
-)
-database.allow_score_multiple_references = True
-
-# Using face crop
-CROPPED_IMAGE_HEIGHT = 80
-CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
-# eye positions for frontal images
-RIGHT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 - 1)
-LEFT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 * 3)
-
-# FaceCrop
-preprocessor = bob.bio.face.preprocessor.INormLBP(
- face_cropper=bob.bio.face.preprocessor.FaceCrop(
- cropped_image_size=(CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH),
- cropped_positions={"leye": LEFT_EYE_POS, "reye": RIGHT_EYE_POS},
- color_channel="gray",
- ),
-)
-
-extractor = bob.bio.face.extractor.GridGraph(
- # Gabor parameters
- gabor_sigma=math.sqrt(2.0) * math.pi,
- # what kind of information to extract
- normalize_gabor_jets=True,
- # setup of the fixed grid
- node_distance=(8, 8),
-)
-
-transformer = make_pipeline(
- Preprocessor(preprocessor, features_dir=os.path.join(base_dir, "face_cropper")),
- Extractor(extractor, features_dir=os.path.join(base_dir, "gabor_graph")),
-)
-
-
-## algorithm
-gabor_jet = bob.bio.face.algorithm.GaborJet(
- gabor_jet_similarity_type="PhaseDiffPlusCanberra",
- multiple_feature_scoring="max_jet",
- gabor_sigma=math.sqrt(2.0) * math.pi,
-)
-
-algorithm = AlgorithmAsBioAlg(callable=gabor_jet, features_dir=base_dir, allow_score_multiple_references=True)
-#algorithm = AlgorithmAsBioAlg(callable=gabor_jet, features_dir=base_dir)
-from bob.bio.base.pipelines.vanilla_biometrics import VanillaBiometrics, dask_vanilla_biometrics
-
-#pipeline = VanillaBiometrics(transformer, algorithm)
-#pipeline = dask_vanilla_biometrics(VanillaBiometrics(transformer, algorithm), npartitions=48)
-pipeline = VanillaBiometrics(transformer, algorithm)
-
diff --git a/bob/bio/base/config/examples/isv_atnt_legacy_all_legacy.py b/bob/bio/base/config/examples/isv_atnt_legacy_all_legacy.py
deleted file mode 100644
index 41ee5f2c..00000000
--- a/bob/bio/base/config/examples/isv_atnt_legacy_all_legacy.py
+++ /dev/null
@@ -1,75 +0,0 @@
-from bob.bio.face.database import AtntBioDatabase
-from bob.bio.gmm.algorithm import ISV
-from bob.bio.face.preprocessor import FaceCrop
-from sklearn.pipeline import make_pipeline
-from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector, Preprocessor, AlgorithmAsTransformer, AlgorithmAsBioAlg, Extractor
-import functools
-from bob.bio.base.pipelines.vanilla_biometrics.implemented import (
- Distance,
- CheckpointDistance,
-)
-import os
-
-# DATABASE
-database = DatabaseConnector(
- AtntBioDatabase(original_directory="./atnt", protocol="Default"),
-)
-database.allow_scoring_with_all_biometric_references = True
-
-base_dir = "example/isv"
-
-# PREPROCESSOR LEGACY
-
-# Cropping
-CROPPED_IMAGE_HEIGHT = 80
-CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
-
-# eye positions for frontal images
-RIGHT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 - 1)
-LEFT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 * 3)
-
-
-# RANDOM EYES POSITIONS
-# I JUST MADE UP THESE NUMBERS
-FIXED_RIGHT_EYE_POS = (30, 30)
-FIXED_LEFT_EYE_POS = (20, 50)
-
-face_cropper = functools.partial(
- FaceCrop,
- cropped_image_size=(CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH),
- cropped_positions={"leye": LEFT_EYE_POS, "reye": RIGHT_EYE_POS},
- fixed_positions={"leye": FIXED_LEFT_EYE_POS, "reye": FIXED_RIGHT_EYE_POS},
-)
-
-
-import bob.bio.face
-
-extractor = functools.partial(
- bob.bio.face.extractor.DCTBlocks,
- block_size=12,
- block_overlap=11,
- number_of_dct_coefficients=45,
-)
-
-
-
-# ALGORITHM LEGACY
-isv = functools.partial(ISV, subspace_dimension_of_u=10, number_of_gaussians=2)
-
-model_path=os.path.join(base_dir, "ubm_u.hdf5")
-transformer = make_pipeline(
- Preprocessor(callable=face_cropper, features_dir=os.path.join(base_dir,"face_crop")),
- Extractor(extractor, features_dir=os.path.join(base_dir, "dcts")),
- AlgorithmAsTransformer(
- callable=isv, features_dir=os.path.join(base_dir,"isv"), model_path=model_path
- ),
-)
-
-
-algorithm = AlgorithmAsBioAlg(callable=isv, features_dir=base_dir, model_path=model_path)
-
-
-from bob.bio.base.pipelines.vanilla_biometrics import VanillaBiometrics, dask_vanilla_biometrics
-
-#pipeline = VanillaBiometrics(transformer, algorithm)
-pipeline = dask_vanilla_biometrics(VanillaBiometrics(transformer, algorithm))
diff --git a/bob/bio/base/config/examples/lda_atnt_legacy.py b/bob/bio/base/config/examples/lda_atnt_legacy.py
deleted file mode 100644
index dd6f93ed..00000000
--- a/bob/bio/base/config/examples/lda_atnt_legacy.py
+++ /dev/null
@@ -1,65 +0,0 @@
-from bob.bio.face.database import AtntBioDatabase
-from bob.bio.base.algorithm import LDA
-from bob.bio.face.preprocessor import FaceCrop
-from sklearn.pipeline import make_pipeline
-from bob.pipelines.transformers import CheckpointSampleLinearize
-from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector, Preprocessor, AlgorithmAsTransformer
-import functools
-from bob.bio.base.pipelines.vanilla_biometrics.implemented import (
- Distance,
- CheckpointDistance,
-)
-
-# DATABASE
-
-database = DatabaseConnector(
- AtntBioDatabase(original_directory="./atnt", protocol="Default"),
-)
-
-
-# PREPROCESSOR LEGACY
-
-# Cropping
-CROPPED_IMAGE_HEIGHT = 80
-CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
-
-# eye positions for frontal images
-RIGHT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 - 1)
-LEFT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 * 3)
-
-
-# RANDOM EYES POSITIONS
-# I JUST MADE UP THESE NUMBERS
-FIXED_RIGHT_EYE_POS = (30, 30)
-FIXED_LEFT_EYE_POS = (20, 50)
-
-face_cropper = functools.partial(
- FaceCrop,
- cropped_image_size=(CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH),
- cropped_positions={"leye": LEFT_EYE_POS, "reye": RIGHT_EYE_POS},
- fixed_positions={"leye": FIXED_LEFT_EYE_POS, "reye": FIXED_RIGHT_EYE_POS},
-)
-
-# ALGORITHM LEGACY
-
-lda = functools.partial(LDA, use_pinv=True, pca_subspace_dimension=0.90)
-
-
-transformer = make_pipeline(
- Preprocessor(callable=face_cropper, features_dir="./example/transformer0"),
- CheckpointSampleLinearize(features_dir="./example/transformer1"),
- AlgorithmAsTransformer(
- callable=lda, features_dir="./example/transformer2", model_path="./example/lda_projector.hdf5"
- ),
-)
-
-
-
-algorithm = CheckpointDistance(features_dir="./example/")
-# algorithm = Distance()
-
-
-from bob.bio.base.pipelines.vanilla_biometrics import VanillaBiometrics, dask_vanilla_biometrics
-
-#pipeline = VanillaBiometrics(transformer, algorithm)
-pipeline = dask_vanilla_biometrics(VanillaBiometrics(transformer, algorithm))
diff --git a/bob/bio/base/config/examples/lda_atnt_legacy_all_legacy.py b/bob/bio/base/config/examples/lda_atnt_legacy_all_legacy.py
deleted file mode 100644
index d9736430..00000000
--- a/bob/bio/base/config/examples/lda_atnt_legacy_all_legacy.py
+++ /dev/null
@@ -1,64 +0,0 @@
-from bob.bio.face.database import AtntBioDatabase
-from bob.bio.base.algorithm import LDA
-from bob.bio.face.preprocessor import FaceCrop
-from sklearn.pipeline import make_pipeline
-from bob.pipelines.transformers import CheckpointSampleLinearize
-from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector, Preprocessor, AlgorithmAsTransformer, AlgorithmAsBioAlg
-import functools
-from bob.bio.base.pipelines.vanilla_biometrics.implemented import (
- Distance,
- CheckpointDistance,
-)
-import os
-
-# DATABASE
-database = DatabaseConnector(
- AtntBioDatabase(original_directory="./atnt", protocol="Default"),
-)
-
-base_dir = "example"
-
-# PREPROCESSOR LEGACY
-
-# Cropping
-CROPPED_IMAGE_HEIGHT = 80
-CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
-
-# eye positions for frontal images
-RIGHT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 - 1)
-LEFT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 * 3)
-
-
-# RANDOM EYES POSITIONS
-# I JUST MADE UP THESE NUMBERS
-FIXED_RIGHT_EYE_POS = (30, 30)
-FIXED_LEFT_EYE_POS = (20, 50)
-
-face_cropper = functools.partial(
- FaceCrop,
- cropped_image_size=(CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH),
- cropped_positions={"leye": LEFT_EYE_POS, "reye": RIGHT_EYE_POS},
- fixed_positions={"leye": FIXED_LEFT_EYE_POS, "reye": FIXED_RIGHT_EYE_POS},
-)
-
-# ALGORITHM LEGACY
-
-lda = functools.partial(LDA, use_pinv=True, pca_subspace_dimension=0.90)
-
-
-transformer = make_pipeline(
- Preprocessor(callable=face_cropper, features_dir=os.path.join(base_dir,"transformer0")),
- CheckpointSampleLinearize(features_dir=os.path.join(base_dir,"transformer1")),
- AlgorithmAsTransformer(
- callable=lda, features_dir=os.path.join(base_dir,"transformer2"), model_path=os.path.join(base_dir, "lda.hdf5")
- ),
-)
-
-
-algorithm = AlgorithmAsBioAlg(callable=lda, features_dir="./example/")
-
-
-from bob.bio.base.pipelines.vanilla_biometrics import VanillaBiometrics, dask_vanilla_biometrics
-
-#pipeline = VanillaBiometrics(transformer, algorithm)
-pipeline = dask_vanilla_biometrics(VanillaBiometrics(transformer, algorithm))
diff --git a/bob/bio/base/config/examples/pca_atnt.py b/bob/bio/base/config/examples/pca_atnt.py
deleted file mode 100644
index e75daf27..00000000
--- a/bob/bio/base/config/examples/pca_atnt.py
+++ /dev/null
@@ -1,33 +0,0 @@
-from bob.bio.base.pipelines.vanilla_biometrics.legacy import DatabaseConnector
-from sklearn.pipeline import make_pipeline
-from bob.pipelines.transformers import CheckpointSampleLinearize, CheckpointSamplePCA
-from bob.bio.base.pipelines.vanilla_biometrics.implemented import (
- CheckpointDistance,
-)
-from bob.bio.face.database import AtntBioDatabase
-import os
-
-
-base_dir = "example"
-
-database = DatabaseConnector(AtntBioDatabase(original_directory="./atnt", protocol="Default"))
-database.allow_scoring_with_all_biometric_references = True
-
-transformer = make_pipeline(
- CheckpointSampleLinearize(features_dir=os.path.join(base_dir, "linearize")),
- CheckpointSamplePCA(
- features_dir=os.path.join(base_dir, "pca_features"), model_path=os.path.join(base_dir, "pca.pkl")
- ),
-)
-algorithm = CheckpointDistance(features_dir=base_dir, allow_score_multiple_references=True)
-
-# # comment out the code below to disable dask
-from bob.pipelines.mixins import estimator_dask_it, mix_me_up
-from bob.bio.base.pipelines.vanilla_biometrics.mixins import (
- BioAlgDaskMixin,
-)
-
-from bob.bio.base.pipelines.vanilla_biometrics import VanillaBiometrics, dask_vanilla_biometrics
-
-pipeline = VanillaBiometrics(transformer, algorithm)
-#pipeline = dask_vanilla_biometrics(VanillaBiometrics(transformer, algorithm))
diff --git a/bob/bio/base/config/examples/pca_mobio-male.py b/bob/bio/base/config/examples/pca_mobio-male.py
deleted file mode 100644
index 668a1e6f..00000000
--- a/bob/bio/base/config/examples/pca_mobio-male.py
+++ /dev/null
@@ -1,50 +0,0 @@
-from bob.bio.base.pipelines.vanilla_biometrics.implemented import (
- CheckpointDistance,
-)
-from bob.bio.base.pipelines.vanilla_biometrics.legacy import (
- DatabaseConnector,
- Preprocessor,
-)
-from bob.bio.face.database.mobio import MobioBioDatabase
-from bob.bio.face.preprocessor import FaceCrop
-from bob.extension import rc
-from bob.pipelines.transformers import CheckpointSampleLinearize, CheckpointSamplePCA
-from sklearn.pipeline import make_pipeline
-import functools
-
-
-database = DatabaseConnector(
- MobioBioDatabase(
- original_directory=rc["bob.db.mobio.directory"],
- annotation_directory=rc["bob.db.mobio.annotation_directory"],
- original_extension=".png",
- protocol="mobile0-male",
- )
-)
-
-# Using face crop
-CROPPED_IMAGE_HEIGHT = 80
-CROPPED_IMAGE_WIDTH = CROPPED_IMAGE_HEIGHT * 4 // 5
-# eye positions for frontal images
-RIGHT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 - 1)
-LEFT_EYE_POS = (CROPPED_IMAGE_HEIGHT // 5, CROPPED_IMAGE_WIDTH // 4 * 3)
-# FaceCrop
-preprocessor = functools.partial(
- FaceCrop,
- cropped_image_size=(CROPPED_IMAGE_HEIGHT, CROPPED_IMAGE_WIDTH),
- cropped_positions={"leye": LEFT_EYE_POS, "reye": RIGHT_EYE_POS},
-)
-
-transformer = make_pipeline(
- Preprocessor(preprocessor, features_dir="./example/extractor0"),
- CheckpointSampleLinearize(features_dir="./example/extractor1"),
- CheckpointSamplePCA(
- features_dir="./example/extractor2", model_path="./example/pca.pkl"
- ),
-)
-algorithm = CheckpointDistance(features_dir="./example/")
-
-from bob.bio.base.pipelines.vanilla_biometrics import VanillaBiometrics, dask_vanilla_biometrics
-
-#pipeline = VanillaBiometrics(transformer, algorithm)
-pipeline = dask_vanilla_biometrics(VanillaBiometrics(transformer, algorithm), npartitions=48)
--
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