cleaning up nonexistant entry-points

parent 8a261761
Pipeline #46391 passed with stage
in 10 minutes and 8 seconds
......@@ -18,18 +18,21 @@ param_grid = [
},
]
classifier = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
classifier = mario.wrap(
["sample"],
classifier,
fit_extra_arguments=[("y", "is_bonafide")],
["sample"], classifier, fit_extra_arguments=[("y", "is_bonafide")],
)
# Pipeline #
frames_classifier = Pipeline([("frame_cont_to_array", frame_cont_to_array), ("classifier", classifier)])
pipeline = Pipeline([
frames_classifier = Pipeline(
[("frame_cont_to_array", frame_cont_to_array), ("classifier", classifier)]
)
pipeline = Pipeline(
[
("preprocessor", preprocessor),
("extractor", extractor),
("svm", frames_classifier),
])
]
)
......@@ -2,44 +2,40 @@
# vim: set fileencoding=utf-8 :
from setuptools import setup, dist
dist.Distribution(dict(setup_requires=['bob.extension']))
dist.Distribution(dict(setup_requires=["bob.extension"]))
# load the requirements.txt for additional requirements
from bob.extension.utils import load_requirements, find_packages
install_requires = load_requirements()
# The only thing we do in this file is to call the setup() function with all
# parameters that define our package.
setup(
# This is the basic information about your project. Modify all this
# information before releasing code publicly.
name='bob.pad.face',
name="bob.pad.face",
version=open("version.txt").read().rstrip(),
description=
'Implements tools for spoofing or presentation attack detection in face biometrics',
url='https://gitlab.idiap.ch/bob/bob.pad.face',
license='GPLv3',
author='Olegs Nikisins',
author_email='olegs.nikisins@idiap.ch',
keywords='bob',
description="Implements tools for spoofing or presentation attack detection in face biometrics",
url="https://gitlab.idiap.ch/bob/bob.pad.face",
license="GPLv3",
author="Olegs Nikisins",
author_email="olegs.nikisins@idiap.ch",
keywords="bob",
# If you have a better, long description of your package, place it on the
# 'doc' directory and then hook it here
long_description=open('README.rst').read(),
long_description=open("README.rst").read(),
# This line is required for any distutils based packaging.
# It will find all package-data inside the 'bob' directory.
packages=find_packages('bob'),
packages=find_packages("bob"),
include_package_data=True,
# This line defines which packages should be installed when you "install"
# this package. All packages that are mentioned here, but are not installed
# on the current system will be installed locally and only visible to the
# scripts of this package. Don't worry - You won't need administrative
# privileges when using buildout.
install_requires=install_requires,
# This entry defines which scripts you will have inside the 'bin' directory
# once you install the package (or run 'bin/buildout'). The order of each
# entry under 'console_scripts' is like this:
......@@ -55,96 +51,52 @@ setup(
# In this simple example we will create a single program that will print
# the version of bob.
entry_points={
# scripts should be declared using this entry:
'console_scripts': [
'quality-assessment.py = bob.pad.face.script.quality_assessment:main',
"console_scripts": [
"quality-assessment.py = bob.pad.face.script.quality_assessment:main",
],
# registered databases:
'bob.pad.database': [
'replay-attack = bob.pad.face.config.replay_attack:database',
'replay-mobile = bob.pad.face.config.replay_mobile:database',
'casiafasd = bob.pad.face.config.casiafasd:database',
'mifs = bob.pad.face.config.mifs:database',
'batl-db = bob.pad.face.config.database.batl.batl_db:database',
'batl-db-infrared = bob.pad.face.config.database.batl.batl_db_infrared:database',
'batl-db-depth = bob.pad.face.config.database.batl.batl_db_depth:database',
'batl-db-thermal = bob.pad.face.config.database.batl.batl_db_thermal:database',
'batl-db-rgb-ir-d-grandtest = bob.pad.face.config.database.batl.batl_db_rgb_ir_d_grandtest:database',
'celeb-a = bob.pad.face.config.celeb_a:database',
'maskattack = bob.pad.face.config.maskattack:database',
'casiasurf-color = bob.pad.face.config.casiasurf_color:database',
'casiasurf = bob.pad.face.config.casiasurf:database',
"bob.pad.database": [
"replay-attack = bob.pad.face.config.replay_attack:database",
"replay-mobile = bob.pad.face.config.replay_mobile:database",
"casiafasd = bob.pad.face.config.casiafasd:database",
"mifs = bob.pad.face.config.mifs:database",
"celeb-a = bob.pad.face.config.celeb_a:database",
"maskattack = bob.pad.face.config.maskattack:database",
"casiasurf-color = bob.pad.face.config.casiasurf_color:database",
"casiasurf = bob.pad.face.config.casiasurf:database",
],
# registered configurations:
'bob.bio.config': [
"bob.pad.config": [
# databases
'replay-attack = bob.pad.face.config.replay_attack',
'replay-mobile = bob.pad.face.config.replay_mobile',
'casiafasd = bob.pad.face.config.casiafasd',
'mifs = bob.pad.face.config.mifs',
'batl-db = bob.pad.face.config.database.batl.batl_db',
'batl-db-infrared = bob.pad.face.config.database.batl.batl_db_infrared',
'batl-db-depth = bob.pad.face.config.database.batl.batl_db_depth',
'batl-db-thermal = bob.pad.face.config.database.batl.batl_db_thermal',
'batl-db-rgb-ir-d-grandtest = bob.pad.face.config.database.batl.batl_db_rgb_ir_d_grandtest',
'celeb-a = bob.pad.face.config.celeb_a',
'maskattack = bob.pad.face.config.maskattack',
# baselines using SVM:
'lbp-svm = bob.pad.face.config.lbp_svm',
'qm-svm = bob.pad.face.config.qm_svm',
# baselines using LR:
'qm-lr = bob.pad.face.config.qm_lr',
'lbp-lr-batl-D-T-IR = bob.pad.face.config.lbp_lr_batl_D_T_IR', # this pipe-line can be used both for BATL databases, Depth, Thermal and Infrared channels.
# baselines using GMM:
'qm-one-class-gmm = bob.pad.face.config.qm_one_class_gmm',
],
# registered preprocessors:
'bob.pad.preprocessor': [
'empty-preprocessor = bob.pad.face.config.preprocessor.filename:empty_preprocessor', # no preprocessing
'rgb-face-detect-dlib = bob.pad.face.config.preprocessor.video_face_crop:rgb_face_detector_dlib', # detect faces locally replacing database annotations
'rgb-face-detect-mtcnn = bob.pad.face.config.preprocessor.video_face_crop:rgb_face_detector_mtcnn', # detect faces locally replacing database annotations
'bw-face-detect-mtcnn = bob.pad.face.config.preprocessor.video_face_crop:bw_face_detect_mtcnn', # detect faces locally, return BW image
'rgb-face-detect-check-quality-128x128 = bob.pad.face.config.preprocessor.face_feature_crop_quality_check:face_feature_0_128x128_crop_rgb', # detect faces locally replacing database annotations, also check face quality by trying to detect the eyes in cropped face.
'video-face-crop-align-bw-ir-d-channels-3x128x128 = bob.pad.face.config.preprocessor.video_face_crop_align_block_patch:video_face_crop_align_bw_ir_d_channels_3x128x128', # Extract a BW-NIR-D patch of size (3 x 128 x 128) containing aligned face
'video-face-crop-align-bw-ir-d-channels-3x128x128-vect = bob.pad.face.config.preprocessor.video_face_crop_align_block_patch:video_face_crop_align_bw_ir_d_channels_3x128x128_vect', # Extract a BW-NIR-D **vectorized** patch of size containing aligned face
],
# registered extractors:
'bob.pad.extractor': [
'video-lbp-histogram-extractor-n8r1-uniform = bob.pad.face.config.extractor.video_lbp_histogram:video_lbp_histogram_extractor_n8r1_uniform',
'video-quality-measure-galbally-msu = bob.pad.face.config.extractor.video_quality_measure:video_quality_measure_galbally_msu',
],
# registered algorithms:
'bob.pad.algorithm': [
'video-svm-pad-algorithm-10k-grid-mean-std = bob.pad.face.config.algorithm.video_svm_pad_algorithm:video_svm_pad_algorithm_10k_grid_mean_std',
'video-svm-pad-algorithm-10k-grid-mean-std-frame-level = bob.pad.face.config.algorithm.video_svm_pad_algorithm:video_svm_pad_algorithm_10k_grid_mean_std_frame_level',
'video-svm-pad-algorithm-default-svm-param-mean-std-frame-level = bob.pad.face.config.algorithm.video_svm_pad_algorithm:video_svm_pad_algorithm_default_svm_param_mean_std_frame_level',
"replay-attack = bob.pad.face.config.replay_attack",
"replay-mobile = bob.pad.face.config.replay_mobile",
"casiafasd = bob.pad.face.config.casiafasd",
"mifs = bob.pad.face.config.mifs",
"celeb-a = bob.pad.face.config.celeb_a",
"maskattack = bob.pad.face.config.maskattack",
# LBPs
"lbp = bob.pad.face.config.lbp_64",
# quality measure
"qm = bob.pad.face.config.qm_64",
# classifiers
"svm-frames = bob.pad.face.config.svm_frames",
],
# registered ``bob pad ...`` commands
'bob.pad.cli': [
'statistics = bob.pad.face.script.statistics:statistics',
"bob.pad.cli": [
"statistics = bob.pad.face.script.statistics:statistics",
],
},
# Classifiers are important if you plan to distribute this package through
# PyPI. You can find the complete list of classifiers that are valid and
# useful here (http://pypi.python.org/pypi?%3Aaction=list_classifiers).
classifiers=[
'Framework :: Bob',
'Development Status :: 3 - Alpha',
'Intended Audience :: Developers',
'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
'Natural Language :: English',
'Programming Language :: Python',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
"Framework :: Bob",
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
"Natural Language :: English",
"Programming Language :: Python",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
)
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