{
    "info": {
        "author": "Pavel Korshunov",
        "author_email": "pavel.korshunov@idiap.ch",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Framework :: Bob",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Natural Language :: English",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": ".. vim: set fileencoding=utf-8 :\n.. Thu Feb 22 11:30:16 CET 2018\n\n.. image:: https://img.shields.io/badge/docs-v1.0.1-yellow.svg\n   :target: https://www.idiap.ch/software/bob/docs/bob/bob.hobpad2.chapter19/v1.0.1/index.html\n.. image:: https://img.shields.io/badge/docs-latest-orange.svg\n   :target: https://www.idiap.ch/software/bob/docs/bob/bob.hobpad2.chapter19/master/index.html\n.. image:: https://gitlab.idiap.ch/bob/bob.hobpad2.chapter19/badges/v1.0.1/build.svg\n   :target: https://gitlab.idiap.ch/bob/bob.hobpad2.chapter19/commits/v1.0.1\n.. image:: https://gitlab.idiap.ch/bob/bob.hobpad2.chapter19/badges/v1.0.1/coverage.svg\n   :target: https://gitlab.idiap.ch/bob/bob.hobpad2.chapter19/commits/v1.0.1\n.. image:: https://img.shields.io/badge/gitlab-project-0000c0.svg\n   :target: https://gitlab.idiap.ch/bob/bob.hobpad2.chapter19\n.. image:: https://img.shields.io/pypi/v/bob.hobpad2.chapter19.svg\n   :target: https://pypi.python.org/pypi/bob.hobpad2.chapter19\n\n\n===============================================================\n A Cross-database Study of Voice Presentation Attack Detection\n===============================================================\n\nThis package is part of the signal-processing and machine learning toolbox\nBob_. It is a software package to reproduce \"A Cross-database Study of Voice Presentation Attack Detection\" Chapter 19 of \"Handbook of Biometric\nAnti-Spoofing: Presentation Attack Detection 2nd Edition\"\n\n\nWe use conda_ to manage the software stack installation. To install this\npackage and all dependencies, first install conda_, and then run the\nfollowing command on your shell::\n\n  $ conda create --name hobpad2-chapter19 --override-channels -c https://www.idiap.ch/software/bob/conda -c defaults python=3 bob.hobpad2.chapter19\n  $ conda activate hobpad2-chapter19\n  (hobpad2-chapter19) $ #type all commands inside this \"activated\" environment\n\n\n.. note::\n\n   At the present time, Bob_ only offers support to Linux and MacOS operating\n   systems. Windows installations are **not** supported.\n\n\nScore files to reproduce the results of the chapter\n===================================================\n\nDue to the large number and size of score files, some of them need to be downloaded and the rest were archived and need to be unzipped. Please follow these steps to prepare the scores, so that error rates and figures used in the chapter can be computed:\n\n* Unzip `pad_handcrafted.zip` and `pad_megafusion.zip` files locate in the `scores' folder into respective `pad_handcrafted` and `pad_megafusion` subfolders.\n\n* Download and unarchive some of the scores of handcrafted features-based PAD systems:\n\n    $ cd scores\n    $ wget http://www.idiap.ch/resource/biometric/data/interspeech_2016.tar.gz\n    $ tar -xzvf interspeech_2016.tar.gz  \n    $ Add these score files inside `pad_handcrafted` folder\n\n* Download and unarchive scores for CNN-based PAD systems:\n\n    $ cd scores\n    $ wget http://www.idiap.ch/resource/biometric/data/isba2018-pad-dnn.tar.gz\n    $ tar -xzvf isba2018-pad-dnn.tar.gz  \n    $ Rename the obtained scores folder into `pad_cnn` folder\n\n\nReproducing the results of the chapter\n======================================\n\nTo compute error rates presented in Tables 5 and 6 of the chapter on performance of PAD systems based on handcrafted features, the following script should be used:\n\n\n    $ ./compute_handcrafted_results.sh\n\nThe script will create a folder for each configuration of PAD system and datasets. The folders contain DET curves for each given configuration, histograms of score distributions, and error rates. The script also creates a text file 'latex_table_handcrafed_stats_eer.txt' which contains a LaTeX formatted table with the results from Table 6 and 6.\n\nTo compute error rates presented in Table 7, run the script that is installed with bob.measure using the following:\n\n\n    $ bob_eval_threshold.py -c eer ../scores/pad_megafusion/corresponding_folder/scores-dev\n\nTo compute error rates presented in Tables 10 and 11 and Figure 6 of the chapter on performance of CNN-based PAD systems, the following script should be used:\n\n\n    $ ./compute_cnn_results.sh\n\nThe script will create a folder for each configuration of PAD system and datasets. The folders contain DET curves for each given configuration (subset of these plots are shown in Figure 6 of the chapter), histograms of score distributions, and error rates. The script also creates a text file 'latex_table_cnn_stats_eer.txt' which contains a LaTeX formatted table with the results from Table 10 and 11.\n\nTo compute error rates for different types of attack as presented in Table 12, please execute the following script:\n\n\n    $ ./compute_results_cnn_per_attack.sh\n\nThe script will compute error rates for each type of attack of voicePA and BioCPqD-PA databases used in the paper and produce 'latex_table_cnn_per_attack_stats_eer.txt' file with LaTeX formatted table that has results from Table 12.\n\n\nContact\n-------\n\nFor questions or reporting issues to this software package, contact our\ndevelopment `mailing list`_.\n\n\n.. Place your references here:\n.. _conda: https://conda.io/\n.. _bob: https://www.idiap.ch/software/bob\n.. _installation: https://www.idiap.ch/software/bob/install\n.. _mailing list: https://www.idiap.ch/software/bob/discuss",
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        "home_page": "https://gitlab.idiap.ch/bob/bob.hobpad2.chapter19",
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        "license": "GPLv3",
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        "name": "bob.hobpad2.chapter19",
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        "summary": "Software package to reproduce Evaluation Methodologies for Biometric Presentation Attack Detection chapter of Handbook of Biometric Anti-Spoofing: Presentation Attack Detection 2nd Edition",
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