{ "info": { "author": "Laurent El Shafey", "author_email": "laurent.el-shafey@idiap.ch", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Natural Language :: English", "Programming Language :: Python", "Programming Language :: Python :: 3", "Topic :: Database :: Front-Ends", "Topic :: Scientific/Engineering :: Artificial Intelligence" ], "description": "======================================\n Verification File Lists Database API\n======================================\n\nThe Verification Filelist database API provides mechanisms to create\nan API for a verification database and protocol, the user providing \nfile lists.\n\nYou would normally not install this package unless you are maintaining it. What\nyou would do instead is to tie it in at the package you need to **use** it.\nThere are a few ways to achieve this:\n\n1. You can add this package as a requirement at the ``setup.py`` for your own\n `satellite package\n `_\n or to your Buildout ``.cfg`` file, if you prefer it that way. With this\n method, this package gets automatically downloaded and installed on your\n working environment, or\n\n2. You can manually download and install this package using commands like\n ``easy_install`` or ``pip``.\n\nThe package is available in two different distribution formats:\n\n1. You can download it from `PyPI `_, or\n\n2. You can download it in its source form from `its git repository\n `_. When you download the\n version at the git repository, you will need to run a command to recreate\n the backend SQLite file required for its operation. This means that the\n database raw files must be installed somewhere in this case. With option\n ``a`` you can run in `dummy` mode and only download the raw data files for\n the database once you are happy with your setup.\n\nYou can mix and match points 1/2 and a/b above based on your requirements. Here\nare some examples:\n\nModify your setup.py and download from PyPI\n===========================================\n\nThat is the easiest. Edit your ``setup.py`` in your satellite package and add\nthe following entry in the ``install_requires`` section (note: ``...`` means\n`whatever extra stuff you may have in-between`, don't put that on your\nscript)::\n\n install_requires=[\n ...\n \"xbob.db.verification.filelist\",\n ],\n\nProceed normally with your ``bootstrap/buildout`` steps and you should be all\nset. That means you can now import the namespace ``xbob.db.verification.filelist`` into your scripts.\n\nModify your buildout.cfg and download from git\n==============================================\n\nYou will need to add a dependence to `mr.developer\n`_ to be able to install from our\ngit repositories. Your ``buildout.cfg`` file should contain the following\nlines::\n\n [buildout]\n ...\n extensions = mr.developer\n auto-checkout = *\n eggs = bob\n ...\n xbob.db.verification.filelist\n\n [sources]\n xbob.db.verification.filelist = git https://github.com/bioidiap/xbob.db.verification.filelist.git\n ...\n \nCreating file lists\n===================\n\nThe initial step for using this package is to provide file lists specifying the world (train), development and evaluation set to be used by the biometric verification algorithm. The following files need to be created:\n\n- **For training**:\n\n1. *world file*, with default name ``train_world.lst``, and default subdirectory ``norm``. It is a 2-column file with format::\n \n filename client_id\n\n2. two (optional) *world files*, with default names ``train_optional_world_1.lst`` and ``train_optional_world_2.lst``, and default subdirectory ``norm``. The format is the same as for the world file. These files are not needed for the most of the face recognition algorithms, hence, they need to be specified only if the algorithm uses them.\n\n- **For enrollment**:\n\n1. two *model files* for the development and evaluation set, with default name ``for_models.lst`` and default subdirectories ``dev`` and ``eval`` respectively. They are 3-column files with format::\n \n filename model_id client_id\n\n- **For scoring**:\n\n1.a. two *probe files* for the development and evaluation set, with default name ``for_probes.lst`` and default subdirectories ``dev`` and ``eval`` respectively. These files need to be provided only if the scoring is to be done exhaustively, meaning by creating a dense probe/model scoring matrix. They are 2-column files with format:: \n \n filename client_id\n\n1.b. two *score files* for the development and evaluation set, with default name ``for_scores.lst`` and default subdirectories ``dev`` and ``eval`` respectively. These files need to be provided only if the scoring is to be done selectively, meaning by creating a sparse probe/model scoring matrix. They are 4-column files with format:: \n\n filename model_id claimed_client_id client_id\n\n2. two (optional) *files for t-score normalization* for the development and evaluation set, with default name ``for_tnorm.lst`` and default subdirectories ``dev`` and ``eval`` respectively. They are 3-column files with format::\n \n filename model_id client_id\n\n3. two (optional) *files for z-score normalization* for the development and evaluation set, with default name ``for_znorm.lst`` and default subdirectories ``dev`` and ``eval`` respectively. They are 2-column files with format:: \n\n filename client_id\n\n.. note:: The verification queries will use either only the probe or only the score files, so only one of them is mandatory.\n In case both probe and score files are provided, the user should set the parameter ``use_dense_probe_file_list``, which specifies the files to consider, when creating the object of the ``Database`` class.\n\n.. note:: If the database does not provide an evaluation set, the scoring files can be ommited.\n Similarly, if the user only define **for scoring** files and omit the remaining ones, the only valid queries will be scoring-related ones.\n\nThe summarized structure of the base directory (here denoted as ``basedir``) containing all the files should be like this::\n\n basedir -- norm -- train_world.lst\n | |-- train_optional_world_1.lst\n | |-- train_optional_world_2.lst\n |\n |-- dev -- for_models.lst\n | |-- for_probes.lst \n | |-- for_scores.lst \n | |-- for_tnorm.lst \n | |-- for_znorm.lst \n |\n |-- eval -- for_models.lst\n |-- for_probes.lst \n |-- for_scores.lst \n |-- for_tnorm.lst \n |-- for_znorm.lst \n \n \nProtocols and file lists\n========================\n\nWhen you instantiate a database, you have to specify the base directory that contains the file lists.\nIf you have only a single protocol, you could specify the full path to the file lists described\nabove as follows::\n\n >>> db = xbob.db.verification.filelist.Database('basedir/protocol')\n\nNext, you should query the data, WITHOUT specifying any protocol::\n \n >>> db.objects()\n\nAlternatively, if you have more protocols, you could do the following::\n\n >>> db = xbob.db.verification.filelist.Database('basedir')\n >>> db.objects(protocol='protocol')\n\nWhen a protocol is specified, it is appended to the base directory that contains the file lists.\nThis allows to use several protocols that are stored in the same base directory, without the need\nto instantiate a new database. For instance, given two protocols 'P1' and 'P2' (with filelists\ncontained in 'basedir/P1' and 'basedir/P2', respectively), the following would work::\n\n >> db = xbob.db.verification.filelist.Database('basedir')\n >> db.objects(protocol='P1') # Get the objects for the protocol P1\n >> db.objects(protocol='P2') # Get the objects for the protocol P2\n\nNote that if you use several protocols as explained above, the scoring part should be defined in\nthe same way for all the protocols, either by using ``for_probes.lst`` or ``for_scores.lst``.\nThis means that at the time of the database instantiation, it will be determined (or specified\nusing the ``use_dense_probe_file_list`` optional argument), whether the protocols should use\nthe content of ``for_probes.lst`` or ``for_scores.lst``. 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