Metadata-Version: 1.1
Name: xbob.db.lfw
Version: 1.2.0
Summary: Labeled Faces in the Wild Database Access API for Bob
Home-page: http://github.com/bioidiap/xbob.db.lfw
Author: Manuel Guenther
Author-email: manuel.guenther@idiap.ch
License: GPLv3
Description: ====================================
         Labeled Faces in the Wild Database
        ====================================
        
        This package contains the access API and descriptions for the `Labeled Faces in the 
        Wild Database <http://vis-www.cs.umass.edu/lfw/>`_. The actual raw data for
        the database should be downloaded from the original URL. This package only
        contains the `Bob <http://www.idiap.ch/software/bob/>`_ accessor methods to use
        the DB directly from python, with our certified protocols.
        
        You would normally not install this package unless you are maintaining it. What
        you would do instead is to tie it in at the package you need to **use** it.
        There are a few ways to achieve this:
        
        1. You can add this package as a requirement at the ``setup.py`` for your own
           `satellite package
           <https://github.com/idiap/bob/wiki/Virtual-Work-Environments-with-Buildout>`_
           or to your Buildout ``.cfg`` file, if you prefer it that way. With this
           method, this package gets automatically downloaded and installed on your
           working environment, or
        
        2. You can manually download and install this package using commands like
           ``easy_install`` or ``pip``.
        
        The package is available in two different distribution formats:
        
        1. You can download it from `PyPI <http://pypi.python.org/pypi>`_, or
        
        2. You can download it in its source form from `its git repository
           <https://github.com/bioidiap/xbob.db.lfw>`_. When you download the
           version at the git repository, you will need to run a command to recreate
           the backend SQLite file required for its operation. This means that the
           database raw files must be installed somewhere in this case. With option
           ``a`` you can run in `dummy` mode and only download the raw data files for
           the database once you are happy with your setup.
        
        You can mix and match points 1/2 and a/b above based on your requirements. Here
        are some examples:
        
        Modify your setup.py and download from PyPI
        ===========================================
        
        That is the easiest. Edit your ``setup.py`` in your satellite package and add
        the following entry in the ``install_requires`` section (note: ``...`` means
        `whatever extra stuff you may have in-between`, don't put that on your
        script)::
        
            install_requires=[
              ...
              "xbob.db.lfw",
            ],
        
        Proceed normally with your ``boostrap/buildout`` steps and you should be all
        set. That means you can now import the ``xbob.db.lfw`` namespace into your scripts.
        
        Modify your buildout.cfg and download from git
        ==============================================
        
        You will need to add a dependence to `mr.developer
        <http://pypi.python.org/pypi/mr.developer/>`_ to be able to install from our
        git repositories. Your ``buildout.cfg`` file should contain the following
        lines::
        
          [buildout]
          ...
          extensions = mr.developer
          auto-checkout = *
          eggs = bob
                 ...
                 xbob.db.lfw
        
          [sources]
          xbob.db.lfw = git https://github.com/bioidiap/xbob.db.lfw.git
          ...
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Database :: Front-Ends
