Metadata-Version: 1.1
Name: gdal2mbtiles
Version: 1.2.0
Summary: Converts a GDAL-readable dataset into an MBTiles file. This is used to generate web maps.
Home-page: https://github.com/ecometrica/gdal2mbtiles
Author: Ecometrica
Author-email: admin@ecometrica.com
License: Apache Software License, version 2.0
Description: ======================================================
         Convert GDAL-readable datasets into an MBTiles file.
        ======================================================
        
        **gdal2mbtiles** helps you generate web mapping tiles that can be shown
        through a browser-based mapping library on your website.
        
        `GDAL-readable files`_ are images that are georeference, that means that
        they are positioned and projected on to the world. In order to display a
        dynamic map on the web, you don't want to serve the whole image at once,
        so it must be sliced into tiles that are hosted by a tile server.
        
        The MBTiles_ file format was developed by MapBox_ to make tile storage
        easier. You can upload the final file to their service, or run your own
        tile server. MapBox provides one called TileStream_.
        
        
        Installation
        ============
        
        You can get a copy of the source by using::
        
            $ git clone https://github.com/ecometrica/gdal2mbtiles.git
        
        Note that this program requires Python 2.7 or higher.
        
        
        External Dependencies
        ---------------------
        
        We rely on GDAL_ to read georeferenced datasets. However, it is not
        available on PyPi.
        
        Under Debian or Ubuntu, run the following to install it::
        
            $ sudo apt-get install python-gdal
        
        
        We also rely on VIPS_ to do fast image processing. It's also not
        available on PyPi.
        
        Under Debian or Ubuntu, run the following to install it::
        
            $ sudo apt-get install python-vipscc
        
        If you are using a virtualenv, you will need to symlink Python library
        in the right place. Under Debian or Ubuntu, assuming Python 2.7, run the
        following::
        
            $ ln -s /usr/lib/python2.7/dist-packages/vipsCC $VIRTUAL_ENV/lib/python2.7/site-packages/
        
        
        You'll also need a few other libraries to deal with large TIFF files and
        to optimize the resulting PNG tiles.
        
        Under Debian or Ubuntu, run the following to install them::
        
            $ sudo apt-get install libtiff5 optipng pngquant
        
        
        Reporting bugs and submitting patches
        =====================================
        
        Please check our `issue tracker`_ for known bugs and feature requests.
        
        We accept pull requests for fixes and new features.
        
        
        Credits
        =======
        
        Maxime Dupuis and Simon Law wrote this program, with the generous
        support of Ecometrica_.
        
        .. _GDAL-readable files: http://www.gdal.org/formats_list.html
        .. _MBTiles: http://mapbox.com/developers/mbtiles/
        .. _MapBox: http://mapbox.com/
        .. _TileStream: https://github.com/mapbox/tilestream
        
        .. _GDAL: http://www.gdal.org/
        .. _VIPS: http://www.vips.ecs.soton.ac.uk/
        
        .. _issue tracker: https://github.com/ecometrica/gdal2mbtiles/issues
        .. _Ecometrica: http://ecometrica.com/
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Other Audience
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Multimedia :: Graphics :: Graphics Conversion
Classifier: Topic :: Scientific/Engineering :: GIS
