Source: dlib
Priority: optional
Maintainer: Séverin Lemaignan <severin@guakamole.org>
Build-Depends: debhelper (>= 9), bzip2, cmake, libpng-dev, libjpeg-dev, libsqlite3-dev, libblas-dev, liblapack-dev
Standards-Version: 3.9.8
Section: libs
Homepage: http://dlib.net/
Vcs-Git: https://github.com/severin-lemaignan/dlib-debian.git
Vcs-Browser: https://github.com/severin-lemaignan/dlib-debian

Package: libdlib-dev
Section: libdevel
Architecture: any
Depends: libdlib18 (= ${binary:Version}), ${misc:Depends}
Description: C++ toolkit for machine learning and computer vision - development
 Dlib is a general purpose cross-platform open source software library written
 in the C++ programming language. It now contains software components for
 dealing with networking, threads, graphical interfaces, complex data
 structures, linear algebra, statistical machine learning, image processing,
 data mining, XML and text parsing, numerical optimization, Bayesian networks,
 and numerous other tasks.
 .
 This package contains the development headers.

Package: libdlib18
Architecture: any
Depends: libdlib-data, ${shlibs:Depends}, ${misc:Depends}
Description: C++ toolkit for machine learning and computer vision - library
 Dlib is a general purpose cross-platform open source software library written
 in the C++ programming language. It now contains software components for
 dealing with networking, threads, graphical interfaces, complex data
 structures, linear algebra, statistical machine learning, image processing,
 data mining, XML and text parsing, numerical optimization, Bayesian networks,
 and numerous other tasks.

Package: libdlib-data
Architecture: all
Multi-Arch: foreign
Depends: ${shlibs:Depends}, ${misc:Depends}
Description: C++ toolkit for machine learning and computer vision - models
 Dlib is a general purpose cross-platform open source software library written
 in the C++ programming language. It now contains software components for
 dealing with networking, threads, graphical interfaces, complex data
 structures, linear algebra, statistical machine learning, image processing,
 data mining, XML and text parsing, numerical optimization, Bayesian networks,
 and numerous other tasks.
 .
 This package contains the trained models provided with dlib.