Source: flann Section: libs Priority: optional Maintainer: Debian Science Team Uploaders: Michael Kleiber , Leopold Palomo-Avellaneda Build-Depends: cmake, debhelper (>= 11), pkg-config, libboost-dev, libboost-mpi-dev, libboost-system-dev, libboost-serialization-dev, libboost-thread-dev, libgtest-dev, libhdf5-mpi-dev, liblz4-dev, mpi-default-dev, python, python-numpy Build-Depends-Indep: latex2html, texlive-binaries, texlive-latex-base Standards-Version: 4.2.1 Rules-Requires-Root: no Homepage: http://www.cs.ubc.ca/research/flann/ Vcs-Browser: https://salsa.debian.org/science-team/flann Vcs-Git: https://salsa.debian.org/science-team/flann.git Package: libflann-dev Section: libdevel Architecture: any Multi-Arch: same Depends: libflann1.9 (= ${binary:Version}), ${misc:Depends}, libboost-dev, libhdf5-mpi-dev, liblz4-dev, Description: Fast Library for Approximate Nearest Neighbors - development FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms found to work best for nearest neighbor search and a system for automatically choosing the best algorithm and optimum parameters depending on the dataset. . This package contains development files needed to build FLANN applications. Package: libflann1.9 Architecture: any Depends: ${misc:Depends}, ${shlibs:Depends} Pre-Depends: ${misc:Pre-Depends} Multi-Arch: same Description: Fast Library for Approximate Nearest Neighbors - runtime FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms found to work best for nearest neighbor search and a system for automatically choosing the best algorithm and optimum parameters depending on the dataset. . This package contains the libraries needed to run FLANN applications. Package: flann-doc Architecture: all Section: doc Depends: doc-base, ${misc:Depends} Description: Fast Library for Approximate Nearest Neighbors - documentation FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms found to work best for nearest neighbor search and a system for automatically choosing the best algorithm and optimum parameters depending on the dataset. . This package contains the documentation for FLANN.