Source: alicevision
Section: contrib/libs
Priority: optional
Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Uploaders: Dima Kogan <dkogan@debian.org>
Build-Depends: debhelper-compat (= 13),
               cmake,
               libgeogram-dev,
               libalembic-graphics-dev,
               libapriltag-dev,
               libflann-dev,
               libnanoflann-dev,
               liblemon-dev,
               libcoin-dev,
               libceres-dev,
               libassimp-dev,
               libboost-all-dev,
               libopenimageio-dev,
               openimageio-tools,
               libmetis-dev,
               libopengv-dev,
               libopencv-dev,
               libmeshsdfilter-dev,
               libopenmesh-dev,
               libexpat1-dev,
               python3-imath,
               libtbb-dev,
               coinor-libcoinutils-dev,
               coinor-libclp-dev,
               liblz4-dev,
# Depth map processing is a part of most meshlab workflows, and it requires
# cuda. At this time we have nvidi-cuda-dev=12.4.1, which apparently doesn't
# work with gcc > 13.2:
#   https://docs.nvidia.com/cuda/archive/12.4.1/cuda-installation-guide-linux/index.html
# Today gcc-13 provides 13.4, so I request gcc-12, and I point nvcc at that.
               nvidia-cuda-toolkit,
               gcc-12,
               g++-12
Standards-Version: 4.6.0
Homepage: https://github.com/alicevision/AliceVision
Vcs-Git: https://salsa.debian.org/science-team/alicevision.git
Vcs-Browser: https://salsa.debian.org/science-team/alicevision

Package: libalicevision3
Section: contrib/libs
Architecture: any
Multi-Arch: same
Depends: ${shlibs:Depends}, ${misc:Depends}, libalicevision-data (= ${source:Version})
Description: Photogrammetric Computer Vision Framework
 AliceVision aims to provide strong software basis with state-of-the-art
 computer vision algorithms that can be tested, analyzed and reused. The project
 is a result of collaboration between academia and industry to provide
 cutting-edge algorithms with the robustness and the quality required for
 production usage.
 .
 This package provides the shared library

Package: libalicevision-dev
Section: contrib/libdevel
Architecture: any
Multi-Arch: same
Depends: ${shlibs:Depends}, ${misc:Depends}, libalicevision3 (= ${binary:Version}),
               libalembic-graphics-dev,
               libceres-dev,
               libapriltag-dev,
               libopengv-dev,
               libopencv-dev,
               libboost-all-dev,
               libopenimageio-dev,
               coinor-libcoinutils-dev,
               coinor-libosi-dev,
               coinor-libclp-dev
Description: Photogrammetric Computer Vision Framework
 AliceVision aims to provide strong software basis with state-of-the-art
 computer vision algorithms that can be tested, analyzed and reused. The project
 is a result of collaboration between academia and industry to provide
 cutting-edge algorithms with the robustness and the quality required for
 production usage.
 .
 This package provides the development files library

Package: libalicevision-data
Section: contrib/libs
Architecture: all
Multi-Arch: foreign
Depends: ${shlibs:Depends}, ${misc:Depends}
Description: Photogrammetric Computer Vision Framework
 AliceVision aims to provide strong software basis with state-of-the-art
 computer vision algorithms that can be tested, analyzed and reused. The project
 is a result of collaboration between academia and industry to provide
 cutting-edge algorithms with the robustness and the quality required for
 production usage.
 .
 This package provides the data files

Package: alicevision
Section: contrib/science
Architecture: any
Depends: ${shlibs:Depends}, ${misc:Depends}, libalicevision3 (= ${binary:Version})
Description: Photogrammetric Computer Vision Framework
 AliceVision aims to provide strong software basis with state-of-the-art
 computer vision algorithms that can be tested, analyzed and reused. The project
 is a result of collaboration between academia and industry to provide
 cutting-edge algorithms with the robustness and the quality required for
 production usage.
 .
 This package provides the executable tools