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gtsam package

gtsam 4.2.0+dfsg-1 source package in Ubuntu

Changelog

gtsam (4.2.0+dfsg-1) unstable; urgency=medium

  * New upstream release
  * Successful build against boost 1.83 (Closes: #1056078)
  * Not depending on the -all python packages (Closes: #1055683)

 -- Dima Kogan <email address hidden>  Mon, 08 Jan 2024 21:51:35 -0800

Upload details

Uploaded by:
Debian Science Team
Uploaded to:
Sid
Original maintainer:
Debian Science Team
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

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Series Pocket Published Component Section

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File Size SHA-256 Checksum
gtsam_4.2.0+dfsg-1.dsc 2.5 KiB 977b78caf0fc8c202b012625431b2424becb6b41d6e99e3275628acf1c98206f
gtsam_4.2.0+dfsg.orig.tar.xz 10.9 MiB 8383cc1fe7ea82549c9cd6c0cead48712d3348f4193c0c16e776e57401343277
gtsam_4.2.0+dfsg-1.debian.tar.xz 20.5 KiB c3f94ef67bacc38ee8dab7b751119361f256feba689ea7ea79e844c33904f496

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Binary packages built by this source

libgtsam-dev: Factor graphs for sensor fusion in robotics

 GTSAM is a C++ library that implements sensor fusion for robotics and computer
 vision applications, including SLAM (Simultaneous Localization and Mapping), VO
 (Visual Odometry), and SFM (Structure from Motion). It uses factor graphs and
 Bayes networks as the underlying computing paradigm rather than sparse matrices
 to optimize for the most probable configuration or an optimal plan. Coupled
 with a capable sensor front-end (not provided here), GTSAM powers many
 impressive autonomous systems, in both academia and industry.
 .
 Development files

libgtsam-doc: Factor graphs for sensor fusion in robotics

 GTSAM is a C++ library that implements sensor fusion for robotics and computer
 vision applications, including SLAM (Simultaneous Localization and Mapping), VO
 (Visual Odometry), and SFM (Structure from Motion). It uses factor graphs and
 Bayes networks as the underlying computing paradigm rather than sparse matrices
 to optimize for the most probable configuration or an optimal plan. Coupled
 with a capable sensor front-end (not provided here), GTSAM powers many
 impressive autonomous systems, in both academia and industry.
 .
 Documentation

libgtsam4: Factor graphs for sensor fusion in robotics

 GTSAM is a C++ library that implements sensor fusion for robotics and computer
 vision applications, including SLAM (Simultaneous Localization and Mapping), VO
 (Visual Odometry), and SFM (Structure from Motion). It uses factor graphs and
 Bayes networks as the underlying computing paradigm rather than sparse matrices
 to optimize for the most probable configuration or an optimal plan. Coupled
 with a capable sensor front-end (not provided here), GTSAM powers many
 impressive autonomous systems, in both academia and industry.

libgtsam4-dbgsym: debug symbols for libgtsam4
python3-gtsam: Factor graphs for sensor fusion in robotics

 GTSAM is a C++ library that implements sensor fusion for robotics and computer
 vision applications, including SLAM (Simultaneous Localization and Mapping), VO
 (Visual Odometry), and SFM (Structure from Motion). It uses factor graphs and
 Bayes networks as the underlying computing paradigm rather than sparse matrices
 to optimize for the most probable configuration or an optimal plan. Coupled
 with a capable sensor front-end (not provided here), GTSAM powers many
 impressive autonomous systems, in both academia and industry.
 .
 Python library

python3-gtsam-dbgsym: debug symbols for python3-gtsam