Ubuntu
gtsam package

gtsam 4.2~9+dfsg-6 source package in Ubuntu

Changelog

gtsam (4.2~9+dfsg-6) unstable; urgency=medium

  * Disabled building examples to cut down on build time
  * Build fixes for 32bit arches

 -- Dima Kogan <email address hidden>  Thu, 31 Aug 2023 13:32:38 -0700

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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

Downloads

File Size SHA-256 Checksum
gtsam_4.2~9+dfsg-6.dsc 2.5 KiB 49f5d5f69a510a8cc9041009bc40526d4bd2538642eb1c3d81cde3ef800cc73f
gtsam_4.2~9+dfsg.orig.tar.xz 10.9 MiB 38a26c43a8513c57a5d56041ca9394a6b60fedf59593792753c5ec1619b7c093
gtsam_4.2~9+dfsg-6.debian.tar.xz 19.1 KiB 29493cc54917c7094743b79a55fe9be691df78ad8001a31f3171e3bb241099f9

Available diffs

No changes file available.

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