opengv 1.0+1git91f4b1-7build2 source package in Ubuntu

Changelog

opengv (1.0+1git91f4b1-7build2) noble; urgency=medium

  * No-change rebuild with Python 3.12 as supported version

 -- Graham Inggs <email address hidden>  Tue, 31 Oct 2023 17:10:34 +0000

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Uploaded by:
Graham Inggs
Uploaded to:
Noble
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
opengv_1.0+1git91f4b1.orig.tar.gz 1.1 MiB 634a049f3d6212c3948e9d355e9c5b658bc687997783a4f5041d17e6a38716b2
opengv_1.0+1git91f4b1-7build2.debian.tar.xz 4.7 KiB 505033ac0c5acc14c346521c4aba2a76db6982a2ebf8f42e1b68f1cc0ff191b7
opengv_1.0+1git91f4b1-7build2.dsc 2.3 KiB a5037ff172a9d501be58c75dfb6ccb5cb5657fa6127e3766622dbfa43a0cde52

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Binary packages built by this source

libopengv-dev: Computer vision methods for solving geometric vision problems.

 Contains absolute-pose, relative-pose, triangulation, and point-cloud alignment
 methods for the calibrated case. All problems can be solved with central or
 non-central cameras, and embedded into a random sample consensus or nonlinear
 optimization context. Matlab and Python interfaces are implemented as well
 .
 This package contains the build-time libraries

libopengv-doc: Computer vision methods for solving geometric vision problems.

 Contains absolute-pose, relative-pose, triangulation, and point-cloud alignment
 methods for the calibrated case. All problems can be solved with central or
 non-central cameras, and embedded into a random sample consensus or nonlinear
 optimization context. Matlab and Python interfaces are implemented as well
 .
 This package contains the documentation

libopengv1: No summary available for libopengv1 in ubuntu noble.

No description available for libopengv1 in ubuntu noble.

libopengv1-dbgsym: No summary available for libopengv1-dbgsym in ubuntu noble.

No description available for libopengv1-dbgsym in ubuntu noble.

python3-opengv: Computer vision methods for solving geometric vision problems.

 Contains absolute-pose, relative-pose, triangulation, and point-cloud alignment
 methods for the calibrated case. All problems can be solved with central or
 non-central cameras, and embedded into a random sample consensus or nonlinear
 optimization context. Matlab and Python interfaces are implemented as well
 .
 This package contains the Python interface