How to Install and Uninstall libopengv1 Package on Kali Linux
Last updated: December 24,2024
1. Install "libopengv1" package
Please follow the steps below to install libopengv1 on Kali Linux
$
sudo apt update
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$
sudo apt install
libopengv1
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2. Uninstall "libopengv1" package
Please follow the guidance below to uninstall libopengv1 on Kali Linux:
$
sudo apt remove
libopengv1
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the libopengv1 package on Kali Linux
Package: libopengv1
Source: opengv (1.0+1git91f4b1-7)
Version: 1.0+1git91f4b1-7+b2
Installed-Size: 3108
Maintainer: Debian Science Maintainers
Architecture: amd64
Depends: libc6 (>= 2.32), libgcc-s1 (>= 4.0), libstdc++6 (>= 13.1)
Size: 650244
SHA256: 3bce3b099e09d952b524867253d3cfca9e6a3676362ef7a8bb9b2e35898a0943
SHA1: 95c88f0393a8cc52eb4b66573703fb5d1667f0ec
MD5sum: 021c72c62f44819606d4ccac6f467371
Description: 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 run-time libraries
Description-md5:
Multi-Arch: same
Homepage: https://laurentkneip.github.io/opengv
Tag: role::shared-lib
Section: libs
Priority: optional
Filename: pool/main/o/opengv/libopengv1_1.0+1git91f4b1-7+b2_amd64.deb
Source: opengv (1.0+1git91f4b1-7)
Version: 1.0+1git91f4b1-7+b2
Installed-Size: 3108
Maintainer: Debian Science Maintainers
Architecture: amd64
Depends: libc6 (>= 2.32), libgcc-s1 (>= 4.0), libstdc++6 (>= 13.1)
Size: 650244
SHA256: 3bce3b099e09d952b524867253d3cfca9e6a3676362ef7a8bb9b2e35898a0943
SHA1: 95c88f0393a8cc52eb4b66573703fb5d1667f0ec
MD5sum: 021c72c62f44819606d4ccac6f467371
Description: 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 run-time libraries
Description-md5:
Multi-Arch: same
Homepage: https://laurentkneip.github.io/opengv
Tag: role::shared-lib
Section: libs
Priority: optional
Filename: pool/main/o/opengv/libopengv1_1.0+1git91f4b1-7+b2_amd64.deb