How to Install and Uninstall libvigraimpex-doc Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 17,2024

1. Install "libvigraimpex-doc" package

This is a short guide on how to install libvigraimpex-doc on Ubuntu 21.10 (Impish Indri)

$ sudo apt update $ sudo apt install libvigraimpex-doc

2. Uninstall "libvigraimpex-doc" package

In this section, we are going to explain the necessary steps to uninstall libvigraimpex-doc on Ubuntu 21.10 (Impish Indri):

$ sudo apt remove libvigraimpex-doc $ sudo apt autoclean && sudo apt autoremove

3. Information about the libvigraimpex-doc package on Ubuntu 21.10 (Impish Indri)

Package: libvigraimpex-doc
Architecture: all
Version: 1.11.1+dfsg-8ubuntu1
Priority: optional
Section: universe/doc
Source: libvigraimpex
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 53283
Suggests: libvigraimpex-dev, python-vigra-doc
Filename: pool/universe/libv/libvigraimpex/libvigraimpex-doc_1.11.1+dfsg-8ubuntu1_all.deb
Size: 5388780
MD5sum: bce824c14d4718558c32b571ea9e190d
SHA1: 0fd99578adc34987a9a5cf364ebb7478f0b29275
SHA256: d9ada7f51a7e6ad4cabc0fc161f2828b288e4ae0ad85ee5759691269edb1a3db
SHA512: fb4c28570d36cad008026893db93fe0cf3f687ffdb08a1e08596f99a83bfb21bcdb6535f5a845ef30d9be6865caa70130ed08ea5ac8e6d4e2e458743ddbb55e8
Homepage: https://ukoethe.github.io/vigra/
Description-en: Documentation for the C++ computer vision library
Vision with Generic Algorithms (VIGRA) is a computer vision library
that puts its main emphasis on flexible algorithms, because
algorithms represent the principle know-how of this field. The
library was consequently built using generic programming as
introduced by Stepanov and Musser and exemplified in the C++ Standard
Template Library. By writing a few adapters (image iterators and
accessors) you can use VIGRA's algorithms on top of your data
structures, within your environment.
.
This package contains documentation for the VIGRA library.
Description-md5: 68e91538adca7e7262cb997daf253940