How to Install and Uninstall v-hacd-devel.noarch Package on Red Hat Enterprise Linux 9 (RHEL 9)
Last updated: November 25,2024
1. Install "v-hacd-devel.noarch" package
This guide covers the steps necessary to install v-hacd-devel.noarch on Red Hat Enterprise Linux 9 (RHEL 9)
$
sudo dnf update
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$
sudo dnf install
v-hacd-devel.noarch
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2. Uninstall "v-hacd-devel.noarch" package
This is a short guide on how to uninstall v-hacd-devel.noarch on Red Hat Enterprise Linux 9 (RHEL 9):
$
sudo dnf remove
v-hacd-devel.noarch
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$
sudo dnf autoremove
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3. Information about the v-hacd-devel.noarch package on Red Hat Enterprise Linux 9 (RHEL 9)
Last metadata expiration check: 1:38:51 ago on Mon Feb 26 07:04:30 2024.
Available Packages
Name : v-hacd-devel
Version : 4.1.0
Release : 1.el9
Architecture : noarch
Size : 774 k
Source : v-hacd-4.1.0-1.el9.src.rpm
Repository : epel
Summary : Development files for V-HACD
URL : https://github.com/kmammou/v-hacd
License : BSD-3-Clause
Description : The V-HACD library decomposes a 3D surface into a set of “near” convex parts.
:
: Why do we need approximate convex decomposition?
:
: Collision detection is essential for realistic physical interactions in video
: games and computer animation. In order to ensure real-time interactivity with
: the player/user, video game and 3D modeling software developers usually
: approximate the 3D models composing the scene (e.g. animated characters, static
: objects…) by a set of simple convex shapes such as ellipsoids, capsules or
: convex-hulls. In practice, these simple shapes provide poor approximations for
: concave surfaces and generate false collision detection.
:
: Convex-hull vs. ACD
:
: A second approach consists in computing an exact convex decomposition of a
: surface S, which consists in partitioning it into a minimal set of convex
: sub-surfaces. Exact convex decomposition algorithms are NP-hard and
: non-practical since they produce a high number of clusters. To overcome these
: limitations, the exact convexity constraint is relaxed and an approximate
: convex decomposition of S is instead computed. Here, the goal is to determine a
: partition of the mesh triangles with a minimal number of clusters, while
: ensuring that each cluster has a concavity lower than a user defined
: threshold.
:
: The v-hacd-devel package contains the header-only library for developing
: applications that use V-HACD.
Available Packages
Name : v-hacd-devel
Version : 4.1.0
Release : 1.el9
Architecture : noarch
Size : 774 k
Source : v-hacd-4.1.0-1.el9.src.rpm
Repository : epel
Summary : Development files for V-HACD
URL : https://github.com/kmammou/v-hacd
License : BSD-3-Clause
Description : The V-HACD library decomposes a 3D surface into a set of “near” convex parts.
:
: Why do we need approximate convex decomposition?
:
: Collision detection is essential for realistic physical interactions in video
: games and computer animation. In order to ensure real-time interactivity with
: the player/user, video game and 3D modeling software developers usually
: approximate the 3D models composing the scene (e.g. animated characters, static
: objects…) by a set of simple convex shapes such as ellipsoids, capsules or
: convex-hulls. In practice, these simple shapes provide poor approximations for
: concave surfaces and generate false collision detection.
:
: Convex-hull vs. ACD
:
: A second approach consists in computing an exact convex decomposition of a
: surface S, which consists in partitioning it into a minimal set of convex
: sub-surfaces. Exact convex decomposition algorithms are NP-hard and
: non-practical since they produce a high number of clusters. To overcome these
: limitations, the exact convexity constraint is relaxed and an approximate
: convex decomposition of S is instead computed. Here, the goal is to determine a
: partition of the mesh triangles with a minimal number of clusters, while
: ensuring that each cluster has a concavity lower than a user defined
: threshold.
:
: The v-hacd-devel package contains the header-only library for developing
: applications that use V-HACD.