Installation

Pre-requisites

This section describes the recommended dependencies to install CV-CUDA.

  • Ubuntu >= 20.04 (22.04 recommended for building the documentation)

  • CUDA >= 11.7 (cuda 12 required for samples)

  • NVIDIA driver r525 or later (r535 required for samples)

Setup

The following steps describe how to install CV-CUDA. Choose the installation method that meets your environment needs. You can download the CV-CUDA tar, deb or wheel packages from the asset section

  • Tar File Installation

    Unzip the cvcuda runtime package:

    tar -xvf cvcuda-lib-<x.x.x>-<cu_ver>-<arch>-linux.tar.xz

    Unzip the cvcuda developer package:

    tar -xvf cvcuda-dev-<x.x.x>-<cu_ver>-<arch>-linux.tar.xz

    Unzip the cvcuda python package:

    tar -xvf cvcuda-python<py_ver>-<x.x.x>-<cu_ver>-<arch>-linux.tar.xz

    [Optional] Unzip the tests.

    tar -xvf cvcuda-tests-<x.x.x>-<cu_ver>-<arch>-linux.tar.xz

  • Debian Installation

    Install the runtime library.

    sudo apt install -y ./cvcuda-lib-<x.x.x>-<cu_ver>-<arch>-linux.deb

    Install the developer library.

    sudo apt install -y ./cvcuda-dev-<x.x.x>-<cu_ver>-<arch>-linux.deb

    Install the python bindings

    sudo apt install -y ./cvcuda-python<py_ver>-<x.x.x>-<cu_ver>-<arch>-linux.deb

    [Optional] Install the tests.

    sudo apt install -y ./cvcuda-tests-<x.x.x>-<cu_ver>-<arch>-linux.deb

  • Python Wheel File Installation

    Download the appropriate .whl file for your computer architecture, Python and CUDA version from the asset section of the latest release

    Execute the following command to install appropriate CV-CUDA Python wheel

    pip install cvcuda_<cu_ver>-<x.x.x>-cp<py_ver>-cp<py_ver>-linux_<arch>.whl

    where <cu_ver> is the desired CUDA version, <x.x.x> the CV-CUDA release version, <py_ver> the desired Python version and <arch> the desired architecture.

    Please note that the Python wheels provided are standalone, they include both the C++/CUDA libraries and the Python bindings.

  • Verifying the Debian or TAR installation on Linux

    To verify that CV-CUDA is installed and is running properly, run the tests from the install folder for tests. Default installation path is /opt/nvidia/cvcuda0/bin.

    cd /opt/nvidia/cvcuda0/bin
./run_tests.sh

If CV-CUDA is properly installed and running on your Linux system, all tests will pass.

  • Running the samples on Linux.

    Follow the instructions written in the README.md file of the samples directory.