Installation
Pre-requisites
This section describes the recommended dependencies to install CV-CUDA.
Ubuntu >= 20.04
CUDA driver >= 11.7
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 here
Tar File Installation
Unzip the cvcuda runtime package:
tar -xvf cvcuda-lib-x.x.x-cuda11-x86_64-linux.tar.xz
Unzip the cvcuda developer package:
tar -xvf cvcuda-dev-x.x.x-cuda11-x86_64-linux.tar.xz
Unzip the cvcuda python package:
tar -xvf cvcuda-python3.*-x.x.x-cuda11-x86_64-linux.tar.xz
[Optional] Unzip the tests.
tar -xvf cvcuda-tests-cuda11-x86_64-linux.tar.xz
Debian Installation
Install the runtime library.
dpkg -i cvcuda-lib-x.x.x-cuda11-x86_64-linux.deb
Install the developer library.
dpkg -i cvcuda-dev-x.x.x-cuda11-x86_64-linux.deb
Install the python bindings
dpkg -i cvcuda-python3.*-x.x.x-cuda11-x86_64-linux.deb
[Optional] Install the tests.
sudo dpkg -i cvcuda-tests-x.x.x-cuda11-x86_64-linux.deb
Python Wheel File Installation
Download the appropriate .whl file for your computer architecture, Python and CUDA version from here
Execute the following command to install appropriate CV-CUDA Python wheel
pip install cvcuda_<cu_ver>-0.6.0b0-cp<py_ver>-cp<py_ver>-linux_<arch>.whl
where <cu_ver> is the desired CUDA 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.