Package: cvcuda-test
CV-CUDACV-CUDA is an open-source project that enables building efficient cloud-scale
Artificial Intelligence (AI) imaging and computer vision (CV) applications. It
uses GPU acceleration to help developers build highly efficient pre- and post-
processing pipelines. CV-CUDA originated as a collaborative effort betweenNVIDIAandByteDance.Refer to ourDeveloper Guidefor more information on the
operators avaliable as of release v0.2.0-alpha.Getting StartedTo get a local copy up and running follow these steps.Pre-requisitesLinux distro:Ubuntu x86_64 >= 18.04WSL2 with Ubuntu >= 20.04 (tested with 20.04)CUDA Driver >= 11.7 (Not tested on 12.0)GCC >= 11.0Python >= 3.7cmake >= 3.22InstallationThe following steps describe how to install CV-CUDA from pre-built install
packages. Choose the installation method that meets your environment needs.Tar File Installationtar -xvf nvcv-lib-0.2.0-cuda11-x86_64-linux.tar.xzDEB File Installationsudo dpkg -i nvcv-lib-0.2.0-cuda11-x86_64-linux.debPython WHL File Installationpip install nvcv_python-0.2.0-cp38-cp38-linux_x86_64.whlBuild from SourceFollow these instruction to successfully build CV-CUDA from source:Build CV-CUDAcd ~/cvcuda
ci/build.shThis will compile a x86 release build of CV-CUDA insidebuild-reldirectory.
The library is in build-rel/lib, docs in build-rel/docs and executables
(tests, etc...) in build-rel/bin.The script accepts some parameters to control the creation of the build tree:ci/build.sh [release|debug] [output build tree path]By default it builds for release.If output build tree path isn't specified, it'll bebuild-relfor release
builds, and build-deb for debug.Build Documentationci/build_docs.sh [build folder]Example:
`ci/build_docs.sh buildBuild Samples./ci/build_samples.sh [build folder](For instructions on how to compile samples outside of the CV-CUDA project,
see theSamplesdocumentation)Run TestsThe tests are in<buildtree>/bin. You can run the script below to run all
tests at once. Here's an example when build tree is created inbuild-relbuild-rel/bin/run_tests.shRun SamplesThe samples are installed in<buildtree>/bin. You can run the script below
to download and serialize the model and run the sample with the test data
provided../ci/run_samples.shPackage installersFrom a succesfully built project, installers can be generated using cpack:cdbuild-rel
cpack.This will generate in the build directory both Debian installers and tarballs
(*.tar.xz), needed for integration in other distros.For a fine-grained choice of what installers to generate, the full syntax is:cmake . -G [DEB|TXZ]DEB for Debian packagesTXZ for *.tar.xz tarballs.ContributingCV-CUDA is an open source project. As part of the Open Source Community, we are
committed to the cycle of learning, improving, and updating that makes this
community thrive. However, as of release v0.2.0-alpha, CV-CUDA is not yet ready
for external contributions.To understand the process for contributing the CV-CUDA, see ourContributingpage. To understand our committment to the Open
Source Community, and providing an environment that both supports and respects
the efforts of all contributors, please read ourCode of Conduct.LicenseCV-CUDA operates under theApache-2.0license.SecurityCV-CUDA, as a NVIDIA program, is committed to secure development practices.
Please read ourSecuritypage to learn more.AcknowledgementsCV-CUDA is developed jointly by NVIDIA and ByteDance.