OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Go to file
2022-03-11 10:45:31 +03:00
.ci Update Linux Azure CI (#10739) 2022-03-02 18:00:32 +03:00
.github Fix NCC (#10105) 2022-02-03 16:51:26 +03:00
cmake ncc build fixes (#10367) 2022-03-09 13:42:06 +03:00
docs Update APT instructions according to repository configuration (#10869) 2022-03-11 10:45:31 +03:00
licensing Removed duplicated words (#10754) 2022-03-03 06:50:54 +00:00
samples ncc build fixes (#10367) 2022-03-09 13:42:06 +03:00
scripts Fix MacOS DYLD_LIBRARY_PATH export (#10750) 2022-03-03 00:36:02 +03:00
src [GNA] Support of overload correction for MatMul with 2 non-constant layers (#10447) 2022-03-10 15:16:17 +03:00
tests Update nightly memcheck models scope (#10709) 2022-03-02 18:03:28 +08:00
thirdparty upd open-model-zoo, upd docs, upd ac cfgs (#10676) 2022-03-09 11:48:47 +03:00
tools [POT] Update BC with the Parameter nodes connection (#10848) 2022-03-10 10:28:47 +03:00
.gitattributes [POT] Update tests with new data (#8209) 2021-10-27 12:40:19 +03:00
.gitignore [Python API] Move old python bindings (#9134) 2022-01-24 13:16:07 +03:00
.gitmodules [GPU] Moved onednn_gpu to plugin folder (#9458) 2021-12-29 11:06:14 +03:00
CMakeLists.txt Moved ngraphConfig.cmake to root (#10618) 2022-02-25 15:47:21 +03:00
CODEOWNERS [GPU] GPU plugin docs (#10734) 2022-03-10 15:01:52 +03:00
CONTRIBUTING.md Add original contribution guide to root (#10644) 2022-02-24 16:13:21 +00:00
install_build_dependencies.sh Update year to 2022 in copyright notice (#9755) 2022-01-19 01:07:49 +03:00
Jenkinsfile Beautify Jenkinsfile a little bit 2021-05-31 15:24:56 +03:00
LICENSE Publishing R3 2018-10-16 13:45:03 +03:00
README.md Docs: Changed OpenVINO Runtime User Guide integration (#10187) 2022-03-02 20:07:52 +03:00
SECURITY.md Added SECURITY.md back (#3177) 2020-11-17 16:44:44 +03:00

OpenVINO™ Toolkit

Stable release Apache License Version 2.0 GitHub branch checks state Azure DevOps builds (branch) PyPI Downloads

This toolkit allows developers to deploy pre-trained deep learning models through a high-level OpenVINO™ Runtime C++ and Python APIs integrated with application logic.

This open source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi.

Repository components

License

OpenVINO™ Toolkit is licensed under Apache License Version 2.0. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.

Resources

Support

Please report questions, issues and suggestions using:


* Other names and brands may be claimed as the property of others.