Maxim Shevtsov 72aee062cb next iteration after discussion with Yuri (#11197)
* next iteration after discussion with Yuri

* WIP tput

* Basic/Advanced Flow

* brushing/links

* wording, testing the failing link

* refactored levels, added hash

* added advanced tput to the TOC (required by sphinx)

* changed wording of the title to be more pro-active

* minor misprint, etc

* emphasized the flow names

* Update two paragraphs in performance hints docs

(cherry picked from commit 61415fd91f417b70eae595cc15976dec7af0865b)

* minor brushing

* e2e flow in the app design

* no separate hints doc

* minor brushing

* final, neat-picking brushing

Co-authored-by: Helena <helena.kloosterman@intel.com>
2022-03-29 16:32:55 +03:00
2022-03-16 15:01:20 +03:00
2022-02-03 16:51:26 +03:00
2022-03-28 15:52:13 +03:00
2022-03-15 17:10:14 +03:00
2021-05-31 15:24:56 +03:00
2018-10-16 13:45:03 +03:00
2022-03-28 15:52:13 +03:00
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.

Languages
C++ 80.5%
Python 15.5%
C 2.8%
CMake 0.9%
Cython 0.1%