Ilya Lavrenov 0df7dab345 New IRC package structure (#6255)
* OV new package structure

* Fixes

* More fixes

* Fixed code style in ngraph tests

* Fixes

* Paths to setupvars inside demo scripts

* Fixed demo_security_barrier_camera.sh

* Added setupvars.sh to old location as well

* Fixed path

* Fixed MO install path in .co

* Fixed install of public headers

* Fixed frontends installation

* Updated DM config files

* Keep opencv in the root

* Improvements

* Fixes for demo scripts

* Added path to TBB

* Fix for MO unit-tests

* Fixed tests on Windows

* Reverted arch

* Removed arch

* Reverted arch back: second attemp

* System type

* Fix for Windows

* Resolve merge conflicts

* Fixed path

* Path for Windows

* Added debug for Windows

* Added requirements_dev.txt to install

* Fixed wheel's setup.py

* Fixed lin build

* Fixes after merge

* Fix 2

* Fixes

* Frontends path

* Fixed deployment manager

* Fixed Windows

* Added cldnn unit tests installation

* Install samples

* Fix samples

* Fix path for samples

* Proper path

* Try to fix MO hardcodes

* samples binary location

* MO print

* Added install for libopencv_c_wrapper.so

* Added library destination

* Fixed install rule for samples

* Updated demo scripts readme.md

* Samples

* Keep source permissions for Python samples

* Fixed python

* Updated path to fast run scripts

* Fixed C samples tests

* Removed debug output

* Small fixes

* Try to unify prefix
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OpenVINO™ Toolkit

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

This toolkit allows developers to deploy pre-trained deep learning models through a high-level C++ Inference Engine API integrated with application logic.

This open source version includes several components: namely Model Optimizer, nGraph and Inference Engine, 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 Caffe*, TensorFlow*, MXNet* and ONNX*.

Repository components:

License

Deep Learning Deployment 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%