c880ecb78a
* [GNA] Update GNA lib + propagate QoS timeout to the calling app (#1188) * [GNA] Remove empty PWL (#1459) * [GNA] Support timeout value set in Wait (#1499) * [GNA] Bump GNA2 version to 1010 (#1510) * [GNA] stored request id for completed sync infer request in order to get status later using wait() (#1458) * stored request id for completed async infer request in order to get it's status later * preserved status not started for multiple sequential calls to wait() Co-authored-by: Denis Orlov <denis.orlov@intel.com> * [GNA] Fix callbacks (#1607) * [GNA] Bump GNA2 version to 1047 (#1614) * merge documentation updates from 2020/4 branch (#1671) * update system requirements (#1321) * update release version in readme * Doc Migration from Gitlab (#1289) * Update FakeQuantize_1.md * Update performance_benchmarks.md * Updates graphs for FPGA * Update performance_benchmarks.md * Change DL Workbench structure (#1) * Changed DL Workbench structure * Update performance_benchmarks_faq.md * Fixes in DL Workbench layout * Fixes for CVS-31290 * [DL Workbench] Minor correction * Fix for CVS-30955 * Added nGraph deprecation notice as requested by Zoe * fix broken links in api doxy layouts * Fixed POT TOC * Update PAC_Configure.md PAC DCP 1.2.1 install guide. * Update inference_engine_intro.md * Update opset.md * Update VisionAcceleratorFPGA_Configure.md (#1378) Updated from 2020.3 to 2020.4 Co-authored-by: domi2000 <domi2000@users.noreply.github.com> * Updated documentation for 2020.4 (#1434) * Updated documentation for 2020.4 * Updated Core::ReadNetwork documentation (#1178) Co-authored-by: Ilya Churaev <ilya.churaev@intel.com> Co-authored-by: Nikolay Tyukaev <nikolay.tyukaev@intel.com> Co-authored-by: domi2000 <domi2000@users.noreply.github.com> Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com> Co-authored-by: Ilya Churaev <ilya.churaev@intel.com> * Documentation updates for 2020.4 (#1672) (#1729) * Doc updates * 2020.4 doc updates * Removed </br> tag * Minor fix * Minor fixes * Updated documentation for 2020.4 (#1434) * Updated documentation for 2020.4 * Updated Core::ReadNetwork documentation (#1178) * Fixed docs Co-authored-by: Ilya Churaev <ilya.churaev@intel.com> Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com> Co-authored-by: Ilya Churaev <ilya.churaev@intel.com> Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com> Co-authored-by: Ilya Churaev <ilya.churaev@intel.com> Co-authored-by: Pavel Rodionov <pavel.rodionov@intel.com> Co-authored-by: Eugene Smirnov <eugene.smirnov@intel.com> Co-authored-by: Alexey Suhov <alexey.suhov@intel.com> Co-authored-by: Ilya Churaev <ilya.churaev@intel.com> Co-authored-by: Nikolay Tyukaev <nikolay.tyukaev@intel.com> Co-authored-by: domi2000 <domi2000@users.noreply.github.com> Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com> Co-authored-by: Andrey Zaytsev <andrey.zaytsev@intel.com>
OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository
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 two components: namely Model Optimizer and Inference Engine, as well as CPU, GPU 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.
Documentation
- OpenVINO™ Release Notes
- OpenVINO™ Inference Engine Build Instructions
- Get Started with Deep Learning Deployment Toolkit on Linux*
- Introduction to Deep Learning Deployment Toolkit
- Inference Engine Developer Guide
- Model Optimizer Developer Guide
How to Contribute
See CONTRIBUTING for details. Thank you!
Support
Please report questions, issues and suggestions using:
- The
openvinotag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.