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(R) CPUs and Intel(R) 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*.
最近的项目中,有客户提出在既有的CPU服务器上运行CNN的方案,即不添加nivida显卡已降低成本。因此调研Intel的OpenVINO方案。
OpenVINO是Intel提供的给予卷积神经网络的计算机视觉开发包。目的在能够快速的在Intel的硬件方案上部署和开发计算机视觉工程和方案。OpenVINO支持多种Intel硬件方案,包括CPU、集成显卡、Intel Movidius算力棒以及FPGA等。
官方给出的硬件和系统需求为:
Processors
6th-8th Generation Intel® Core™
Intel® Xeon® v5 family
Intel® Xeon® v6 family
Intel® Pentium® processor N4200/5, N3350/5, N3450/5 with Intel® HD Graphics
Intel Movidius NCS
Operating Systems
Ubuntu* 16.04 long-term support (LTS), 64-bit
CentOS* 7.4 or higher, 64-bit
Yocto Project* Poky Jethro* v2.0.3, 64-bit (for target only)
Deep Learning Deployment Toolkit is licensed under Apache License Version 2.0.
- OpenVINO™ Release Notes
- Inference Engine build instructions
We welcome community contributions to the Deep Learning Deployment Toolkit repository. If you have an idea how to improve the product, please share it with us doing the following steps:
- Make sure you can build the product and run all tests and samples with your patch
- In case of a larger feature, provide a relevant unit tests and sample
- Submit a pull request at https://github.com/opencv/dldt/pulls
We will review your contribution and, if any additional fixes or modifications are necessary, may give some feedback to guide you. When accepted, your pull request will be merged into GitHub* repositories.
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.
Please report questions, issues and suggestions using:
- #dldt tag on StackOverflow*
- GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.