onnxruntime-openvino 1.12.0

Requirements

• Ubuntu 18.04, 20.04, RHEL(CPU only) or Windows 10 - 64 bit

• Python 3.7, 3.8 or 3.9 for Linux and only Python3.9 for Windows

This package supports:

• Intel® CPUs

• Intel® integrated GPUs

• Intel® Movidius™ Vision Processing Units (VPUs).

Please Note for VAD-M use Docker installation / Build from Source for Linux.

pip3 install onnxruntime-openvino==1.12.0

Please install OpenVINO™ PyPi Package separately for Windows. For installation instructions on Windows please refer to OpenVINO™ Execution Provider for ONNX Runtime for Windows.

OpenVINO™ Execution Provider for ONNX Runtime Linux Wheels comes with pre-built libraries of OpenVINO™ version 2022.1.0 eliminating the need to install OpenVINO™ separately. The OpenVINO™ libraries are prebuilt with CXX11_ABI flag set to 0.

The package also includes module that is used by torch-ort-inference to accelerate inference for PyTorch models with OpenVINO Execution Provider. See torch-ort-inference for more details.

For more details on build and installation please refer to Build.

Usage

By default, Intel® CPU is used to run inference. However, you can change the default option to either Intel® integrated GPU or Intel® VPU for AI inferencing. Invoke the provider config device type argument to change the hardware on which inferencing is done.

For more API calls and environment variables, see Usage.

Samples

To see what you can do with OpenVINO™ Execution Provider for ONNX Runtime, explore the demos located in the Examples.

Docker Support

The latest OpenVINO™ EP docker image can be downloaded from DockerHub. For more details see Docker ReadMe.

Prebuilt Images

• Please find prebuilt docker images for Intel® CPU and Intel® iGPU on OpenVINO™ Execution Provider Release Page.

License

OpenVINO™ Execution Provider for ONNX Runtime is licensed under MIT. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.

Support

Please submit your questions, feature requests and bug reports via GitHub Issues.

How to Contribute

We welcome community contributions to OpenVINO™ Execution Provider for ONNX Runtime. If you have an idea for improvement:

• Share your proposal via GitHub Issues.

• Submit a Pull Request.