NOTE: The openvino-nightly PyPI module has been deprecated and will be discontinued with 2024.5 release. End-users should proceed with the Simple PyPI nightly repo instead. More information in Release Policy.
NOTE: This version is pre-release software and has not undergone full release validation or qualification. No support is offered on pre-release software and APIs/behavior are subject to change. It should NOT be incorporated into any production software/solution and instead should be used only for early testing and integration while awaiting a final release version of this software.
Intel® Distribution of OpenVINO™ toolkit is an open-source toolkit for optimizing and deploying AI inference. It can be used to develop applications and solutions based on deep learning tasks, such as: emulation of human vision, automatic speech recognition, natural language processing, recommendation systems, etc. It provides high-performance and rich deployment options, from edge to cloud.
If you have chosen a model, you can integrate it with your application through OpenVINO™ and deploy it on various devices. The OpenVINO™ Python package includes a set of libraries for easy inference integration with your products.
Commit used for current package: https://github.com/openvinotoolkit/openvino/commit/84e683737918e8169ec0fe05132c5157ece7754c
Before you start the installation, check the supported operating systems and required Python* versions. The complete list of supported hardware is available on the System Requirements page.
C++ libraries are also required for the installation on Windows*. To install that, you can download the Visual Studio Redistributable file (.exe).
NOTE: This package may work on other Linux and Windows versions but only the versions specified in system requirements are fully validated.
Use a virtual environment to avoid dependency conflicts. To create a virtual environment, use the following commands:
On Windows:
python -m venv openvino_env
On Linux and macOS:
python3 -m venv openvino_env
NOTE: On Linux and macOS, you may need to install pip.
On Windows:
openvino_env\Scripts\activate
On Linux and macOS:
source openvino_env/bin/activate
Run the command below:
python -m pip install --upgrade pip
Run the command below:
pip install openvino-nightly
Run the command below:
python -c "from openvino import Core; print(Core().available_devices)"
If installation was successful, you will see the list of available devices.
| Component | Content | Description |
|---|---|---|
| OpenVINO Runtime | `openvino package` | OpenVINO Runtime is a set of C++ libraries with C and Python bindings providing a common API to deliver inference solutions on the platform of your choice. Use the OpenVINO Runtime API to read PyTorch, TensorFlow, TensorFlow Lite, ONNX, and PaddlePaddle models and execute them on preferred devices. OpenVINO Runtime uses a plugin architecture and includes the following plugins: CPU, GPU, Auto Batch, Auto, Hetero, |
| OpenVINO Model Converter (OVC) | `ovc` | OpenVINO Model Converter converts models that were trained in popular frameworks to a
format usable by OpenVINO components. Supported frameworks include ONNX, TensorFlow, TensorFlow Lite, and PaddlePaddle. |
| Benchmark Tool | `benchmark_app` | Benchmark Application** allows you to estimate deep learning inference performance on supported devices for synchronous and asynchronous modes. |
For general troubleshooting steps and issues, see Troubleshooting Guide for OpenVINO Installation. The following sections also provide explanations to several error messages.
Users in China may encounter errors while downloading sources via PIP during OpenVINO™ installation. To resolve the issues, try the following solution:
Add the download source using the -i parameter with the Python pip command. For example:
pip install openvino-nightly -i https://mirrors.aliyun.com/pypi/simple/
Use the --trusted-host parameter if the URL above is http instead of https.
On Windows, additional libraries may be necessary to run OpenVINO. To resolve this issue, install the C++ redistributable (.exe). You can also view a full download list on the official support page.
To resolve missing external dependency on Ubuntu*, execute the following command:
sudo apt-get install libpython3.8
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LEGAL NOTICE: Your use of this software and any required dependent software (the “Software Package”) is subject to the terms and conditions of the Apache 2.0 License for the Software Package, which may also include notices, disclaimers, or license terms for third party or open source software included in or with the Software Package, and your use indicates your acceptance of all such terms. Please refer to the “third-party-programs.txt” or other similarly-named text file included with the Software Package for additional details.
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Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries. Other names and brands may be claimed as the property of others.
NOTE: This version is pre-release software and has not undergone full release validation or qualification. No support is offered on pre-release software and APIs/behavior are subject to change. It should NOT be incorporated into any production software/solution and instead should be used only for early testing and integration while awaiting a final release version of this software.
FAQs
OpenVINO(TM) Runtime
We found that openvino-nightly demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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