OpenVINO™ Runtime

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 already finished developing your models and converting them to the OpenVINO model format, you can install OpenVINO Runtime to deploy your applications on various devices. The OpenVINO™ Runtime Python package includes a set of libraries for an easy inference integration with your products.

System Requirements

Before you start the installation, check the supported operating systems and required Python* versions. The complete list of supported hardware is available in the System Requirements.

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 can be installed on other versions of Linux and Windows OSes, but only the specific versions above are fully validated.

Install the OpenVINO™ Runtime Package

Step 1. Set Up Python Virtual Environment

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. For example, on Ubuntu execute the following command to get pip installed: sudo apt install python3-venv python3-pip.

Step 2. Activate Virtual Environment

On Linux and macOS:

source openvino_env/bin/activate

On Windows:

openvino_env\Scripts\activate

Step 3. Set Up and Update PIP to the Highest Version

Run the command below:

python -m pip install --upgrade pip

Step 4. Install the Package

Run the command below:

pip install openvino

Step 5. Verify that the Package Is Installed

Run the command below:

python -c "from openvino.runtime import Core; print(Core().available_devices)"

If installation was successful, you will see the list of available devices.

Troubleshooting

For general troubleshooting steps and issues, see Troubleshooting Guide for OpenVINO Installation. The following sections also provide explanations to several error messages.

Errors with Installing via PIP for Users in China

Users in China might 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 -i https://mirrors.aliyun.com/pypi/simple/
  

  Use the --trusted-host parameter if the URL above is http instead of https.

ERROR:root:Could not find the Inference Engine or nGraph Python API.

On Windows*, some libraries are 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.

ImportError: libpython3.8.so.1.0: cannot open shared object file: No such file or directory

To resolve missing external dependency on Ubuntu*, execute the following command:

sudo apt-get install libpython3.8

Additional Resources

• Intel® Distribution of OpenVINO™ toolkit
• OpenVINO™ Documentation
• OpenVINO™ Notebooks
• OpenVINO Installation Selector Tool

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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.