OpenVINO™

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/a7ccc5e0efcc55455e4f2988489a64d70e6be0f7

System Requirements

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.

Install OpenVINO™

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.

Step 2. Activate the Virtual Environment

On Windows:

openvino_env\Scripts\activate

On Linux and macOS:

source openvino_env/bin/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-nightly

Step 5. Verify that the Package Is Installed

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.

What's in the Package

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 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.

ERROR:root:Could not find OpenVINO Python API.

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.

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.