Install Intel® Distribution of OpenVINO™ Toolkit from PyPI Repository

Note

Note that the PyPi distribution:

• offers the Python API only

• is dedicated to users of all major OSes: Windows, Linux, and macOS (all x86_64 / arm64 architectures)

• Windows and Linux do not offer support for GNA and NPU inference

• macOS offers support only for CPU inference

System Requirements

Full requirement listing is available in:

System Requirements Page

PyPI OpenVINO page

Processor Notes

To see if your processor includes the integrated graphics technology and supports iGPU inference, refer to:

Product Specifications

Installing OpenVINO Runtime

Step 1. Set Up Python Virtual Environment

Use a virtual environment to avoid dependency conflicts. To create a virtual environment, use the following command:

Windows

python -m venv openvino_env

Linux and macOS

python3 -m venv openvino_env

Step 2. Activate Virtual Environment

Windows

openvino_env\Scripts\activate

Linux and macOS

source openvino_env/bin/activate

Important

The above command must be re-run every time a new command terminal window is opened.

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

Use the following command:

python -m pip install --upgrade pip

Step 4. Install the Package

Use the following command:

python -m pip install openvino

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.

Congratulations! You’ve just Installed OpenVINO! For some use cases you may still need to install additional components. Check the list of additional configurations to see if your case needs any of them.

What’s Next?

Now that you’ve installed OpenVINO Runtime, you’re ready to run your own machine learning applications! Learn more about how to integrate a model in OpenVINO applications by trying out the following tutorials.

Try the Python Quick Start Example to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.

Get started with Python

Visit the Tutorials page for more Jupyter Notebooks to get you started with OpenVINO, such as:

• OpenVINO Python API Tutorial

• Basic image classification program with Hello Image Classification

• Convert a PyTorch model and use it for image background removal

Additional Resources

• Intel® Distribution of OpenVINO™ toolkit home page: https://software.intel.com/en-us/openvino-toolkit

• For IoT Libraries & Code Samples, see Intel® IoT Developer Kit.