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Install Intel® Distribution of OpenVINO™ Toolkit from PyPI Repository
You can install both OpenVINO™ Runtime and OpenVINO Development Tools through the PyPI repository. This page provides the main steps for installing OpenVINO Runtime.
NOTE: From the 2022.1 release, the OpenVINO™ Development Tools can only be installed via PyPI. See Install OpenVINO Development Tools for detailed steps.
Installing OpenVINO Runtime
For system requirements and troubleshooting, see https://pypi.org/project/openvino/.
Step 1. Set Up Python Virtual Environment
Use a virtual environment to avoid dependency conflicts.
To create a virtual environment, use the following command:
@sphinxdirective
.. tab:: Linux and macOS
.. code-block:: sh
python3 -m venv openvino_env
.. tab:: Windows
.. code-block:: sh
python -m venv openvino_env
@endsphinxdirective
Step 2. Activate Virtual Environment
@sphinxdirective
.. tab:: On Linux and macOS
.. code-block:: sh
source openvino_env/bin/activate
.. tab:: On Windows
.. code-block:: sh
openvino_env\Scripts\activate
@endsphinxdirective
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:
pip install openvino
Step 5. Verify that the Package Is Installed
Run the command below:
python -c "from openvino.runtime import Core"
If installation was successful, you will not see any error messages (no console output).
Installing OpenVINO Development Tools
OpenVINO Development Tools include Model Optimizer, Benchmark Tool, Accuracy Checker, Post-Training Optimization Tool and Open Model Zoo tools including Model Downloader. If you want to install OpenVINO Development Tools, OpenVINO Runtime will also be installed as a dependency, so you don't need to install OpenVINO Runtime separately.
See Install OpenVINO™ Development Tools for detailed steps.
What's Next?
Now you may continue with the following tasks:
- To convert models for use with OpenVINO, see Model Optimizer Developer Guide.
- See pre-trained deep learning models in our Open Model Zoo.
- Try out OpenVINO via OpenVINO Notebooks.
- To write your own OpenVINO™ applications, see OpenVINO Runtime User Guide.
- See sample applications in OpenVINO™ Toolkit Samples Overview.
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.