docs/articles_en/get-started/install-openvino/install-openvino-pip.rst
.. meta:: :description: Learn how to install OpenVINO™ Runtime on Windows, Linux, and macOS operating systems, using a PyPi package.
.. note::
Note that the PyPi distribution:
Before installing OpenVINO, see the
:doc:System Requirements page <../../../about-openvino/release-notes-openvino/system-requirements>.
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:
.. tab-set::
.. tab-item:: Windows
:sync: windows
.. code-block:: sh
python -m venv openvino_env
.. tab-item:: Linux and macOS
:sync: linux-and-macos
.. code-block:: sh
python3 -m venv openvino_env
Step 2. Activate Virtual Environment ++++++++++++++++++++++++++++++++++++
.. tab-set::
.. tab-item:: Windows
:sync: windows
.. code-block:: sh
openvino_env\Scripts\activate
.. tab-item:: Linux and macOS
:sync: linux-and-macos
.. code-block:: sh
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:
.. code-block:: sh
python -m pip install --upgrade pip
Step 4. Install the Package +++++++++++++++++++++++++++
Use the following command to install either the base or GenAI OpenVINO package:
.. code-block:: python
python -m pip install openvino
Step 5. Verify that the Package Is Installed ++++++++++++++++++++++++++++++++++++++++++++
Run the command below:
.. code-block:: sh
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
:doc:list of additional configurations <./configurations>
to see if your case needs any of them.
| Simplified Build and Integration
| The package includes CMake configurations, precompiled static libraries, and headers, which
can be easily accessed through the Python API. You can use the get_cmake_path() method to
retrieve the paths to the CMake configurations and libraries:
.. code-block:: python
from openvino.utils import get_cmake_path cmake_path = get_cmake_path()
For detailed instructions on how to use these configurations in your build setup, check out the
:ref:Create a library with extensions <create_a_library_with_extensions> section.
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.
.. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif :width: 400
Try the Python Quick Start Example <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-monodepth>__
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 :doc:Tutorials <../../../get-started/learn-openvino/interactive-tutorials-python> page for more
Jupyter Notebooks to get you started with OpenVINO, such as:
OpenVINO Python API Tutorial <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/openvino-api>__Basic image classification program with Hello Image Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hello-world>__Convert a PyTorch model and use it for image background removal <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-background-removal>__Additional Resources ####################
toolkit home page <https://software.intel.com/en-us/openvino-toolkit>__