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openvino/docs/install_guides/installing-openvino-yum.md

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Install OpenVINO™ Runtime on Linux From YUM Repository

@sphinxdirective

With the OpenVINO™ 2022.3 release, you can install OpenVINO Runtime on Linux using the YUM repository. OpenVINO™ Development Tools can be installed via PyPI only. See Installing Additional Components <#step-3-optional-install-additional-components>__ for more information.

See the Release Notes <https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino-2022-3-lts-relnotes.html>_ for more information on updates in the latest release.

Installing OpenVINO Runtime from YUM is recommended for C++ developers. If you are working with Python, the PyPI package has everything needed for Python development and deployment on CPU and GPUs. Visit the :doc:Install OpenVINO from PyPI <openvino_docs_install_guides_installing_openvino_pip> page for instructions on how to install OpenVINO Runtime for Python using PyPI.

.. warning::

By downloading and using this container and the included software, you agree to the terms and conditions of the software license agreements <https://software.intel.com/content/dam/develop/external/us/en/documents/intel-openvino-license-agreements.pdf>_.

@endsphinxdirective

Prerequisites

@sphinxdirective .. tab:: System Requirements

| Full requirement listing is available in: | System Requirements Page <https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/system-requirements.html>_

.. note::

  Installing OpenVINO from YUM is only supported on RHEL 8.2 and higher versions. CentOS 7 is not supported for this installation method.

.. tab:: Processor Notes

Processor graphics are not included in all processors. See Product Specifications_ for information about your processor.

.. _Product Specifications: https://ark.intel.com/

.. tab:: Software

  • CMake 3.13 or higher, 64-bit <https://cmake.org/download/>_
  • GCC 8.2.0
  • Python 3.7 - 3.10, 64-bit <https://www.python.org/downloads/>_

Install OpenVINO Runtime ########################

Step 1: Set Up the Repository +++++++++++++++++++++++++++++

  1. Create a YUM repository file (openvino-2022.repo) in the /tmp directory as a normal user:

    .. code-block:: sh

    tee > /tmp/openvino-2022.repo << EOF [OpenVINO] name=Intel(R) Distribution of OpenVINO 2022 baseurl=https://yum.repos.intel.com/openvino/2022 enabled=1 gpgcheck=1 repo_gpgcheck=1 gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB EOF

  2. Move the new openvino-2022.repo file to the YUM configuration directory, i.e. /etc/yum.repos.d:

    .. code-block:: sh

    sudo mv /tmp/openvino-2022.repo /etc/yum.repos.d

  3. Verify that the new repository is set up properly.

    .. code-block:: sh

    yum repolist | grep -i openvino

    You will see the available list of packages.

To list available OpenVINO packages, use the following command:

.. code-block:: sh

yum list 'openvino*'

Step 2: Install OpenVINO Runtime Using the YUM Package Manager ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Install OpenVINO Runtime

.. tab:: The Latest Version

Run the following command:

.. code-block:: sh

  sudo yum install openvino

.. tab:: A Specific Version

Run the following command:

.. code-block:: sh

  sudo yum install openvino-<VERSION>.<UPDATE>.<PATCH>

For example:

.. code-block:: sh

  sudo yum install openvino-2022.3.0

Check for Installed Packages and Version

Run the following command:

.. code-block:: sh

yum list installed 'openvino*'

.. _intall additional components yum:

Step 3 (Optional): Install Additional Components +++++++++++++++++++++++++++++++++++++++++++++++++

OpenVINO Development Tools is a set of utilities for working with OpenVINO and OpenVINO models. It provides tools like Model Optimizer, Benchmark Tool, Post-Training Optimization Tool, and Open Model Zoo Downloader. If you installed OpenVINO Runtime using YUM, OpenVINO Development Tools must be installed separately.

See For C++ Developers section on the :doc:Install OpenVINO Development Tools <openvino_docs_install_guides_install_dev_tools> page for instructions.

Step 4 (Optional): Configure Inference on Non-CPU Devices ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

To enable the toolkit components to use processor graphics (GPU) on your system, follow the steps in [GPU Setup Guide](@ref openvino_docs_install_guides_configurations_for_intel_gpu).

Step 5: Build Samples ++++++++++++++++++++++

To build the C++ or C sample applications for Linux, run the build_samples.sh script:

.. tab:: C++

.. code-block:: sh

  /usr/share/openvino/samples/cpp/build_samples.sh

.. tab:: C

.. code-block:: sh

  /usr/share/openvino/samples/c/build_samples.sh

For more information, refer to :doc:Build the Sample Applications on Linux <openvino_docs_OV_UG_Samples_Overview>.

Uninstalling OpenVINO Runtime ##############################

To uninstall OpenVINO Runtime via YUM, run the following command based on your needs:

.. tab:: The Latest Version

.. code-block:: sh

  sudo yum autoremove openvino

.. tab:: A Specific Version

.. code-block:: sh

  sudo yum autoremove openvino-<VERSION>.<UPDATE>.<PATCH>

For example:

.. code-block:: sh

  sudo yum autoremove openvino-2022.3.0

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 C++ Quick Start Example <openvino_docs_get_started_get_started_demos.html>_ for step-by-step instructions on building and running a basic image classification C++ application.

    .. image:: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg :width: 400

  • Visit the :ref:Samples <code samples> page for other C++ example applications to get you started with OpenVINO, such as:

    • Basic object detection with the Hello Reshape SSD C++ sample <openvino_inference_engine_samples_hello_reshape_ssd_README.html>_
    • Automatic speech recognition C++ sample <openvino_inference_engine_samples_speech_sample_README.html>_

You can also try the following things:

  • Learn more about :doc:OpenVINO Workflow <openvino_workflow>.
  • To prepare your models for working with OpenVINO, see :doc:Model Preparation <openvino_docs_model_processing_introduction>.
  • See pre-trained deep learning models in our :doc:Open Model Zoo <model_zoo>.
  • Learn more about :doc:Inference with OpenVINO Runtime <openvino_docs_OV_UG_OV_Runtime_User_Guide>.
  • See sample applications in :doc:OpenVINO toolkit Samples Overview <openvino_docs_OV_UG_Samples_Overview>.
  • Take a glance at the OpenVINO product home page: https://software.intel.com/en-us/openvino-toolkit.

@endsphinxdirective

Additional Resources