apt brew yum (#15297)
This commit is contained in:
Sebastian Golebiewski
GitHub
parent
994b227b86
commit
a1fb7fe5bc
@ -2,14 +2,19 @@
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@sphinxdirective
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This guide provides detailed steps for installing OpenVINO™ Runtime through the APT repository and guidelines for installing OpenVINO Development Tools.
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With the OpenVINO™ 2022.3 release, you can install OpenVINO Runtime on Linux using the APT repository. OpenVINO™ Development Tools can be installed via PyPI only. See :ref:`Installing Additional Components <intall additional components apt>` for more information.
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.. note:: From the 2022.1 release, OpenVINO™ Development Tools can be installed via PyPI only. See :ref:`Install OpenVINO Development Tools <installing-openvino-development-tools>` for more information.
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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.
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.. 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>`_.
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Installing OpenVINO Runtime from APT 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.
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.. warning::
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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>`_.
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@endsphinxdirective
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## Prerequisites
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@sphinxdirective
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@ -33,10 +38,11 @@ This guide provides detailed steps for installing OpenVINO™ Runtime through th
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* `Python 3.7 - 3.10, 64-bit <https://www.python.org/downloads/>`_
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.. _installing-openvino-runtime:
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.. _install runtime apt:
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@endsphinxdirective
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## Installing OpenVINO Runtime
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### Step 1: Set Up the OpenVINO Toolkit APT Repository
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@ -149,43 +155,16 @@ Run the following command:
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apt list --installed | grep openvino
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.. _intall additional components apt:
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@endsphinxdirective
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#### Uninstalling OpenVINO Runtime
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@sphinxdirective
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.. tab:: The Latest Version
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Run the following command:
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.. code-block:: sh
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sudo apt autoremove openvino
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.. tab:: A Specific Version
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Run the following command:
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.. code-block:: sh
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sudo apt autoremove openvino-<VERSION>.<UPDATE>.<PATCH>
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For example:
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.. code-block:: sh
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sudo apt autoremove openvino-2022.3.0
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@endsphinxdirective
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### Step 3 (Optional): Install Additional Components
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@sphinxdirective
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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 install OpenVINO Runtime using APT, OpenVINO Development Tools must be installed separately.
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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 APT, OpenVINO Development Tools must be installed separately.
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See the **For C++ Developers** section on the :doc:`Install OpenVINO Development Tools <openvino_docs_install_guides_install_dev_tools>` page for instructions.
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@ -217,30 +196,60 @@ To build the C++ or C sample applications for Linux, run the ``build_samples.sh`
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/usr/share/openvino/samples/c/build_samples.sh
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For more information, refer to :ref:`Build the Sample Applications on Linux <build-samples-linux>`.
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@endsphinxdirective
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### Uninstalling OpenVINO Runtime
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@sphinxdirective
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To uninstall OpenVINO Runtime via APT, run the following command based on your needs:
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.. tab:: The Latest Version
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.. code-block:: sh
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sudo apt autoremove openvino
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.. tab:: A Specific Version
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.. code-block:: sh
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sudo apt autoremove openvino-<VERSION>.<UPDATE>.<PATCH>
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For example:
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.. code-block:: sh
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sudo apt autoremove openvino-2022.3.0
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@endsphinxdirective
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## What's Next?
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@sphinxdirective
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Now you may continue with the following tasks:
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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:
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* To convert models for use with OpenVINO, see :doc:`Model Optimizer Developer Guide <openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide>`.
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* 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.
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.. image:: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg
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:width: 400
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* Visit the :ref:`Samples <code samples>` page for other C++ example applications to get you started with OpenVINO, such as:
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* `Basic object detection with the Hello Reshape SSD C++ sample <openvino_inference_engine_samples_hello_reshape_ssd_README.html>`_
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* `Automatic speech recognition C++ sample <openvino_inference_engine_samples_speech_sample_README.html>`_
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You can also try the following things:
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* Learn more about :doc:`OpenVINO Workflow <openvino_workflow>`.
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* To prepare your models for working with OpenVINO, see :doc:`Model Preparation <openvino_docs_model_processing_introduction>`.
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* See pre-trained deep learning models in our :doc:`Open Model Zoo <model_zoo>`.
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* Try out OpenVINO via `OpenVINO Notebooks <https://docs.openvino.ai/nightly/notebooks/notebooks.html>`_.
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* To write your own OpenVINO™ applications, see :doc:`OpenVINO Runtime User Guide <openvino_docs_OV_UG_OV_Runtime_User_Guide>`.
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* See sample applications in :doc:`OpenVINO™ Toolkit Samples Overview <openvino_docs_OV_UG_Samples_Overview>`.
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@endsphinxdirective
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## Additional Resources
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@sphinxdirective
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- Intel® Distribution of OpenVINO™ toolkit home page: https://software.intel.com/en-us/openvino-toolkit.
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- For IoT Libraries & Code Samples see the `Intel® IoT Developer Kit <https://github.com/intel-iot-devkit>`_.
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* Learn more about :doc:`Inference with OpenVINO Runtime <openvino_docs_OV_UG_OV_Runtime_User_Guide>`.
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* See sample applications in :doc:`OpenVINO toolkit Samples Overview <openvino_docs_OV_UG_Samples_Overview>`.
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* Take a glance at the OpenVINO product home page: https://software.intel.com/en-us/openvino-toolkit.
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@endsphinxdirective
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102
docs/install_guides/installing-openvino-brew.md
Normal file
102
docs/install_guides/installing-openvino-brew.md
Normal file
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# Install OpenVINO™ Runtime via Homebrew {#openvino_docs_install_guides_installing_openvino_brew}
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@sphinxdirective
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With the OpenVINO™ 2022.3 release, you can install OpenVINO Runtime on macOS and Linux via `Homebrew <https://brew.sh/>`_. OpenVINO™ Development Tools can be installed via PyPI only. See :ref:`Installing Additional Components <intall additional components brew>` for more information.
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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.
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Installing OpenVINO Runtime from Homebrew 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.
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.. note::
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Only CPU is supported for inference if you install OpenVINO via HomeBrew.
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.. warning::
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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>`_.
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@endsphinxdirective
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## Prerequisites
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### System Requirements
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@sphinxdirective
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Full requirement listing is available on the `System Requirements Page <https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/system-requirements.html>`_
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@endsphinxdirective
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### Software Requirements
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@sphinxdirective
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.. tab:: macOS
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* `Homebrew <https://brew.sh/>`_
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* `CMake 3.13 or higher <https://cmake.org/download/>`_ (choose "macOS 10.13 or later"). Add `/Applications/CMake.app/Contents/bin` to path (for default installation).
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* `Python 3.7 - 3.10 <https://www.python.org/downloads/mac-osx/>`_ (choose 3.7 - 3.10). Install and add it to path.
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* Apple Xcode Command Line Tools. In the terminal, run `xcode-select --install` from any directory to install it.
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* (Optional) Apple Xcode IDE (not required for OpenVINO™, but useful for development)
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.. tab:: Linux
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* `Homebrew <https://brew.sh/>`_
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* `CMake 3.13 or higher, 64-bit <https://cmake.org/download/>`_
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* GCC 7.5.0 (for Ubuntu 18.04) or GCC 9.3.0 (for Ubuntu 20.04)
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* `Python 3.7 - 3.10, 64-bit <https://www.python.org/downloads/>`_
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@endsphinxdirective
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## Installing OpenVINO Runtime
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@sphinxdirective
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1. Make sure that you have installed HomeBrew on your system. If not, follow the instructions on `the Homebrew website <https://brew.sh/>`_ to install and configure it.
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2. Open a command prompt terminal window, and run the following command to install OpenVINO Runtime:
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.. code-block:: sh
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brew install openvino
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Congratulations, you've finished the installation!
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.. _intall additional components brew:
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@endsphinxdirective
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## (Optional) Installing Additional Components
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@sphinxdirective
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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 Homebrew, OpenVINO Development Tools must be installed separately.
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See **For C++ Developers** section on the :doc:`Install OpenVINO Development Tools <openvino_docs_install_guides_install_dev_tools>` page for instructions.
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OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the `instructions on GitHub <https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO>`_.
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@endsphinxdirective
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## Uninstalling OpenVINO
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To uninstall OpenVINO via HomeBrew, use the following command:
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```sh
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brew uninstall openvino
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```
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## What's Next?
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@sphinxdirective
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Now that you've installed OpenVINO Runtime, you can try the following things:
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* Learn more about :doc:`OpenVINO Workflow <openvino_workflow>`.
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* To prepare your models for working with OpenVINO, see :doc:`Model Preparation <openvino_docs_model_processing_introduction>`.
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* See pre-trained deep learning models in our :doc:`Open Model Zoo <model_zoo>`.
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* Learn more about :doc:`Inference with OpenVINO Runtime <openvino_docs_OV_UG_OV_Runtime_User_Guide>`.
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* See sample applications in :doc:`OpenVINO toolkit Samples Overview <openvino_docs_OV_UG_Samples_Overview>`.
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* Take a glance at the OpenVINO product home page: https://software.intel.com/en-us/openvino-toolkit.
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@endsphinxdirective
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@ -10,6 +10,7 @@
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From PyPI <openvino_docs_install_guides_installing_openvino_pip>
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From APT <openvino_docs_install_guides_installing_openvino_apt>
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From YUM <openvino_docs_install_guides_installing_openvino_yum>
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Using HomeBrew <openvino_docs_install_guides_installing_openvino_brew>
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Using Docker <openvino_docs_install_guides_installing_openvino_docker_linux>
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@endsphinxdirective
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@ -6,6 +6,7 @@ Currently the following ways are provided to install OpenVINO™:
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* [Install OpenVINO Runtime from APT](@ref openvino_docs_install_guides_installing_openvino_apt)
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* [Install OpenVINO Runtime from YUM](@ref openvino_docs_install_guides_installing_openvino_yum)
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* [Install OpenVINO from PyPI](installing-openvino-pip.md)
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* [Install OpenVINO Runtime via HomeBrew](installing-openvino-brew.md)
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* [Install OpenVINO with Docker](installing-openvino-docker-linux.md)
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* [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)
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@ -8,10 +8,12 @@
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From Archive <openvino_docs_install_guides_installing_openvino_from_archive_macos>
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From PyPI <openvino_docs_install_guides_installing_openvino_pip>
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Using HomeBrew <openvino_docs_install_guides_installing_openvino_brew>
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@endsphinxdirective
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If you want to install OpenVINO™ Runtime on macOS, there are a few ways to accomplish this. We prepared following options for you:
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* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-macos.md)
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* [Install OpenVINO Runtime via HomeBrew](installing-openvino-brew.md)
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* [Install OpenVINO from PyPI](installing-openvino-pip.md)
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@ -3,6 +3,7 @@
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Currently only the following ways are provided to install OpenVINO™:
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* [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-macos.md)
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* [Install OpenVINO Runtime via HomeBrew](installing-openvino-brew.md)
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* [Install OpenVINO from PyPI](installing-openvino-pip.md)
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* [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)
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@ -1,10 +1,18 @@
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# Install OpenVINO™ Runtime on Linux Using YUM Repository {#openvino_docs_install_guides_installing_openvino_yum}
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This guide provides installation steps for OpenVINO™ Runtime for Linux distributed through the YUM repository.
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@sphinxdirective
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> **NOTE**: From the 2022.1 release, the OpenVINO™ Development Tools can only be installed via PyPI. If you want to develop or optimize your models with OpenVINO, see [Install OpenVINO Development Tools](installing-model-dev-tools.md) for detailed steps.
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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 :ref:`Installing Additional Components <intall additional components yum>` for more information.
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> **IMPORTANT**: 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).
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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.
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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.
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.. warning::
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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>`_.
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@endsphinxdirective
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## Prerequisites
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@ -96,7 +104,6 @@ To list available OpenVINO packages, use the following command:
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@endsphinxdirective
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#### Check for Installed Packages and Version
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Run the following command:
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@ -107,43 +114,20 @@ Run the following command:
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yum list installed 'openvino*'
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@endsphinxdirective
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#### Uninstalling OpenVINO Runtime
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@sphinxdirective
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.. tab:: The Latest Version
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Run the following command:
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.. code-block:: sh
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sudo yum autoremove openvino
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.. tab:: A Specific Version
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Run the following command:
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.. code-block:: sh
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sudo yum autoremove openvino-<VERSION>.<UPDATE>.<PATCH>
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For example:
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.. code-block:: sh
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sudo yum autoremove openvino-2022.3.0
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.. _intall additional components yum:
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@endsphinxdirective
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### Step 3 (Optional): Install Additional Components
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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 install OpenVINO Runtime using YUM, OpenVINO Development Tools must be installed separately.
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See the **For C++ Developers** section on the [Install OpenVINO Development Tools](installing-model-dev-tools.md) page for instructions.
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@sphinxdirective
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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.
|
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See **For C++ Developers** section on the :doc:`Install OpenVINO Development Tools <openvino_docs_install_guides_install_dev_tools>` page for instructions.
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@endsphinxdirective
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### Step 4 (Optional): Configure Inference on Non-CPU Devices
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@ -171,17 +155,56 @@ To build the C++ or C sample applications for Linux, run the `build_samples.sh`
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For more information, refer to <a href="openvino_docs_OV_UG_Samples_Overview.html#build-samples-linux">Build the Sample Applications on Linux</a>.
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### Uninstalling OpenVINO Runtime
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@sphinxdirective
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||||
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To uninstall OpenVINO Runtime via YUM, run the following command based on your needs:
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.. tab:: The Latest Version
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.. code-block:: sh
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sudo yum autoremove openvino
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.. tab:: A Specific Version
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.. code-block:: sh
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||||
|
||||
sudo yum autoremove openvino-<VERSION>.<UPDATE>.<PATCH>
|
||||
|
||||
For example:
|
||||
|
||||
.. code-block:: sh
|
||||
|
||||
sudo yum autoremove openvino-2022.3.0
|
||||
|
||||
@endsphinxdirective
|
||||
|
||||
## What's Next?
|
||||
|
||||
Now you may continue with the following tasks:
|
||||
@sphinxdirective
|
||||
|
||||
* To convert models for use with OpenVINO, see [Model Optimizer Developer Guide](../MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md).
|
||||
* See pre-trained deep learning models in our [Open Model Zoo](../model_zoo.md).
|
||||
* Try out OpenVINO via [OpenVINO Notebooks](https://docs.openvino.ai/nightly/notebooks/notebooks.html).
|
||||
* To write your own OpenVINO™ applications, see [OpenVINO Runtime User Guide](../OV_Runtime_UG/openvino_intro.md).
|
||||
* See sample applications in [OpenVINO™ Samples Overview](../OV_Runtime_UG/Samples_Overview.md).
|
||||
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:
|
||||
|
||||
## Additional Resources
|
||||
* 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.
|
||||
|
||||
- OpenVINO™ home page: <https://software.intel.com/en-us/openvino-toolkit>
|
||||
- For IoT Libraries & Code Samples, see [Intel® IoT Developer Kit](https://github.com/intel-iot-devkit).
|
||||
.. 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
|
||||
|
||||
Loading…
Reference in New Issue
Block a user