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

Install and Configure Intel® Distribution of OpenVINO™ Toolkit for Linux

Note

: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. These tools are now only available on pypi.org.

System Requirements

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• Ubuntu 18.04 long-term support (LTS), 64-bit
• Ubuntu 20.04 long-term support (LTS), 64-bit

.. note:: Since the OpenVINO™ 2022.1 release, CentOS 7.6, 64-bit is not longer supported.

.. tab:: Hardware

Optimized for these processors:

• 6th to 12th generation Intel® Core™ processors and Intel® Xeon® processors
• 3rd generation Intel® Xeon® Scalable processor (formerly code named Cooper Lake)
• Intel® Xeon® Scalable processor (formerly Skylake and Cascade Lake)
• Intel Atom® processor with support for Intel® Streaming SIMD Extensions 4.1 (Intel® SSE4.1)
• Intel Pentium® processor N4200/5, N3350/5, or N3450/5 with Intel® HD Graphics
• Intel® Iris® Xe MAX Graphics
• Intel® Neural Compute Stick 2
• Intel® Vision Accelerator Design with Intel® Movidius™ VPUs

.. 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/

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Overview

This guide provides step-by-step instructions on how to install the Intel® Distribution of OpenVINO™ toolkit. Links are provided for each type of compatible hardware including downloads, initialization and configuration steps. The following steps will be covered:

1. Install the Intel® Distribution of OpenVINO™ Toolkit
2. Install External Software Dependencies
3. Configure the Environment
4. Download additional components (Optional)
5. Configure Inference on non-CPU Devices (Optional)
6. What's next?

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.. important:: Before you start your journey with installation of the Intel® Distribution of OpenVINO™, we encourage you to check up our :ref:code samples <code samples> in C, C++, and Python and :ref:notebook tutorials <notebook tutorials> that we prepared for you, so you could see all amazing things that you can achieve with our tool.

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Step 1: Install the Intel® Distribution of OpenVINO™ Toolkit

1. Select and download the Intel® Distribution of OpenVINO™ toolkit installer file from Intel® Distribution of OpenVINO™ toolkit for Linux.

2. Open a command prompt terminal window. You can use the keyboard shortcut: Ctrl+Alt+T

3. Change directories to where you downloaded the Intel Distribution of OpenVINO™ toolkit for Linux file.
   If you downloaded the starter script to the current user's Downloads directory:

   cd ~/Downloads/
   

   You should find there a bootstrapper script l_openvino_toolkit_p_<version>.sh.

4. Add executable rights for the current user:

   chmod +x l_openvino_toolkit_p_<version>.sh
   

5. If you want to use graphical user interface (GUI) installation wizard, run the script without any parameters:

   ./l_openvino_toolkit_p_<version>.sh
   

   
   You should see the following dialog box open up:

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   .. image:: _static/images/openvino-install.png :width: 400px :align: center

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   Otherwise, you can add parameters -a for additional arguments and --cli to run installation in command line (CLI):

   ./l_openvino_toolkit_p_<version>.sh -a --cli
   

   Note

   : To get additional information on all parameters that can be used, check up the help option: --help. Among others, you can find there -s option which offers silent mode, which together with --eula approve allows you to run whole installation with default values without any user inference.

6. Follow the instructions on your screen. During the installation you will be asked to accept the license agreement. The acceptance is required to continue. Check out the installation process on the image below:
   

   Click on the image to see the details.
   
   By default, the Intel® Distribution of OpenVINO™ is installed to the following directory, referred to as <INSTALL_DIR> elsewhere in the documentation:

   • For root or administrator: /opt/intel/openvino_<version>/
   • For regular users: /home/<USER>/intel/openvino_<version>/

   
   For simplicity, a symbolic link to the latest installation is also created: /opt/intel/openvino_2022/ or /home/<USER>/intel/openvino_2022/.

To check Release Notes please visit: Release Notes.

The core components are now installed. Continue to the next section to install additional dependencies.

Step 2: Install External Software Dependencies

This script allows to install Linux platform development tools and components to work with the product.

1. Go to the install_dependencies directory:

   cd <INSTALL_DIR>/install_dependencies
   

2. Run a script to download and install the external software dependencies:

   sudo -E ./install_openvino_dependencies.sh
   

   Once the dependencies are installed, continue to the next section to set your environment variables.

Step 3: Configure the Environment

You must update several environment variables before you can compile and run OpenVINO™ applications. Set environment variables as follows:

source <INSTALL_DIR>/setupvars.sh

If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing setupvars.sh of your choice.

Note

: You can also run this script every time when you start new terminal session. Open ~/.bashrc in your favorite editor, and add source <INSTALL_DIR>/setupvars.sh. Next time when you open a terminal, you will see [setupvars.sh] OpenVINO™ environment initialized. Changing .bashrc is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require different setup.

The environment variables are set. Next, you can download some additional tools.

Step 4 (Optional): Download Additional Components

Note

: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See Install OpenVINO™ Development Tools for detailed steps.

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.. dropdown:: OpenCV

OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples and demos also use OpenCV as a dependency. The Intel® Distribution of OpenVINO™ provides a script to install OpenCV: <INSTALL_DIR>/extras/scripts/download_opencv.sh.

.. note:: Make sure you have 2 prerequisites installed: curl and tar.

Depending on how you have installed the Intel® Distribution of OpenVINO™, the script should be run either as root or regular user. After the execution of the script, you will find OpenCV extracted to <INSTALL_DIR>/extras/opencv.

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Step 5 (Optional): Configure Inference on Non-CPU Devices

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Only if you want to enable the toolkit components to use processor graphics (GPU) on your system, follow the steps in :ref:GPU Setup Guide <gpu guide>.

.. tab:: NCS 2

Only if you want to perform inference on Intel® Neural Compute Stick 2 powered by the Intel® Movidius™ Myriad™ X VPU, follow the steps on :ref:NCS2 Setup Guide <ncs guide>.

.. tab:: VPU

To install and configure your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, see the :ref:VPUs Configuration Guide <vpu guide>. After configuration is done, you are ready to run the verification scripts with the HDDL Plugin for your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs. Check up our :ref:Movidius VPU demos <vpu demos>.

.. warning:: While working with either HDDL or NCS, choose one of them as they cannot run simultaneously on the same machine.

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Step 6: What's Next?

Now you are ready to try out the toolkit.

Developing in Python:

• Start with TensorFlow models with OpenVINO™
• Start with ONNX and PyTorch models with OpenVINO™
• Start with PaddlePaddle models with OpenVINO™

Developing in C++:

• [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
• [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
• [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)

Uninstall the Intel® Distribution of OpenVINO™ Toolkit

To uninstall the toolkit, follow the steps on the Uninstalling page.

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.. dropdown:: Troubleshooting

PRC developers might encounter pip errors during Intel® Distribution of OpenVINO™ installation. To resolve the issues, try one of the following options:

• Add the download source using the -i parameter with the Python pip command. For example:

.. code-block:: sh

  pip install openvino-dev -i https://mirrors.aliyun.com/pypi/simple/

Use the --trusted-host parameter if the URL above is http instead of https.

• If you run into incompatibility issues between components after installing new Intel® Distribution of OpenVINO™ version, try running requirements.txt with the following command:

.. code-block:: sh

  pip install -r <INSTALL_DIR>/tools/requirements.txt

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.. dropdown:: Additional Resources

• Convert models for use with OpenVINO™: :ref:Model Optimizer Developer Guide <deep learning model optimizer>
• Write your own OpenVINO™ applications: :ref:OpenVINO™ Runtime User Guide <deep learning inference engine>
• Information on sample applications: :ref:OpenVINO™ Toolkit Samples Overview <code samples>
• Information on a supplied set of models: :ref:Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>
• IoT libraries and code samples in the GitHUB repository: Intel® IoT Developer Kit_

To learn more about converting models from specific frameworks, go to:

• :ref:Convert Your Caffe Model <convert model caffe>
• :ref:Convert Your TensorFlow Model <convert model tf>
• :ref:Convert Your MXNet Modele <convert model mxnet>
• :ref:Convert Your Kaldi Model <convert model kaldi>
• :ref:Convert Your ONNX Model <convert model onnx>

.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit

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