OpenVINO™ Development Tools

NOTE: This version is pre-release software and has not undergone full release validation or qualification. No support is offered on pre-release software and APIs/behavior are subject to change. It should NOT be incorporated into any production software/solution and instead should be used only for early testing and integration while awaiting a final release version of this software.

Intel® Distribution of OpenVINO™ toolkit is an open-source toolkit for optimizing and deploying AI inference. It can be used to develop applications and solutions based on deep learning tasks, such as: emulation of human vision, automatic speech recognition, natural language processing, recommendation systems, etc. It provides high-performance and rich deployment options, from edge to cloud.

OpenVINO™ Development Tools enables you to download models from Open Model Zoo, convert your own models to OpenVINO IR, as well as optimize and tune pre-trained deep learning models. See What's in the Package for more information.

System Requirements

Before you start the installation, check the supported operating systems and required Python* versions. The complete list of supported hardware is available in the Release Notes.

C++ libraries are also required for the installation on Windows*. To install that, you can download the Visual Studio Redistributable file (.exe).

NOTE: This package can be installed on other versions of macOS, Linux and Windows, but only the specific versions above are fully validated.

NOTE: The current version of the OpenVINO™ Runtime for macOS* supports inference on Intel® CPUs only.

Install the OpenVINO™ Development Tools Package

Step 1. Set Up Python Virtual Environment

Use a virtual environment to avoid dependency conflicts.

To create a virtual environment, use the following commands:

On Windows:

python -m venv openvino_env

On Linux and macOS:

python3 -m venv openvino_env

NOTE: On Linux and macOS, you may need to install pip. For example, on Ubuntu execute the following command to get pip installed: sudo apt install python3-venv python3-pip.

Step 2. Activate Virtual Environment

On Linux and macOS:

source openvino_env/bin/activate

On Windows:

openvino_env\Scripts\activate

Step 3. Set Up and Update PIP to the Highest Version

Run the command below:

python -m pip install --upgrade pip

Step 4. Install the Package

There are two options to install OpenVINO Development Tools:

Installing Default Components

To install the default components in the package (see the What's in the Package section of this article), use the following command:

pip install openvino-dev

Installing Components for Specific Frameworks

To install and configure the components of the package for working with specific frameworks, use the following command:

pip install openvino-dev[extras]

where extras has the following values:

For example, to install and configure the components for working with TensorFlow 2.x, Apache MXNet and Caffe, use the following command:

pip install openvino-dev[tensorflow2,mxnet,caffe]

NOTE: Model Optimizer support for TensorFlow 1.x environment has been deprecated. Use TensorFlow 2.x environment to convert both TensorFlow 1.x and 2.x models.

Step 5. Verify that the Package Is Installed

• To verify that the developer package is properly installed, run the command below (this may take a few seconds):

  mo -h
  

  You will see the help message for Model Optimizer if installation finished successfully.

• To verify that OpenVINO Runtime from the runtime package is available, 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).

What's in the Package?

NOTE: The openvino-dev package installs OpenVINO™ Runtime as a dependency, which is the engine that runs the deep learning model and includes a set of libraries for an easy inference integration into your applications.

In addition, the openvino-dev package installs the following components by default:

Troubleshooting

For general troubleshooting steps and issues, see Troubleshooting Guide for OpenVINO Installation. The following sections also provide explanations to several error messages.

Errors with Installing via PIP for Users in China

Users in China might encounter errors while downloading sources via PIP during OpenVINO™ installation. To resolve the issues, try the following solution:

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

  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. You can also run the following command to install openvino-dev with specific frameworks. For example:

  pip install openvino-dev[tensorflow2] -i https://mirrors.aliyun.com/pypi/simple/
  

zsh: no matches found : openvino-dev[...]

If you use zsh (Z shell) interpreter, that is the default shell for macOS starting with version 10.15 (Catalina), you may encounter the following error while installing openvino-dev package with extras:

pip install openvino-dev[tensorflow2,mxnet,caffe]
zsh: no matches found: openvino-dev[tensorflow2,mxnet,caffe]

By default zsh interprets square brackets as an expression for pattern matching. To resolve this issue, you need to escape the command with quotes:

pip install 'openvino-dev[tensorflow2,mxnet,caffe]'

To avoid such issues you can also disable globbing for PIP commands by defining an alias in ~/.zshrc file:

alias pip='noglob pip'

ERROR:root:Could not find the Inference Engine or nGraph Python API.

On Windows*, some libraries are necessary to run OpenVINO. To resolve this issue, install the C++ redistributable (.exe). You can also view a full download list on the official support page.

ImportError: libpython3.7m.so.1.0: cannot open shared object file: No such file or directory

To resolve missing external dependency on Ubuntu* 18.04, execute the following command:

sudo apt-get install libpython3.7

Additional Resources

• Intel® Distribution of OpenVINO™ toolkit
• OpenVINO™ Documentation
• OpenVINO™ Notebooks

Copyright © 2018-2022 Intel Corporation

LEGAL NOTICE: Your use of this software and any required dependent software (the “Software Package”) is subject to the terms and conditions of the Apache 2.0 License for the Software Package, which may also include notices, disclaimers, or license terms for third party or open source software included in or with the Software Package, and your use indicates your acceptance of all such terms. Please refer to the “third-party-programs.txt” or other similarly-named text file included with the Software Package for additional details.

Intel is committed to the respect of human rights and avoiding complicity in human rights abuses, a policy reflected in the Intel Global Human Rights Principles. Accordingly, by accessing the Intel material on this platform you agree that you will not use the material in a product or application that causes or contributes to a violation of an internationally recognized human right.