Install OpenVINO™ Runtime on Linux from an Archive File¶
Note
Note that the Archive distribution:
offers both C/C++ and Python APIs
additionally includes code samples
is dedicated to Linux users (archives for other systems are also available)
may offer different hardware support under different operating systems (see the drop-down below for more details).
Inference Options
Operating System |
CPU |
GPU |
GNA |
NPU |
---|---|---|---|---|
Debian9 armhf |
V |
n/a |
n/a |
n/a |
Debian9 arm64 |
V |
n/a |
n/a |
n/a |
CentOS7 x86_64 |
V |
V |
n/a |
n/a |
Ubuntu18 x86_64 |
V |
V |
V |
n/a |
Ubuntu20 x86_64 |
V |
V |
V |
V |
Ubuntu22 x86_64 |
V |
V |
V |
V |
RHEL8 x86_64 |
V |
V |
V |
n/a |
GCC 9.3.0
GCC 7.5.0
GCC 8.4.1
GCC 8.3.1
Use the following instructions to install it:
Install GCC 8.3.1 via devtoolset-8
sudo yum update -y && sudo yum install -y centos-release-scl epel-release
sudo yum install -y devtoolset-8
Enable devtoolset-8 and check current gcc version
source /opt/rh/devtoolset-8/enable
gcc -v
Installing OpenVINO Runtime¶
Step 1: Download and Install the OpenVINO Core Components¶
Open a command prompt terminal window. You can use the keyboard shortcut: Ctrl+Alt+T
Create the
/opt/intel
folder for OpenVINO by using the following command. If the folder already exists, skip this step.sudo mkdir /opt/intel
Note
The
/opt/intel
path is the recommended folder path for administrators or root users. If you prefer to install OpenVINO in regular userspace, the recommended path is/home/<USER>/intel
. You may use a different path if desired.Browse to the current user’s
Downloads
folder:cd <user_home>/Downloads
Download the OpenVINO Runtime archive file for your system, extract the files, rename the extracted folder and move it to the desired path:
curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2023.2/linux/l_openvino_toolkit_ubuntu22_2023.2.0.13089.cfd42bd2cb0_x86_64.tgz --output openvino_2023.2.0.tgz tar -xf openvino_2023.2.0.tgz sudo mv l_openvino_toolkit_ubuntu22_2023.2.0.13089.cfd42bd2cb0_x86_64 /opt/intel/openvino_2023.2.0
curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2023.2/linux/l_openvino_toolkit_ubuntu20_2023.2.0.13089.cfd42bd2cb0_x86_64.tgz --output openvino_2023.2.0.tgz tar -xf openvino_2023.2.0.tgz sudo mv l_openvino_toolkit_ubuntu20_2023.2.0.13089.cfd42bd2cb0_x86_64 /opt/intel/openvino_2023.2.0
curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2023.2/linux/l_openvino_toolkit_ubuntu18_2023.2.0.13089.cfd42bd2cb0_x86_64.tgz --output openvino_2023.2.0.tgz tar -xf openvino_2023.2.0.tgz sudo mv l_openvino_toolkit_ubuntu18_2023.2.0.13089.cfd42bd2cb0_x86_64 /opt/intel/openvino_2023.2.0
curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2023.2/linux/l_openvino_toolkit_rhel8_2023.2.0.13089.cfd42bd2cb0_x86_64.tgz --output openvino_2023.2.0.tgz tar -xf openvino_2023.2.0.tgz sudo mv l_openvino_toolkit_rhel8_2023.2.0.13089.cfd42bd2cb0_x86_64 /opt/intel/openvino_2023.2.0
curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2023.2/linux/l_openvino_toolkit_centos7_2023.2.0.13089.cfd42bd2cb0_x86_64.tgz --output openvino_2023.2.0.tgz tar -xf openvino_2023.2.0.tgz sudo mv l_openvino_toolkit_centos7_2023.2.0.13089.cfd42bd2cb0_x86_64 /opt/intel/openvino_2023.2.0
curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2023.2/linux/l_openvino_toolkit_debian9_2023.2.0.13089.cfd42bd2cb0_arm64.tgz -O openvino_2023.2.0.tgz tar -xf openvino_2023.2.0.tgz sudo mv l_openvino_toolkit_debian9_2023.2.0.13089.cfd42bd2cb0_arm64 /opt/intel/openvino_2023.2.0
curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2023.2/linux/l_openvino_toolkit_debian9_2023.2.0.13089.cfd42bd2cb0_armhf.tgz -O openvino_2023.2.0.tgz tar -xf openvino_2023.2.0.tgz sudo mv l_openvino_toolkit_debian9_2023.2.0.13089.cfd42bd2cb0_armhf /opt/intel/openvino_2023.2.0
Install required system dependencies on Linux. To do this, OpenVINO provides a script in the extracted installation directory. Run the following command:
cd /opt/intel/openvino_2023.2.0 sudo -E ./install_dependencies/install_openvino_dependencies.sh
(Optional) Install numpy Python Library:
Note
This step is required only when you decide to use Python API.
You can use the
requirements.txt
file from the/opt/intel/openvino_2023.2.0/python
folder:cd /opt/intel/openvino_2023.2.0 python3 -m pip install -r ./python/requirements.txt
For simplicity, it is useful to create a symbolic link as below:
cd /opt/intel sudo ln -s openvino_2023.2.0 openvino_2023
Note
If you have already installed a previous release of OpenVINO 2023, a symbolic link to the
openvino_2023
folder may already exist. Unlink the previous link withsudo unlink openvino_2023
, and then re-run the command above.
Congratulations, you have finished the installation! For some use cases you may still need to install additional components. Check the description below, as well as the list of additional configurations to see if your case needs any of them.
The /opt/intel/openvino_2023
folder now contains the core components for OpenVINO.
If you used a different path in Step 2, for example, /home/<USER>/intel/
,
OpenVINO is now in /home/<USER>/intel/openvino_2023
. The path to the openvino_2023
directory is also referred as <INSTALL_DIR>
throughout the OpenVINO documentation.
Step 2: Configure the Environment¶
You must update several environment variables before you can compile and run OpenVINO applications.
Open a terminal window and run the setupvars.sh
script as shown below to temporarily set your environment variables.
If your <INSTALL_DIR> is not /opt/intel/openvino_2023
, use the correct one instead.
source /opt/intel/openvino_2023/setupvars.sh
If you have more than one OpenVINO version installed on your system, you can easily switch versions by sourcing the setupvars.sh of your choice.
Note
The above command must be re-run every time you start a new terminal session.
To set up Linux to automatically run the command every time a new terminal is opened,
open ~/.bashrc
in your favorite editor and add source /opt/intel/openvino_2023/setupvars.sh
after the last line.
Next time when you open a terminal, you will see [setupvars.sh] OpenVINO™ environment initialized
.
Changing .bashrc
is not recommended when you have multiple OpenVINO versions on your machine and want to switch among them.
The environment variables are set.
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 Python Quick Start Example to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
![https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif](https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif)
Visit the Tutorials page for more Jupyter Notebooks to get you started with OpenVINO, such as:
Try the C++ Quick Start Example for step-by-step instructions on building and running a basic image classification C++ application.
![https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg](https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg)
Visit the Samples page for other C++ example applications to get you started with OpenVINO, such as:
Uninstalling the Intel® Distribution of OpenVINO™ Toolkit¶
If you have installed OpenVINO Runtime from archive files, you can uninstall it by deleting the archive files and the extracted folders. Uninstallation removes all Intel® Distribution of OpenVINO™ Toolkit component files but does not affect user files in the installation directory.
If you have created the symbolic link, remove the link first:
sudo rm /opt/intel/openvino_2023
To delete the files:
rm -r <extracted_folder> && rm <path_to_archive>
Additional Resources¶
Troubleshooting Guide for OpenVINO Installation & Configuration
Converting models for use with OpenVINO™: Convert a Model
Writing your own OpenVINO™ applications: OpenVINO™ Runtime User Guide
Sample applications: OpenVINO™ Toolkit Samples Overview
Pre-trained deep learning models: Overview of OpenVINO™ Toolkit Pre-Trained Models
IoT libraries and code samples in the GitHub repository: Intel® IoT Developer Kit