Install OpenVINO™ Runtime on Windows from an Archive File¶
Note that the Archive distribution:
offers both C/C++ and Python APIs
additionally includes code samples
is dedicated to Windows users (archives for other systems are also available)
CMake 3.14 or higher, 64-bit (optional, only required for building sample applications)
To install Microsoft Visual Studio 2019, follow the Microsoft Visual Studio installation guide. You can choose to download the Community version. During installation in the Workloads tab, choose Desktop development with C++.
You can either use cmake<version>.msi which is the installation wizard or cmake<version>.zip where you have to go into the bin folder and then manually add the path to environmental variables.
When installing Python, make sure you click the option Add Python 3.x to PATH to add Python to your PATH environment variable.
Installing OpenVINO Runtime¶
Step 1: Download and Install OpenVINO Core Components¶
Intelfolder in the
C:\Program Files (x86)\directory. Skip this step if the folder already exists.
You can also do this via command-lines. Open a new command prompt window as administrator by right-clicking Command Prompt from the Start menu and select Run as administrator, and then run the following command:
mkdir "C:\Program Files (x86)\Intel"
C:\Program Files (x86)\Intelis the recommended folder. You may also use a different path if desired or if you don’t have administrator privileges on your computer.
Download the OpenVINO Runtime archive file for Windows to your local
If you prefer using command-lines, run the following commands in the command prompt window you opened:
cd <user_home>/Downloads curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2023.2/windows/w_openvino_toolkit_windows_2023.2.0.13089.cfd42bd2cb0_x86_64.zip --output openvino_2023.2.0.zip
.sha256file is provided together with the archive file to validate your download process. To do that, download the
.sha256file from the same repository and run
CertUtil -hashfile openvino_2023.2.0.zip SHA256. Compare the returned value in the output with what’s in the
.sha256file: if the values are the same, you have downloaded the correct file successfully; if not, create a Support ticket here.
Use your favorite tool to extract the archive file, rename the extracted folder, and move it to the
C:\Program Files (x86)\Inteldirectory.
To do this step using command-line, run the following commands in the command prompt window you opened:
tar -xf openvino_2023.2.0.zip ren w_openvino_toolkit_windows_2023.2.0.13089.cfd42bd2cb0_x86_64 openvino_2023.2.0 move openvino_2023.2.0 "C:\Program Files (x86)\Intel"
(Optional) Install numpy Python Library:
This step is required only when you decide to use Python API.
You can use the
requirements.txtfile from the
C:\Program Files (x86)\Intel\openvino_2023.2.0\pythonfolder:
cd "C:\Program Files (x86)\Intel\openvino_2023.2.0" python -m pip install -r .\python\requirements.txt
For simplicity, it is useful to create a symbolic link. Open a command prompt window as administrator (see Step 1 for how to do this) and run the following commands:
cd C:\Program Files (x86)\Intel mklink /D openvino_2023 openvino_2023.2.0
If you have already installed a previous release of OpenVINO 2022, a symbolic link to the
openvino_2023folder may already exist. If you want to override it, navigate to the
C:\Program Files (x86)\Intelfolder and delete the existing linked folder before running the
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.
C:\Program Files (x86)\Intel\openvino_2023 folder now contains the core components for OpenVINO.
If you used a different path in Step 1, you will find the
openvino_2023 folder there.
The path to the
openvino_2023 directory is also referred as
throughout the OpenVINO documentation.
Step 2: Configure the Environment¶
You must update several environment variables before you can compile and run OpenVINO™ applications. Open the Command Prompt, and run the
setupvars.bat batch file to temporarily set your environment variables. If your
<INSTALL_DIR> is not
C:\Program Files (x86)\Intel\openvino_2023, use the correct directory instead.
"C:\Program Files (x86)\Intel\openvino_2023\setupvars.bat"
The above command must be re-run every time a new Command Prompt window is opened.
If you see an error indicating Python is not installed, Python may not be added to the PATH environment variable (as described here). Check your system environment variables, and add Python if necessary.
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.
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.
Visit the Samples page for other C++ example applications to get you started with OpenVINO, such as:
Uninstalling OpenVINO Runtime¶
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.
Use either of the following methods to delete the files:
Use Windows Explorer to remove the files.
Open a Command Prompt and run:
rmdir /s <extracted_folder> del <path_to_archive>
Converting models for use with OpenVINO™: Model Optimizer Developer Guide
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