Install and Configure Intel® Distribution of OpenVINO™ toolkit for Windows* 10¶
By default, the OpenVINO™ Toolkit installation on this page installs the following components:
This tool imports, converts, and optimizes models that were trained in popular frameworks to a format usable by Intel tools, especially the Inference Engine. Popular frameworks include Caffe*, TensorFlow*, MXNet*, and ONNX*.
This is the engine that runs the deep learning model. It includes a set of libraries for an easy inference integration into your applications.
OpenCV* community version compiled for Intel® hardware
A set of simple command-line applications demonstrating how to utilize specific OpenVINO capabilities in an application and how to perform specific tasks, such as loading a model, running inference, querying specific device capabilities, and more.
A set of command-line applications that serve as robust templates to help you implement multi-stage pipelines and specific deep learning scenarios.
Documentation for the pre-trained models available in the Open Model Zoo repo .
Optimized for these processors:
6th to 11th 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
Since the OpenVINO™ 2020.4 release, Intel® Movidius™ Neural Compute Stick is not supported.
Processor graphics are not included in all processors. See Product Specifications for information about your processor.
Microsoft Windows* 10, 64-bit
As part of this installation, make sure you click the option Add Python 3.x to PATH to add Python to your
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:
After installing your Intel® Movidius™ VPU, you will return to this guide to complete OpenVINO™ installation.
Step 1: Install External Software Dependencies¶
Install these dependencies:
Microsoft Visual Studio* 2019 with MSBuild> NOTE : You can choose to download Community version. Use Microsoft Visual Studio installation guide to walk you through the installation. During installation in the Workloads tab, choose Desktop development with C++.
CMake 3.14 or higher 64-bit> NOTE : You can either use
cmake<version>.msiwhich is the installation wizard or
cmake<version>.zipwhere you have to go into the
binfolder and then manually add the path to environmental variables.
Step 2: Install the Intel® Distribution of OpenVINO™ toolkit Core Components¶
Download the Intel® Distribution of OpenVINO™ toolkit package file from Intel® Distribution of OpenVINO™ toolkit for Windows*. Select the Intel® Distribution of OpenVINO™ toolkit for Windows* package from the dropdown menu.
Go to the
Downloadsfolder and double-click
w_openvino_toolkit_p_<version>.exe. A window opens to let you choose your installation directory and components.
Follow the instructions on your screen. Watch for informational messages such as the following in case you must complete additional steps:
By default, the Intel® Distribution of OpenVINO™ is installed to the following directory, referred to as
<INSTALL_DIR>elsewhere in the documentation:
C:\Program Files (x86)\Intel\openvino_<version>
For simplicity, a shortcut to the latest installation is also created:
C:\Program Files (x86)\Intel\openvino_2021.
Optional : You can choose Customize to change the installation directory or the components you want to install.
If there is an OpenVINO™ toolkit version previously installed on your system, the installer will use the same destination directory for next installations. If you want to install a newer version to a different directory, you need to uninstall the previously installed versions.
The Finish screen indicates that the core components have been installed:
Click Finish to close the installation wizard.
Once you click Finish to close the installation wizard, a new browser window opens with the document you’re reading now (in case you installed without it) and jumps to the section with the next installation steps.
The core components are now installed. Continue to the next section to install additional dependencies.
Step 3: Configure the Environment¶
If you installed the Intel® Distribution of OpenVINO™ to a non-default install directory, replace
C:\Program Files (x86)\Intel with that directory in this guide’s instructions.
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:
"C:\Program Files (x86)\Intel\openvino_2021\bin\setupvars.bat"
Windows PowerShell* is not recommended to run the configuration commands. Please use the command prompt (cmd) instead.
**(Optional)**: OpenVINO toolkit environment variables are removed when you close the command prompt window. As an option, you can permanently set the environment variables manually.
If you see an error indicating Python is not installed when you know you installed it, your computer might not be able to find the program. For the instructions to add Python to your system environment variables, see Update Your Windows Environment Variables.
The environment variables are set. Next, you will configure the Model Optimizer.
Step 4: Configure the Model Optimizer¶
The Model Optimizer is a Python*-based command line tool for importing trained models from popular deep learning frameworks such as Caffe*, TensorFlow*, Apache MXNet*, ONNX* and Kaldi*.
The Model Optimizer is a key component of the Intel Distribution of OpenVINO toolkit. Performing inference on a model (with the exception of ONNX and nGraph models) requires running the model through the Model Optimizer. When you convert a pre-trained model through the Model Optimizer, your output is an Intermediate Representation (IR) of the network. The Intermediate Representation is a pair of files that describe the whole model:
.xml: Describes the network topology
.bin: Contains the weights and biases binary data
For more information about the Model Optimizer, refer to the Model Optimizer Developer Guide.
If you see error messages, make sure you installed all dependencies. These steps use a command prompt to make sure you see error messages.
Open a command prompt by typing
cmdin your Search Windows box and then pressing Enter. Type commands in the opened window:
Go to the Model Optimizer prerequisites directory.
cd C:\Program Files (x86)\Intel\openvino_2021\deployment_tools\model_optimizer\install_prerequisites
Run this batch file to configure the Model Optimizer for Caffe, TensorFlow 2.x, MXNet, Kaldi*, and ONNX:
Optional: You can choose to configure each framework separately instead. If you see error messages, make sure you installed all dependencies.
From the Model Optimizer prerequisites directory, run the scripts for the model frameworks you want support for. You can run more than one script.
You can choose to install Model Optimizer support for only certain frameworks. In the same directory are individual scripts for Caffe, TensorFlow 1.x, TensorFlow 2.x, MXNet, Kaldi*, and ONNX (install_prerequisites_caffe.bat, etc.).
The Model Optimizer is configured for one or more frameworks.
You have now completed all required installation, configuration and build steps in this guide to use your CPU to work with your trained models.
If you want to use a GPU or VPU, or update your Windows* environment variables, read through the Optional Steps section:
Or proceed to the Start Using the Toolkit section to learn the basic OpenVINO™ toolkit workflow and run code samples and demo applications.
Step 5 (Optional): Configure Inference on non-CPU Devices:¶
Optional: Steps for Intel® Processor Graphics (GPU)¶
These steps are required only if you want to use an Intel® integrated GPU. NOTE : This section will help you check if you require driver installation. Install indicated version or higher.
If your applications offload computation to Intel® Integrated Graphics, you must have the Intel Graphics Driver for Windows installed on your hardware. Download and install the recommended version.
To check if you have this driver installed:
Type device manager in your Search Windows box and press Enter. The Device Manager opens.
Click the drop-down arrow to view the Display adapters. You can see the adapter that is installed in your computer:
Right-click the adapter name and select Properties.
Click the Driver tab to see the driver version.
You are done updating your device driver and are ready to use your GPU. Proceed to the Start Using the Toolkit section to learn the basic OpenVINO™ toolkit workflow and run code samples and demo applications.
Optional: Steps for Intel® Vision Accelerator Design with Intel® Movidius™ VPUs¶
These steps are required only if you want to use Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
To enable inference on Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, the following additional installation steps are required:
Download and install Visual C++ Redistributable for Visual Studio 2017
Check with a support engineer if your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs card requires SMBUS connection to PCIe slot (most unlikely). Install the SMBUS driver only if confirmed (by default, it’s not required):
Go to the
<INSTALL_DIR>is the directory in which the Intel Distribution of OpenVINO toolkit is installed.
Right click on the
hddlsmbus.inffile and choose Install from the pop up menu.
You are done installing your device driver and are ready to use your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
For advanced configuration steps for your IEI Mustang-V100-MX8 accelerator, see Intel® Movidius™ VPUs Setup Guide for Use with Intel® Distribution of OpenVINO™ toolkit.
After you’ve configurated your Intel® Vision Accelerator Design with Intel® Movidius™ VPUs, see Intel® Movidius™ VPUs Programming Guide for Use with Intel® Distribution of OpenVINO™ toolkit to learn how to distribute a model across all 8 VPUs to maximize performance.
After configuration is done, you are ready to go to Start Using the Toolkit section to learn the basic OpenVINO™ toolkit workflow and run code samples and demo applications.
Optional: Update Your Windows Environment Variables¶
These steps are only required under special circumstances, such as if you forgot to check the box during the CMake* or Python* installation to add the application to your Windows
PATH environment variable.
Use these steps to update your Windows
PATH if a command you execute returns an error message stating that an application cannot be found.
In your Search Windows box, type Edit the system environment variables and press Enter. A window like the following appears:
At the bottom of the screen, click Environment Variables.
Under System variables, click Path and then Edit :
In the opened window, click Browse. A browse window opens:
If you need to add CMake to the
PATH, browse to the directory in which you installed CMake. The default directory is
If you need to add Python to the
PATH, browse to the directory in which you installed Python. The default directory is
C:\Users\<USER_ID>\AppData\Local\Programs\Python\Python36\Python. Note that the
AppDatafolder is hidden by default. To view hidden files and folders, see these Windows 10 instructions.
Click OK repeatedly to close each screen.
PATH environment variable is updated. If the changes don’t take effect immediately, you may need to reboot.
Step 6: Start Using the Toolkit¶
Now you are ready to try out the toolkit. To continue, see the Get Started Guide section to learn the basic OpenVINO™ toolkit workflow and run code samples and demo applications with pre-trained models on different inference devices.
Uninstall the Intel® Distribution of OpenVINO™ Toolkit¶
To uninstall the toolkit, follow the steps on the Uninstalling page.
Get started with samples and demos: Get Started Guide
Intel® Distribution of OpenVINO™ toolkit home page: https://software.intel.com/en-us/openvino-toolkit
OpenVINO™ toolkit online documentation: https://docs.openvinotoolkit.org
Convert models for use with OpenVINO™: Model Optimizer Developer Guide
Write your own OpenVINO™ applications: Inference Engine Developer Guide
Information on sample applications: Inference Engine Samples Overview
Information on a supplied set of models: Overview of OpenVINO™ Toolkit Pre-Trained Models
IoT libraries and code samples: Intel® IoT Developer Kit
To learn more about converting models from specific frameworks, go to: