OpenVINO™ Deep Learning Workbench

Table of Contents

• Introduction
• System Requirements
• Install DL Workbench
  • Using Python wrapper
  • Using plain Docker command
• Useful Links

Copyright © 2018-2023 Intel Corporation

Introduction

Deep Learning Workbench is an official OpenVINO™ graphical user interface designed to make the production of pre-trained deep learning models significantly easier.

The DL Workbench is an official UI environment of the OpenVINO™ toolkit that enables you to:

• Learn what neural networks are, how they work, and how to analyze their architectures and performance.
• Get familiar with the OpenVINO™ ecosystem and its main components without installing it on your system.
• Measure and interpret model performance.
• Analyze the quality of your model and visualize output.
• Optimize your model and prepare it for deployment on the target system.

In the DL Workbench, you can use the following OpenVINO™ toolkit components:

System Requirements

The complete list of recommended requirements is available in the documentation.

To successfully run the DL Workbench with Python Starter, install Python 3.6 or higher.

Windows*, Linux* and MacOS* support CPU targets. GPU, Intel® Neural Compute Stick 2 and Intel® Vision Accelerator Design with Intel® Movidius™ VPUs are supported only for Linux*.

Install DL Workbench

Install the DL Workbench Starter

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.

This section describes how to start the DL Workbench using the Python wrapper, which works on Linux OS*, macOS* and Windows*.

For additional details, such as prerequisites, security, and troubleshooting, see OpenVINO DL Workbench documentation.

Step 1. Set Up Python Virtual Environment

To avoid dependency conflicts, use a virtual environment. Skip this step only if you do want to install all dependencies globally.

Create virtual environment by executing the following commands in your terminal:

• On Linux and MacOS:

python3 -m pip install --user virtualenv
python3 -m venv venv

• On Windows:

py -m pip install --user virtualenv
py -m venv venv

Step 2. Activate Virtual Environment

• On Linux and MacOS:

source venv/bin/activate

• On Windows:

venv\Scripts\activate

Step 3. Update PIP to the Latest Version

Run the command below:

python -m pip install --upgrade pip

Step 4. Install the Python Wrapper

pip install -U openvino-workbench

Step 5. Verify the Installation

To verify that the package is properly installed, run the command below:

openvino-workbench --help

You will see the help message for the starting package if installation finished successfully.

Use the DL Workbench Starter

To start the latest available version of the DL Workbench, execute the following command:

openvino-workbench --image openvino/workbench:2021.3

You can see the list of available arguments with the following command:

openvino-workbench --help

Refer to the documentation for additional information.

Use web-form to build a starting command

This section describes how to start the DL Workbench using the plain Docker* command, which works on Linux OS*, macOS* and Windows*.

For additional details, such as prerequisites, security, and troubleshooting, see OpenVINO DL Workbench documentation.

Step 1. Navigate to the web-form website

• Web-form is available here: https://openvinotoolkit.github.io/workbench_aux/

Step 2. Select the necessary capabilities

• Go through the web-form interface and select the most suitable capabilities for you.

Step 3. Start DL Workbench

• Copy the resulting command and execute it in your terminal.

Additional Resources

• Release Notes
• Documentation
• Feedback
• Troubleshooting