OpenVINO Beginner: Building a Crossroad AI Camera

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In this Guided Project, you will:

You will be able to, explain the OpenVINO Toolkit Components and perform Model Conversion, Preparation and Optimization

You will be able to, utilize the Inference Engine to accelerate image and video analytics processing workloads

Clock2 Hours
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 2-hour long project-based course, you will learn how to Build a Crossroad AI Camera: Learning Objective 1: By the end of Task 1, you will be able to explain the OpenVINO™ Toolkit Workflow and OpenVINO™ Toolkit Components Learning Objective 2: By the end of Task 2, you will be able to operationalize models using the Model Downloader utility Learning Objective 3: By the end of Task 3, you will be able to perform Model Preparation, Conversion and Optimization Learning Objective 4: By the end of Task 4, you will be able to Running and Tuning Inference Learning Objective 5: By the end of Task 5, you will be able to create visualization of Person Attributes and Person Re-identification (REID) information for each detected person in an Image/Video/Camera input.

Skills you will develop

  • Deep Learning Inference
  • Image Processing
  • model optimization
  • Internet Of Things (IOT)
  • Computer Vision

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introduction to Intel Distribution of the OpenVINO Toolkit and it's main components

  2. Download Pre-trained Deep Learning Models using Model Downloader utility

  3. Perform Model Conversion and Preparation using Model Optimizer

  4. Utilize the Inference Engine to run and tune Optimized Models

  5. Visualize Inference Results for a Crossroad AI Camera

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.