OpenVINO Beginner: Building a Crossroad AI Camera

학습자는 이 안내 프로젝트에서 다음을 수행하게 됩니다.

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
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

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.

개발할 기술

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

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  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

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

자주 묻는 질문

자주 묻는 질문

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