Working With Amazon Rekognition for Video and Image Analysis

Posted Sep 7, 2024 Updated Nov 5, 2024

By Deniz Yilmaz 1 min read

This lesson looks at Amazon Rekognition, a service that uses generative AI to analyze images and videos enabling developers to add advanced visual analysis capabilities to their applications.

Learning Objectives

Understand Amazon Rekognition and its capabilities
Identify key features and use cases of Rekognition
Work with Rekognition APIs
Use Rekognition through the AWS Management Console, CLI, and SDKs
Implement best practices for Rekognition in your applications
Build a practical, serverless image analysis solution with Rekognition

Demo

Learn how to build a serverless solution for image analysis and sentiment detection using Amazon S3, AWS Lambda, Amazon Rekognition, Amazon Comprehend, Amazon DynamoDB, and Amazon SNS. The solution performs object detection, text extraction, and sentiment analysis on uploaded images.

GitHub

The Python scripts for the demo are available in the GitHub Repository

Intended Audience

This lesson is designed for software developers, data scientists, and IT professionals looking to implement advanced image and video analysis capabilities in their applications using Amazon Rekognition.

Prerequisites

To get the most out of this lesson, you should already have some basic working knowledge of building cloud solutions on the AWS platform. Familiarity with Python programming and AWS services like Lambda, S3, and DynamoDB will be beneficial.

Get Started

Working With Amazon Rekognition for Video and Image Analysis

AWS, Machine Learning

This post is licensed under CC BY 4.0 by the author.