Amazon Rekognition allows you to detect objects and scene details from images. It provides a stateless and secure API that simply returns a list of related labels, with a certain confidence level.
In this hands-on lab, you will build a serverless system that runs object detection when images are uploaded to an Amazon S3 bucket. You will use AWS Lambda for the processing logic and you will use Amazon DynamoDB to store the results of the label detection.
Learning Objectives
Upon completion of this beginner-level lab, you will be able to:
- Create an Amazon S3 bucket
- Create an AWS Lambda function
- Configure an AWS Lambda function to trigger on an upload to Amazon S3
- Implement image label detection using Amazon Rekognition and Python
Intended Audience
- Cloud Engineers
- Data Engineers
Prerequisites
Knowledge of the following will be beneficial but is not required:
- Amazon S3
- AWS Lambda
- Amazon Rekognition
- Python
The following courses can be used to fulfill the prerequisites:
- Introduction to Amazon Rekognition
- Storage Fundamentals for AWS
- Compute Fundamentals For AWS
- Python for Beginners
Updates
July 3rd, 2023 - Updated instructions and screenshots to reflect the latest UI
March 11th, 2021 - Updated AWS Lambda lab steps to reflect latest user interface updates
January 22nd, 2021 - Updated AWS Lambda lab steps to reflect latest user interface updates
December 8th, 2020 - Updated all instructions and screenshots to address issues with the UI being outdated
February 21st, 2020 - Updated instructions to clarify the need to use the provided code and the detect labels API for the lab to function correctly
January 10th, 2019 - Added a validation Lab Step to check the work you perform in the Lab
Andrew is a Labs Developer with previous experience in the Internet Service Provider, Audio Streaming, and CryptoCurrency industries. He has also been a DevOps Engineer and enjoys working with CI/CD and Kubernetes.
He holds multiple AWS certifications including Solutions Architect Associate and Professional.