Skip to content

This Repository creates a serverless stack with AWS SQS, Lambda and Dynamo DB to leverage the AWS Rekognition service at high scale on a large image database. Finding people, text or classify images can now be done within seconds on thousands of images.

Notifications You must be signed in to change notification settings

daMichaelB/aws-rekognition-serverless

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

AWS Rekognition Serverless

This lambda function will use Rekognition to detect a specific person on thousands of images.

Due to the serverless approach thousands of images can be processed at the same time.

We will create a lambda function / SQS Queue / DynamoDB and IAM Roles.

Prerequisites

  • AWS Account
  • A S3 bucket containing all your images
  • A S3 bucket (can be the same) that contains an image of the target person.

Deploy function:

First deploy the Serverless stack into your AWS account:

export INPUT_BUCKET='your-bucket-name'
serverless deploy -v

Trigger Lambda

Put this item into the SQS queue to trigger the lambda function:

{"img_url": "images/image1.jpg", "target_img_url": "target.jpg"}

You can already use the fill_queue.py script to automatically add all images from a .txt file into that queue.

The results will directly be stored into a Dynamo-DB.

Remove stack

serverless remove

About

This Repository creates a serverless stack with AWS SQS, Lambda and Dynamo DB to leverage the AWS Rekognition service at high scale on a large image database. Finding people, text or classify images can now be done within seconds on thousands of images.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages