The Image Recognition and Processing Backend demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition. This workflow processes photos uploaded to Amazon S3 and extracts metadata from the image such as geolocation, size/format, time, etc. It then uses image recognition to tag objects in the photo. In parallel, it also produces a thumbnail of the photo.

This repository contains .NET5 sample code for all the Lambda functions depicted in the diagram below as well as an AWS CloudFormation template through AWS CDK for creating the functions and related resources. There is also a test web app (coming soon!!) that you can run to interact with the backend.

1. An image is uploaded to the PhotoRepo S3 bucket under the private/{userid}/uploads prefix
2. The S3 upload event triggers the S3Trigger Lambda function, which kicks off an execution of the ImageProcStateMachine in AWS Step Functions, passing in the S3 bucket and object key as input parameters.
3. The ImageProcStateMachine has the following sub-steps:

• Read the file from S3 and extract image metadata (format, EXIF data, size, etc.)
• Based on output from previous step, validate if the file uploaded is a supported file format (png or jpg). If not, throw NotSupportedImageType error and end execution.
• Store the extracted metadata in the ImageMetadata DynamoDB table
• In parallel, kick off two processes simultaneously:
  • Call Amazon Rekognition to detect objects in the image file. If detected, store the tags in the ImageMetadata DynamoDB table
  • Generate a thumbnail and store it under the private/{userid}/resized prefix in the PhotoRepo S3 bucket