Project 1: Event Driven Image Detection

In this project, I will be implementing an Image Detection Event Driven architecture based around S3, DynamoDB, Lambda and Amazon Rekognition. Upon uploading an image of a vehicle to S3, the image will be analyzed and the vehicle license plate number will be detected and put into a DynamoDB table. In effect, we are simulating how toll roads would capture a license plate number.

Architecture

Infrastructure

• To quickly create/release the S3 Bucket and DynamoDB table I created this Cloudformation template.

• CloudFormation template, Lambda function and IAM role can be found here:

  Event Driven Image Detection

Lambda function

The Lambda Function is created with Python

• Triggered via object creation in S3

• Utilizes an IAM role with Amazon Rekognition, S3, DynamoDB and Cloudwatch Log permissions.

Lambda IAM Role

The Lambda Function will need an IAM role that allows:

• Writing logs/creating log streams to CloudWatch

• Call Amazon Rekognition Detect Text API

• Get objects from S3 bucket

• Read/write/update to DynamoDB

• Execute queries on DynamoDB

Testing Lambda Function

• The Lambda Function will invoke upon uploading the image to S3

• Armed with a test image from Google

• Upload an image to S3 to invoke the lambda function:

• After uploading is complete

  • Check the CloudWatch logs to determine if the text was found:

• Lambda Function detected the license plate text and logged it in the log stream.

Check DynamoDB Entry

• The highest entry was for the license plate number; however other results were included such as the state name and month/year of tag expiration.

  • Exclude results under 99% confidence:

Conclusion

This project was a great learning experience in CloudFormation, CloudWatch Logs, DynamoDB, Amazon Rekognition and Lambda. I thoroughly enjoyed working on this project and look to evolve this architecture in the future.

To allow users to upload to the S3 bucket, create pre-signed URLs to give users access to the S3 bucket.