We built an Elastic application using AWS that can automatically scale out and in on demand and cost-effectively by using AWS Lambda functions.
This app takes videos from the user(uploaded to S3), a Lambda function is invoked for every upload which extracts the first frame from the video and performs face recognition, looks up the recognized face in the database(DynamoDB), and returns the relevant information back to the user as CSV file in S3 bucket.
- Dockerfile - This file contains the code to create docker image.
- handler.py - This file contains the lambda handler and logic for our application.
- encoding - This file contains encodings of all the students.
- entry.sh - The entry point for the Dockerfile
- workload.py - This file uploads the test videos to input S3 bucket.
- Shikhar Gupta - Worked on configuring S3, Lambda, ECR and testing scripts.
- Ayushi Agarwal - Worked on the script in splitting the video into frames and identifying the face.
- Maitry Trivedi - Worked on configuring the DynamoDB and the script to upload and fetch records from DynamoDB.