In this recipe, we’ll show you how to build a simple face detection application that counts the number of cups of coffee that people drink and displays the tally on a leaderboard.
We will go through the following steps:
For this tutorial you will need to know how to:
Please revisit these sections if you are not familiar with the steps.
Let’s review the following architectural diagram for the project. The AWS DeepLens device enables you to run deep learning on the edge. It detects a scene and runs it against a face detection model.
When the model detects a face, it uploads a frame to Amazon S3. An AWS Lambda function then runs the frame against AWS Rekognition to detect a mug in the scene and check if a face has been detected before or if is it a new face. After a face is registered or recognized, it’s stored in Amazon DynamoDB, which is used as an incremental counter for a web application.
Following this post, you’ll be able to replicate the architecture and get the necessary information to build an application like this.