A collection of 3 lambda functions that are invoked by Amazon S3 or Amazon API Gateway to analyze uploaded images with Amazon Rekognition and save picture labels to ElasticSearch (written in Kotlin)

A working prototype for capturing frames off of a live MJPEG video stream, identifying objects in near real-time using deep learning, and triggering actions based on an objects watch list.

Apply different text recognition services to images of handwritten documents.

Serverless web app for streaming browser webcam feed to Amazon Kinesis Video Streams and Rekognition Video. See our post on the AWS Machine Learning Blog: https://aws.amazon.com/blogs/machine-learning/building-automatic-analysis-of-body-language-to-gauge-attention-and-engagement-using-amazon-kinesis-video-streams-and-amazon-ai-services

A demo to test Custom Labels with models trained by Amazon Rekognition

Open innovation with 60 minute cloud experiments on AWS

A solution to assist with virtual proctoring of exams using Amazon Rekognition

Amazon Rekognition Code Samples

The Engagement Meter calculates and shows engagement levels of an audience participating in a meeting

Vue2 + Amazon Rekognition + Amazon S3 + Progressive Web App With Face Detection

Detect Personal Protective Equipment using Amazon Rekognition

This is an application for analyzing the content of images and videos. It includes a GUI and back-end analytical workflows. It is the reference application for the Media Insights Engine.

Personal Protective Equipment detection demo showed at AWS re:Inforce 2019: source code and materials.

A script to retrieve image of automobiles from a pdf, spanning pages.

This project contains source code and supporting files for a serverless application which can be used for Computer Vision inferencing using Amazon Rekognition.

This repository provides a step-by-step setup of Amazon Rekognition’s Streaming Video Events for connected home use cases.

This repository contains sample app code to build an object and text detection web app. An individual can upload images that contains real world objects or text, and get the labels for all the detected objects and texts in the image.

This repository offers a UI component for Amazon Rekognition Face Liveness, enabling developers to ensure that only authentic users, and not bad actors using spoofs, can access their services.

This repository contains a series of 4 jupyter notebooks demonstrating how AWS AI Services like Amazon Rekognition, Amazon Transcribe and Amazon Comprehend can help you extract valuable metadata from your video assets and store that information in a Graph database like Amazon Neptune for maximum query performance and flexibility.

Application that tries recognize pokémons analyzing an photo (a.k.a pokédex). Built to AWS Cloud.