Our first Challenges of building AI-Powered APP
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Updated
May 25, 2024 - Vue
Our first Challenges of building AI-Powered APP
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.
A demo to test Custom Labels with models trained by Amazon Rekognition
The Engagement Meter calculates and shows engagement levels of an audience participating in a meeting
Detect Personal Protective Equipment using Amazon Rekognition
A solution to assist with virtual proctoring of exams using Amazon Rekognition
A simple Python application supporting face based user verification using Amazon Rekognition and Polly, and verbal instructions using Google API speechrecognition.
Open innovation with 60 minute cloud experiments on AWS
Application that tries recognize pokémons analyzing an photo (a.k.a pokédex). Built to AWS Cloud.
Detecting objects in an image using Amazon Rekognition and Lambda
Using Amazon Rekognition to detect Personal Protection Equipment(PPE) in photos
Using Amazon Rekognition to create a collection, add faces to the collection, deleting collections, deleting faces in collection, listing all the collections and describing collections.
Used Amazon Rekognition to identify celebrities
Comparing Faces in two pictures using Amazon Rekognition
We are using Amazon Rekognition to detect and identify text from images
AWS CloudFormation template for creating resources for a static website on an S3 bucket with an application for painting drawings according to the selected topic, where it is checked whether the drawing coincides with the topic using Amazon Rekognition image analysis.
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 contains the implementation of various AWS AI Services.
Amazon Rekognition Code Samples
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