rekognition
There are 237 repositories under rekognition topic.
jakowenko/double-take
Unified UI and API for processing and training images for facial recognition.
seydx/homebridge-camera-ui
Homebridge plugin for RTSP Cameras with HSV, motion detection support, Image Rekognition, Web UI to manage/watch streams and WebApp support
seydx/camera.ui
NVR like user Interface for RTSP capable cameras
goruck/smart-zoneminder
Fast object detection, face recognition and S3 upload of ZoneMinder alarms.
aws-samples/liveness-detection
Backend and a JavaScript frontend of a liveness detection application.
robmarkcole/HASS-amazon-rekognition
Home Assistant Object detection with Amazon Rekognition
dabit3/real-time-image-tracking
Real-time image tracking with React, GraphQL, and AWS AppSync
rizwansoaib/face-attendence
Face Attendance (AWS rekognition)
tangowhisky37/LetsHack
Notes & HowTo's covering the Raspberry Pi, Arduino, ESP8266, ESP32, etc.
28mm/Fovea
unified cli for various saas image classification apis.
aws-samples/amazon-rekognition-id-verification-sample-with-amplify
This sample, built using AWS Amplify, is meant to showcase recommended flows when using Amazon Rekognition for Identity Verification.
adhorn/poliko
Demo web applications that use AWS Artificial Intelligence services Rekognition and Polly (http://poliko.adhorn.me)
aws-samples/automating-livestream-video-monitoring
This repo presents a demo application for realtime livestream video quality monitoring using AWS serverless and AI/ML services.
aws-samples/rekognition-identity-verification
Example implementation of the Identity Verification using Amazon Rekognition whitepaper.
geerlingguy/drupal-photo-gallery
An intelligent photo gallery built with Drupal 8.
dabit3/amplify-ml-ai-predictions-example
This is a general overview of the Predictions category of Amplify. It shows examples of Machine Learning and AI service integration in a React app with AWS Amplify Predictions category
jpcaparas/laravel-aws-demo
A demo illustrating Laravel's integration with the AWS suite (e.g. S3, Rekognition, Elastic Transcoder)
meemalabs/laravel-media-recognition
๐ A wrapper to easily & quickly integrate popular image & video recognition libraries. Currently supports AWS Rekognition.
mbudm/fotopia-serverless
An API, storage and face detection for a photo archive web app using serverless framework
oleurud/node-rekognition
AWS Rekognition library
larareko/aws-rekognition
A Laravel Package/Facade for the AWS Rekognition API
aws-samples/amazon-rekognition-custom-labels-batch-processing
This project contains source code and supporting files for a serverless application which can be used for Computer Vision inferencing using Amazon Rekognition.
wayncheng/mypass
Biometric user authentication system using face recognition and voice recognition.
okandavut/aws-webrtc-recognition-example
Example with WebRTC , AWS Rekognition :+1:
pimlock/whats-your-name
Sample app for AWS Serverless Repository - uses Amazon Rekognition to recognize person on the photo
aws-samples/smart-shopping-list
Sample demo that shows how to build an AI powered app using Amplify, AppSync, DynamoDB, Cognito and Rekognition.
kyeahen/ExpressionRekognitionMusicService
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Tritlo/TACOS
TACOS (There's a Cat On the Sundeck) Detector
aws-samples/amazon-rekognition-custom-labels-a2i-automated-continuous-model-improvement
With Amazon Rekognition Custom Labels, you can easily build and deploy Machine Learning (ML) models to identify custom objects which are specific to your business domain in images without requiring advanced ML knowledge. When combined with Amazon Augmented AI (A2I), you can quickly integrate a ML workflow to capture and label images with a human workforce for model training. As ML lifecycle is an iterative and repetitive process, you need to implement an effective workflow that can provide for continuous model training with new data and automated deployment. Your workflow also needs to be flexible enough to allow for changes without requiring development rework as your business objectives change. Operationalizing an effective and flexible workflow can be resource intensive, especially for customers who have limited machine learning capabilities. In this post, we will use AWS Step Functions, AWS Lambda, and AWS System Manager Parameter Store to automate a configurable ML workflow for Rekognition Custom Labels and A2I. We will provide an overview of the solution and instructions to deploy it with AWS CloudFormation.
jpbarbosa/sst-rekognition
An event-driven app to label images on top of AWS using SST (Serverless Stack), TypeScript, and React.
p1ass/emojic.ch
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Cryptonomic/ImageProxy
Image Proxy for use with Wallets
drpventura/PythonRekognitionDemo
Examples of using AWS Rekognition from Python
KaleFive/Categorize
Lambda function to pull from S3, run image through AWS Rekognition and store in DynamoDB
alexjsmac/soundscape-generator
A Flask app to generate soundscapes from pictures and videos
aws-samples/amazon-ivs-moderation-with-record-to-s3-web-demo
This demo shows how you can use Amazon IVS's Auto-Record-to-S3 feature in conjunction with Amazon Rekognition to moderate streams.