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video-rekognition's Introduction

Video-Rekognition

A project uses AWS Rekognition to do video analysis.

  • Re-implemented the front-end based on my previous implementation Smart Retailer;

AWS Setup

Take a look at this file for the backend, follow the format and use your own customized contents.

https://github.com/denven/Video-Rekognition/blob/master/back-end/.env.example

What business analytics do we get from videos?

The app will extrapolate simple business analytics from videos for the day to day operations.

  • Number of customers in video
  • Age, sex, emotions (physical)
  • Average time in video
  • Recurrences of previously analyzed people in videos
  • Average time before recurrences

Screenshots

Videos Uploaded and status of Analysis Analysis for new customers-Line Chart View Analysis for new customers-Bar Chart View

How to use this APP?

  1. Hit Upload Tab at the SiderBar
  2. Drag and drop mp4 files (files named as: VID_YYYYMMDD_HHMMSS.mp4 will be accepted)
  3. Upload file and drink a cup of coffee to wait until the analysis is done!

Note:

  • The video analysis takes time, and the waiting time varies from duration, motions, persons, file sizes, resolutions of the video. It will awalys take several minutes to for a 20s video;
  • You should have your AWS account configured, including users/roles/credential keys, Rekognition, S3, SQS, SNS services setup etc.
  • Be aware of your bill if you stick to uploading large size and complex videos for analysis.

What's the stack

Backend

  • Node.js
  • Express.js
  • Postgres
  • AWS Rekognition, S3, SNS, SQS
  • Server Sent Events

Frontend

  • React.js
  • Material UI
  • Material table
  • reCharts

video-rekognition's People

Contributors

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Watchers

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