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Code for the workshop in BOUN Tech Summit (03.03.2019)

License: MIT License

HTML 4.12% CSS 9.89% JavaScript 85.99%

intenseye-boun-workshop's Introduction

Emotion and gender recognition in browser

Intenseye Bogazici University Tech Summit Workshop

This application is for demonstration of how to run deep learning models on the browser using javascript and Tensorflow.js

Demo

To run the demo please visit https://intenseye.github.io/intenseye-boun-workshop/.

Development

This project was bootstrapped with Create React App. For more information about how to run it please visit the link. In order to run the app in the development mode, you can run :

npm install
npm start

Open http://localhost:3000 to view it in the browser. The page will reload if you make edits. You will also see any lint errors in the console. Multiple pretrained models are included in the repository as url.

In this repository we are using Keras models. If you wish to use your own model you can reference to this link to convert your own models.

Intenseye

Intenseye is deep learning powered video analytics platform @intenseye โ€“ [email protected] For more information https://intenseye.com/.

Contributing

  1. Fork it (https://github.com/yourname/yourproject/fork)
  2. Create your feature branch (git checkout -b feature/fooBar)
  3. Commit your changes (git commit -am 'Add some fooBar')
  4. Push to the branch (git push origin feature/fooBar)
  5. Create a new Pull Request

Model Credit

For more information about how to train, obtain or understand these models you can check out this awesome repository

intenseye-boun-workshop's People

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