Real-time Offline Objects Recognition (ROOR) Progressive Web App (PWA)

ROOR brings the benefits of AI and machine learning to your device's browser, it integrates a pre-trained machine learning objects recognition model for offline use, and since it is a Progressive Web App (PWA) that means the whole app can be operated completely offline. After the initial load, no connection is required to operate the app.

This PWA requires access to the device's camera feed.

This project was implemented using Angular (TypeScript), HTML and CSS.

This project was generated with Angular CLI version 8.2.1.

Demo

https://irkan-hadi.github.io/roor/index.html

https://roor-pwa.web.app

https://roor-pwa.firebaseapp.com

Development server

• Run npm install
• Run ng build --prod && http-server dist\\roor-pwa -a localhost -p 8080 -c-1 for a dev server. Navigate to http://localhost:8080/.

Code scaffolding

Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.

Build

Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the --prod flag for a production build.