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Project Post 5/11/2026

Angular PWA — Object Detection

Object Detection PWA with Angular

PWA built with Angular 19 for client-side image classification using TensorFlow.js and MobileNet. Offline support and GPU acceleration via WebGL.

🧭 Overview

Progressive Web App that lets users upload an image and get object classification predictions directly in the browser using TensorFlow.js (MobileNet). Inference runs client-side — no images are sent to external servers.

🔗 Demo: https://pwa-angular.vercel.app/

✨ Features

  • Image classification with TensorFlow.js + MobileNet.
  • Installable PWA with offline support.
  • GPU-accelerated predictions via WebGL.
  • Update notifications when a new version is available.
  • Responsive UI with Angular Material.

🛠️ Tech Stack

  • Angular 19
  • TypeScript 5
  • Angular Material
  • Angular Service Worker
  • TensorFlow.js + MobileNet
  • SCSS + ESLint

📋 Requirements

  • Node.js 18+
  • npm
  • Angular CLI (optional, recommended)

🚀 Installation

git clone https://github.com/Fr4n0m/pwa-angular.git
cd pwa-angular
npm install
npm start

App runs at http://localhost:4200.

🌍 Test PWA Mode (Offline)

npm run build
npx http-server -p 8080 -c-1 dist/pwa-angular/browser

Open http://localhost:8080.

📜 Main Scripts

Script Description
npm start Start dev server
npm run build Production build
npm run watch Watch build
npm test Unit tests
npm run lint Lint code

🤝 Contributing

  1. Fork the repository.
  2. Create a branch: git checkout -b feature/your-change.
  3. Keep commits clear and focused.
  4. Run npm run lint and npm test.
  5. Open a PR with a concise explanation of the change.

Open an Issue first if you find a bug or want to discuss an enhancement.

📄 License

MIT

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