🎉 Face Recognition Application

A professional face recognition application built with Node.js, TensorFlow.js, and Docker. This project delivers advanced face detection and recognition with enterprise-grade security and blazing-fast performance.

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🚀 Features

✨ AI-Powered Recognition: Advanced face detection and recognition using TensorFlow.js and face-api.js
🔒 Enterprise Security: Security best practices (rate limiting, input validation, secure file handling, CSP, CORS)
🐳 Docker Ready: Multi-stage Docker build for consistent deployment
⚡ High Performance: Optimized with compression, Redis caching, and efficient image processing
💻 Modern UI: Responsive web interface (EJS + Tailwind CSS)
🔗 API First: RESTful API endpoints for integration
⏱️ Real-time Processing: Fast face detection and recognition with confidence scoring
🎥 Live Face Recognition: Real-time face detection and recognition from webcam (WebRTC), with smart pause and overlay
📋 Comprehensive Logging: Winston logger, request logging, error tracking
🧪 Automated Testing: Jest, Supertest, CI/CD pipeline

📸 Demo & Screenshots

Here are some main views of the application:

Home

Main dashboard view of the Face Recognition app.

Enroll Face

Page to enroll a new face into the database.

Recognize Face

Page to recognize a face from an uploaded photo.

Live Face Recognition

Real-time face recognition from webcam with overlay and results card.

About

Project and developer profile page.

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🛠️ Tech Stack

• Backend: Node.js, Express.js
• AI/ML: TensorFlow.js, face-api.js
• Database: SQLite3
• Image Processing: Sharp, Canvas
• Security: Helmet, Rate Limiting, Input Validation, CORS, CSP
• Performance: Compression, Redis Caching
• Frontend: EJS, Tailwind CSS
• Containerization: Docker, Docker Compose
• Development: ESLint, Prettier, Nodemon, Jest, Supertest

📋 Prerequisites

• Node.js >= 18.0.0
• npm >= 8.0.0
• Docker & Docker Compose (for containerized deployment)

🚦 Quick Start

1. Clone the repository

   git clone https://github.com/dedinopriadi/face-recognition-app.git
cd face-recognition-app

2. Install dependencies

npm install

3. Download Face Recognition Models

node scripts/download-models.js
   # Or download manually from:
# https://github.com/justadudewhohacks/face-api.js/tree/master/weights
# Place files in ./models directory

4. Start development server

npm run dev

5. Access the application
   • 🌐 Web UI: http://localhost:3000
   • 📝 Enroll Faces: http://localhost:3000/enroll
   • 🕵️ Recognize Faces: http://localhost:3000/recognize
   • 🎥 Live Face Recognition: http://localhost:3000/live-recognize
   • 💓 Health Check: http://localhost:3000/health
   • 📊 API Status: http://localhost:3000/api/status

🐳 Docker Development

npm run docker:dev
# App: http://localhost:3000
# Redis: localhost:6379
# Redis Commander: http://localhost:8081

🚢 Production Deployment

npm run docker:prod

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🛠 Project Structure

face-recognition-app/
├── src/
│   ├── config/
│   │   ├── database.js
│   │   ├── logger.js
│   │   ├── redis.js
│   │   └── config.js
│   ├── controllers/
│   │   └── faceController.js
│   ├── middleware/
│   │   ├── upload.js
│   │   └── validator.js
│   ├── routes/
│   │   └── faceRoutes.js
│   ├── services/
│   │   └── faceRecognitionService.js
│   ├── views/
│   │   ├── index.ejs
│   │   ├── enroll.ejs
│   │   ├── recognize.ejs
│   │   ├── 404.ejs
│   │   └── error.ejs
│   └── server.js
├── models/              # Face-api.js model files
├── data/                # SQLite database files
├── uploads/             # File uploads
├── public/              # Static assets
├── tests/               # Test files
├── scripts/             # Build and deployment scripts
├── Dockerfile           # Multi-stage Docker build
├── docker-compose.dev.yml
├── docker-compose.prod.yml
├── package.json
└── README.md

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🔧 Configuration

Environment Variables

Buat file .env di root project, contoh:

NODE_ENV=development
PORT=3000
REDIS_HOST=redis
REDIS_PORT=6379
# REDIS_URL=redis://localhost:6379
UPLOAD_PATH=./uploads
MAX_FILE_SIZE=10485760
CORS_ORIGIN=http://localhost:3000
RATE_LIMIT_WINDOW_MS=900000
RATE_LIMIT_MAX_REQUESTS=100

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🔒 Security Features

• Helmet: Security headers
• CSP: Content Security Policy strict
• CORS: Configurable via env
• Rate Limiting: Global & sensitive endpoint (Redis store)
• Input Validation: All endpoints
• File Upload Validation: Type, size, and content
• User non-root: Dockerfile prod

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📚 API Documentation

Health Check

GET /health

Returns application health status.

API Status

GET /api/status

Returns API version and environment information.

Face Recognition Health

GET /api/face/health

Returns face recognition service status and model loading status.

Enroll New Face

POST /api/face/enroll
Content-Type: multipart/form-data
Body:
- name: string (required)
- image: file (required)

Enrolls a new face in the database.

Recognize Face

POST /api/face/recognize
Content-Type: multipart/form-data
Body:
- image: file (required)

Recognizes a face against the enrolled database.

Live Face Recognition (Webcam)

POST /api/face/recognize-live
Content-Type: multipart/form-data
Body:
- image: file (required, JPEG/PNG/WebP frame from webcam)

Performs real-time face recognition from webcam frames. Returns detected face info, bounding box, name, confidence, and overlay data.

Smart Pause:

• When the same face is recognized continuously, the client will pause sending frames to save resources.
• Recognition resumes automatically if the face changes or is no longer detected.

Example Response:

{
  "message": "Face recognized successfully",
  "data": {
    "recognized": true,
    "person": {
      "id": 8,
      "name": "Dedi Nopriadi",
      "confidence": 0.63,
      "similarity": 0.63,
      "box": { "x": 172, "y": 133, "width": 163, "height": 141 }
    }
  },
  "source": "live"
}

Get All Faces

GET /api/face/faces

Returns all enrolled faces.

Get Face by ID

GET /api/face/faces/:id

Returns specific face details.

Delete Face

DELETE /api/face/faces/:id

Deletes a face from the database.

Get Dashboard Data

GET /api/face/dashboard

Returns statistics and recent recognition logs.

Get Statistics

GET /api/face/stats

Returns face recognition statistics.

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🧪 Testing & Code Quality

npm test           # Run all tests
npm run test:watch # Watch mode
npm run lint       # Lint code
npm run lint:fix   # Auto-fix lint
npm run format     # Format code

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🐳 Docker Commands

npm run docker:dev   # Development
npm run docker:prod  # Production
npm run docker:down  # Stop all containers

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📊 Monitoring & Logging

• Health check: /health
• API status: /api/status
• Face recognition health: /api/face/health
• Request logging with Morgan
• Error tracking and logging (Winston)
• Live recognize: All frames are processed in-memory, no files are saved to disk for live recognition. Only important events are logged.

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🤝 Contribute & Support

We welcome contributions from everyone! 🚀

• Fork this repository and submit your awesome pull requests.
• Open issues for bugs, ideas, or questions.
• Let's build something amazing together!

If you like this project, consider supporting it:

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📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

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🙏 Acknowledgments

• @vladmandic/face-api for face recognition (Node.js optimized fork of face-api.js)
• TensorFlow.js for AI capabilities
• Express.js for the web framework
• Tailwind CSS for styling

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Made with ❤️ by dedinopriadi — Happy coding!