Face Recognition Security System

A sophisticated security system that combines facial recognition with web-based authentication for secure file access and real-time monitoring.

Features

• Advanced Face Recognition

  • Real-time face detection and recognition
  • Anti-spoofing measures with screen detection
  • Face encoding caching for improved performance
  • Support for multiple known faces
  • Unknown face detection with email alerts

• Security System

  • JWT-based authentication
  • Secure file access control
  • Email notifications for security events
  • Session management
  • Face verification required for access

• Web Interface

  • Modern responsive design
  • User registration and login
  • Real-time face verification
  • File management system
  • Secure file upload/download

Technology Stack

• Backend

  • Python (Flask) for face recognition server
  • Node.js/Express for web server
  • MongoDB for data storage
  • JWT for authentication
  • GridFS for file storage

• Frontend

  • HTML5/CSS3
  • JavaScript
  • Responsive design
  • WebRTC for camera access

• Libraries

  • OpenCV (cv2)
  • face_recognition
  • dlib
  • numpy
  • bcrypt
  • mongoose

Prerequisites

• Python 3.x
• Node.js
• MongoDB
• CMake (for dlib installation)
• Webcam
• SMTP server access for email notifications

Installation

1. Clone the repository:

   git clone [repository-url]
   cd IOMP_Home

2. Install Python dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

3. Install Node.js dependencies:

   cd templates
   npm install

4. Configure environment variables: Create a .env file in the templates directory with:

   JWT_SECRET_KEY=your-secure-key
   MONGODB_URI=your-mongodb-uri
   SESSION_SECRET=your-session-secret
   

5. Set up email configuration in app.py:

   sender_email="your-email@gmail.com"
   email_password="your-app-specific-password"

Usage

1. Start the Flask server:

   python app.py

2. Start the Node.js server:

   cd templates
   node index.js

3. Access the web interface:

   • Open http://localhost:8080 for the web interface
   • Create an account or login
   • Complete face verification
   • Access secure files

Adding Known Faces

1. Add face images to the dataset_family/ directory
2. Images should be clear frontal faces
3. Name the files with the person's name (e.g., John.jpg)
4. The system will automatically encode and cache the faces

Security Features

• Face recognition with anti-spoofing
• JWT authentication with expiration
• Secure password hashing
• Email notifications for:
  • Unknown face detection
  • Failed verification attempts
  • Successful verifications
  • File access events

Project Structure

IOMP_Home/
├── app.py                 # Flask server & face recognition
├── face_Recog.py         # Face recognition system
├── requirements.txt      # Python dependencies
├── dataset_family/       # Known faces storage
├── templates/           
│   ├── index.js         # Node.js server
│   ├── public/          # Frontend files
│   ├── routes/          # API routes
│   ├── models/          # Database models
│   └── middleware/      # Auth middleware

Error Handling

• See NOTE.txt for common installation issues
• For face_recognition_models errors:
  1. Delete the venv folder
  2. Recreate virtual environment
  3. Install requirements
  4. Install setuptools
• For dlib errors, install CMake and add to PATH

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit changes
4. Push to the branch
5. Open a pull request

License

[Your License Here]

Acknowledgments

• OpenCV and face_recognition libraries
• Node.js and Express communities
• MongoDB and Mongoose teams