Enhanced Face Recognition Access Control System

A modern, GUI-based face recognition access control system for secure user management and real-time access logging. Built with Python, OpenCV, face_recognition, and Tkinter.

Features

• Face Recognition: Real-time face detection and recognition using webcam.
• Admin Panel: Secure login for administrators to manage users and view access logs.
• User Management: Add, edit, and delete users with face image capture.
• Access Logs: Automatic logging of all access attempts (granted/denied) with timestamps.
• Encodings Management: Regenerate face encodings as needed.
• Modern GUI: User-friendly interface built with Tkinter.

Project Structure

├── database_manager.py        # Handles SQLite database operations
├── enhanced_encoder.py        # Face encoding generation and management
├── run_face_recognition.py    # Real-time face recognition logic
├── main_gui.py                # Main GUI application (Tkinter)
├── requirements.txt           # Python dependencies
├── EncodedImages.p            # Pickled face encodings (auto-generated)
├── img/
│   └── Modes/                 # User face images (auto-managed)
├── README.md                  # Project documentation

Installation

1. Clone the repository
2. Create a virtual environment (recommended):

   python3 -m venv myenv
   source myenv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

Usage

1. Run the main GUI:

   python main_gui.py

2. Default Admin Login:
   • Username: admin
   • Password: admin123
3. Add users via the Admin Panel (capture face images for recognition).
4. Use the CHECK button to start real-time face recognition.
5. Monitor access logs in the Admin Panel.

Requirements

• Python 3.8+
• Webcam
• Linux, Windows, or macOS

Dependencies

See requirements.txt for all Python packages:

• opencv-python
• face-recognition
• face-recognition-models
• numpy
• pillow
• tk
• sqlite3 (usually included with Python)

Notes

• All user face images are stored in img/Modes/.
• Face encodings are stored in EncodedImages.p (auto-generated).
• The database is face_recognition.db (auto-generated).
• For best results, use clear, front-facing face images.
• If you got problem while installing face_recognition you have to make sure that cMake and dlib are correctly installed in your pc

---

🤝 Feel free to contribute or reach out:
kadanassim42@gmail.com