SmartFace Attendance System

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Overview

SmartFace_Attendance_System is a real-time face recognition system for automated student attendance tracking using computer vision. It detects and recognizes faces from a webcam, logs attendance to CSV files with timestamps, and optionally sends data to a university backend via API.

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Key Features

• Real-time face detection and recognition using webcam
• Encodes known face images and saves as .pkl
• Automatic CSV attendance logging (date + time)
• API integration with university systems (optional)
• Session-based duplicate prevention
• Modular, maintainable Python architecture

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Sample Use Cases

• Classroom attendance automation
• University smart attendance systems
• Student presence analytics
• Integration with college management platforms

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Tech Stack

Component	Description
Python	Main programming language
OpenCV	Real-time video processing
face_recognition	Face detection & encoding
NumPy	Numerical operations
CSV	Local attendance logging
Requests	API communication

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Project Structure

SmartFace_Attendance_System/
│
├── attendance_records/
│   └── 04-07-2025_22-32-13_attendance.csv
│
├── known_faces_data/
│   └── Raafat_Nagy.jpg
│
├── models/
│   └── encodings.pkl
│
├── src/
│   ├── api/
│   │   └── send_attendance_api.py
│   ├── encoder/
│   │   └── face_encoder.py
│   ├── recognizer/
│   │   └── face_recognition_system.py
│   ├── logger/
│   │   └── csv_logger.py
│   └── utils/
│       └── draw_box_label.py
│
├── encode_faces.ipynb
├── face_recognition_system_main.ipynb
├── requirements.txt
└── run_recognition.py

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Installation

Clone the repository

git clone https://github.com/Raafat-Nagy/SmartFace_Attendance_System.git
cd SmartFace_Attendance_System

Create virtual environment

python -m venv venv
source venv/bin/activate      # For Linux/macOS
venv\Scripts\activate         # For Windows

Install dependencies

pip install -r requirements.txt

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Face Encoding

Place labeled student images in known_faces_data/, where each filename corresponds to the student name or ID.

Then run:

python encode_faces.py

This creates models/encodings.pkl.

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Run the System

Launch the recognition system:

python run_recognition.py

The webcam window will show face boxes and names. Attendance will be saved automatically.

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API Integration

If send_api=True, attendance is sent to:

GET https://nextgenedu-database.azurewebsites.net/api/attendance/{hall_id}/{student_tag}

You can enable or disable this in run_recognition.py.

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Output Example

• Real-time webcam feed with name overlays
• Logs saved in attendance_records/DATE_TIME_attendance.csv
• Columns: Name, Time

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Acknowledgments

• face_recognition
• OpenCV
• NumPy

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