A Python-based Smart Attendance System that uses Face Recognition technology to automatically identify individuals and record attendance in real time. The project leverages OpenCV and Machine Learning techniques to provide a fast, accurate, and contactless attendance solution.

• Real-time face detection using OpenCV
• Face recognition using trained face datasets
• Automatic attendance marking
• User-friendly interface
• Stores face data for future recognition
• Reduces manual attendance errors
• Fast and efficient attendance management

• Python
• OpenCV
• NumPy
• Pandas
• Scikit-learn
• Pickle

Face-Recognition-Based-Smart-Attendance-System/
│
├── add_faces.py
├── app.py
├── test.py
├── background.png
├── README.md
│
└── data/
    ├── faces_data.pkl
    ├── names.pkl
    └── haarcascade_frontalface_default.xml

git clone https://github.com/Injamul2k24/Face-Recognition-Based-Smart-Attendance-System.git
cd Face-Recognition-Based-Smart-Attendance-System

python -m venv .venv

Windows:

.venv\Scripts\activate

pip install -r requirements.txt

python add_faces.py

python app.py

python test.py

![Home Screen](screenshots/home.png)

• Educational Institutions
• Offices and Workplaces
• Training Centers
• Events and Conferences
• Smart Campus Management

• Database Integration (MySQL/MongoDB)
• Cloud-based Attendance Tracking
• Web Dashboard
• Mobile Application Support
• Email Notifications
• Face Mask Detection

Injamul Hoque

GitHub: https://github.com/Injamul2k24

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