An AI-powered web application that automatically detects and recognizes faces from an uploaded image and generates attendance records.
Built using Python, Flask, OpenCV, and dlib face recognition models.
Upload a classroom image → Detect faces → Recognize students → Automatically generate attendance.
- Face detection using dlib HOG detector
- Face recognition using 128D face embeddings
- Multi-face recognition
- Automatic attendance marking
- Bounding boxes with names on faces
- Web interface built with Flask + Bootstrap
- CSV attendance logging
- Upload image through browser
Browser ↓ Flask Web Server ↓ Face Recognition Engine (dlib) ↓ Attendance Generator ↓ CSV Attendance File
face_recognition_attendance_system/
│ ├── app.py # Flask application ├── src/ # Recognition logic │ ├── dataset/ # Training images │ ├── encodings/ # Encoded face vectors │ ├── models/ # dlib models │ ├── attendance/ # Attendance CSV logs │ ├── static/ │ ├── uploads/ # Uploaded images │ └── results/ # Output images │ ├── templates/ │ ├── index.html │ └── result.html │ ├── README.md └── .gitignore
Clone repository
git clone https://github.com/YOUR_USERNAME/face-recognition-attendance-system.git
cd face-recognition-attendance-system
Create virtual environment
python3 -m venv venv source venv/bin/activate
Install dependencies
pip install -r requirements.txt
Start Flask server
python app.py
Open browser
Upload an image and generate attendance.
- Face detection with bounding boxes
- Recognized students list
- Attendance saved to:
attendance/attendance.csv
- Python
- Flask
- OpenCV
- dlib
- NumPy
- Bootstrap
- Live webcam attendance
- Cloud deployment
- Database integration
- Student registration portal
- Admin dashboard
Bhoopendra Singh
B.Tech Student | AI & Systems Enthusiast
Give it a star on GitHub ⭐