🎓 Face Recognition Attendance System

A real-time face recognition-based attendance system using YOLOv8/YOLOv11n for face detection, ArcFace (ONNX) for face embeddings, and FAISS for fast and scalable face matching. The system captures frames from a WiFi camera, recognizes students, and logs their attendance in a CSV file, while storing metadata in MongoDB.

📌 Features

• 🔍 Face Detection using YOLOv8/YOLOv11n
• 🧠 Face Recognition using ArcFace embeddings
• 📷 Live Frame Capture from WiFi camera
• 📦 Student Data stored in MongoDB (name, ID, class)
• 🧾 Attendance Logging in CSV format
• 🚀 Fast search with FAISS index

🛠️ Tech Stack

Component	Technology
Face Detection	YOLOv8 / YOLOv11n
Face Embeddings	ArcFace (ONNX)
Face Search	FAISS
Backend Language	Python
Database	MongoDB
Logging Format	MongoDB
Video Source	WiFi Camera (IP-based)

📂 Project Structure

project/
├── camera_capture/
│   └── capture.py
├── face_detection/
│   └── detect_faces.py
├── face_recognition/
│   ├── arcface_model.py
│   └── recognize.py
├── attendance_log/
│   └── log_attendance.py
├── database/
│   └── students.db
├── training/
│   └── fine_tune.py
└── main.py

🚀 Setup Instructions

1. Clone the Repository

git clone https://github.com/Pawan4356/Smart-attendance.git
cd Smart-attendance

2. Create Virtual Environment & Install Dependencies

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

3. Configure MongoDB

Make sure MongoDB is running. Update connection URI and collection info in database folder.

4. Install Both models Required.

5. Run the System

python main.py