Face Recognition Attendance System

AI-powered attendance management using facial recognition with Python, OpenCV, and Flask.

📷 Project Screenshot / Demo Preview
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📄 Project Overview

The Face Recognition Attendance System is an AI-based solution that automates student attendance marking using facial recognition technology. The system uses OpenCV and face_recognition library to detect and identify registered students through a webcam feed and automatically records their attendance in a database.

This eliminates manual attendance processes, prevents proxy attendance, and provides instant reports for teachers and administrators. The project includes an admin dashboard built with Flask where reports can be exported and viewed in real time.

📚 Abstract

Traditional attendance systems are prone to manual errors and proxy marking. This project proposes an intelligent face recognition system that leverages Haar Cascade and deep learning-based facial embedding models to identify students from a live camera feed. The system achieves over 95% recognition accuracy under controlled lighting conditions and integrates seamlessly with a MySQL database for persistent attendance records.

Technologies Used

Python 3.x OpenCV face_recognition Flask MySQL HTML/CSS/JS NumPy Pandas

🔌 Project Modules

Module 1: User Registration & Face Dataset Creation
Module 2: Face Detection and Feature Extraction (OpenCV)
Module 3: Face Recognition Engine (face_recognition library)
Module 4: Attendance Recording and Database Management
Module 5: Admin Dashboard (Flask Web Interface)
Module 6: Attendance Reports & Export (CSV/PDF)
Module 7: Teacher / Admin Authentication Module

📚 Documentation Included

Project Synopsis (2–3 pages)
Abstract & Literature Survey
System Requirements Specification (SRS)
Full Project Report (50+ pages)
UML Diagrams (Use Case, ER Diagram, DFD)
PowerPoint Presentation (20 slides)
Setup & Installation Guide

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