Screenshots & Demo
Real-time face detection interface
Administrator control panel
Detailed attendance reports
Face Recognition-Based Attendance Tracking System
The AI Attendance System is an intelligent face recognition-based attendance tracking solution designed for educational institutions. The system uses advanced computer vision algorithms to automatically identify and record student attendance, eliminating manual processes and reducing errors.
Built with Python and OpenCV, this system provides real-time face detection, recognition, and attendance logging with high accuracy and reliability. The application features a user-friendly interface for both administrators and students.
Real-time face detection using OpenCV's Haar cascades for accurate identification of individuals in various lighting conditions.
Advanced face recognition algorithms that can identify registered students with high accuracy and minimal false positives.
Automatic timestamped attendance recording with detailed logs including date, time, and student identification.
Comprehensive dashboard for administrators to manage students, view attendance reports, and monitor system performance.
Secure SQLite database for storing student information, face encodings, and attendance records with data privacy.
Detailed analytics and reporting features to track attendance patterns and generate comprehensive reports.
Capture and process face images for training the recognition model
Generate unique face encodings for each registered student
Train the face recognition model with collected face data
Implement live face detection and recognition in video streams
Record attendance with timestamps and student identification
Create detailed attendance reports and analytics
Several enhancements are planned for the next versions of the AI Attendance System: