The Attendance Management System with Face Recognition and Student Management is a comprehensive Desktop-based application designed to automate attendance tracking for organizations schools or any group. This system employs face recognition technology to enhance accuracy and security in attendance monitoring. Additionally it provides functionalities for managing students' information and attendance records.

Here're some of the project's best features:

• The Facial Recognition Attendance and Student Management System combines modern technology with administrative convenience to enhance the attendance tracking process. Here are the key features of this system:
• 1. Facial Recognition Authentication: Utilizes advanced facial recognition algorithms to accurately identify and verify registered students.
• 2. User Authentication and Authorization: Provides secure login functionality for administrators instructors and students. Implements role-based access control to ensure appropriate privileges for each user type.
• 3. Student Management: Allows administrators to add edit and delete student profiles. Captures and stores student information such as name ID contact details and additional relevant data.
• 4. Face Enrollment: Enables the system to register and store facial features of students for subsequent recognition.
• 5. Real-Time Attendance Tracking: Automatically records attendance using facial recognition during class sessions. Provides immediate feedback on attendance status for both students and instructors.
• 6. Manual Attendance Entry: Allows for manual attendance entry in cases where facial recognition may not be feasible.
• 7. User-Friendly Interface: Offers an intuitive and easy-to-use interface for all types of users including administrators instructors and students.
• 8. Data Security and Privacy: Implements robust security measures to protect sensitive data including encryption and secure access controls.
• 9. Instructor Dashboard: Equips instructors with tools to view and manage attendance records for their respective classes. Enables them to monitor attendance trends and patterns.
• 10. Cross-Platform Compatibility: Ensures the system is accessible and functional across various devices and operating systems.

Technologies used in the project:

• SQL
• Python
• Tkinter
• OpenCV
• Machine Learning
• Artificial Intelligence
• haar-cascade frontal face