Automated Attendance System with Face Recognition

Overview

The "Automated Attendance System with Face Recognition" is a sophisticated project designed to simplify and enhance the process of recording and managing student attendance. Leveraging advanced face recognition technology, this system automates attendance tracking, making it accurate, efficient, and user-friendly.

Key Features

• Face Recognition Technology: Utilizes cutting-edge face recognition technology for automated student identification based on facial features.

• Real-time Attendance Tracking: Marks attendance in real-time as students enter the designated area, eliminating manual attendance recording.

• User-Friendly Interface: Provides an intuitive graphical interface displaying essential information, including student details, date, and time.

• Data Management: Stores student information and attendance records in structured formats for easy management and analysis.

• Photo Display: Enhances user experience by displaying student photos alongside attendance records for visual verification.

• Automatic Notifications: Notifies users when their attendance is successfully marked, ensuring transparency and student awareness.

How it Works

1. Initialization: The system initializes with pre-trained facial encodings.

2. Face Detection: As students enter the area, the system detects faces in real-time.

3. Recognition: Faces are matched against stored encodings to identify students.

4. Attendance Marking: When a student's face is recognized, their attendance is marked with a timestamp.

5. User Interface Update: The graphical interface displays student details and photos along with attendance records.

6. Data Management: Attendance data is stored in a CSV file for real-time access or export.

APP GUI

User Interface

Face found

Attendance marked

Trying to re-take the Attendance

Error

Benefits

• Accuracy: Eliminates the possibility of proxy attendance or manual errors.

• Efficiency: Reduces administrative workload and accelerates the attendance process.

• Transparency: Provides immediate feedback to students about their attendance status.

• Data Management: Organizes attendance data for easy access and analysis.

• Scalability: Can be adapted for various educational or corporate environments.

Usage

1. Clone this repository to your local machine.

2. Install the required dependencies using pip install -r requirements.txt.

3. Configure the system settings and paths in the code to suit your specific environment.

4. Run the project using python GUI.py.

Author

• Chandrababu Namani