Attendance Management System GUI Application

A graphical user interface (GUI) Application built on QT Creator, utilizing C++ programming, QMake and OpenCV libraries. The application uses facial recognition technology to mark attendance for events, classes, or meetings.

Preview

Requirements

• OpenCV library for facial recognition.
• Qt for GUI design and development.

Features

• Ability to add new faces to the database for recognition.
• Automatic recognition of registered faces.
• GUI for easy attendance marking and management.
• Records attendance in a text file for later analysis.

Installation

Windows

Install OpenCV and Qt on your system.

Clone or download this repository to your local system.

Open the project in Qt and build the project.

Run the executable file to start the program.

Linux

Install OpenCV and Qt using the terminal by executing the following commands:

  sudo apt-get install libopencv-dev
  sudo apt-get install qt6-default
  
Clone or download this repository to your local system.

Open the project in Qt and build the project.

Run the executable file to start the program.

• QT installation
• OpenCV and OpenCV Contrib installation

Usage

• Start the program and navigate to the "Add Student" tab.
• Add student data to the database and then add face data by clicking the "Add face" button and capturing images of the individual by using any of the two options present:
  1. WebCam
  2. Video (In case of the this option the recorded video should already be present in database folder and it's relative path should be entered when prompted)
• Navigate to the "Mark attendance" tab to start the facial recognition process.
• Registered faces will be automatically recognized, and attendance will be marked in real-time.
• The attendance records can be viewed in the text file created in the folder of the batch entered automatically.

Limitations

The program may not work as expected with low-quality images or poorly lit environments.
Additionally, the program may not be able to recognize faces with significant changes such as facial hair, glasses, masks, etc.

Team Members

• M Satya Sai Teja (Myself) [GUI App Developer & Code Debugger]
• Shivam Litoria [Face Detection & Core Working]
• Holesh Sharma [Code Debugger & Software Tester]

Contribute

If you would like to contribute to the development of this program, please feel free to submit a pull request.

Note

This Program has been written and tested on Ubuntu 22.04 LTS, using :

• QT Creator 6.4.2
• Opencv 4.7.0
• Opencv Contrib

To run the program, you need to make necessary changes to the code according to your system.

License

This program is licensed under the MIT License.