Face Recognition Based Attendance System

Face Recognition Based Attendance System

Face Recognition Based Attendance System

Project Overview

The Face Recognition Based Attendance System is a Python-based application that integrates face recognition with a graphical user interface (GUI) to simplify and automate attendance management. This project is user-friendly, secure, and highly functional, making it ideal for educational institutions or corporate environments.

Screenshot-2025-01-12-153720-1024x410 Face Recognition Based Attendance System

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Project Details

Project Attribute Details
Project Name Face Recognition Based Attendance System
Language/s Used Python
Python Version (Recommended) 3.x
Database CSV Files (No external database required)
Type Paid Project
Developer updategadh.com

Available Features

  • Graphical User Interface (GUI):

    • Developed using Python’s tkinter library for intuitive navigation.

  • Face Recognition:

    • Utilizes OpenCV for real-time face recognition and attendance marking.

  • Secure Registration:

    • Password-protected feature for registering new students or employees.

  • Attendance Record Management:

    • Automatically generates and updates CSV files for daily attendance records.

  • Real-Time Updates:

    • Displays live attendance records in a tabular format with ID, name, date, and time.

  • Report Generation:

    • Stores detailed logs of attendance for future reference.

Technology Stack

  1. tkinter: For GUI development.
  2. OpenCV: For face detection and recognition.
  3. Pandas, Numpy, CSV: For data handling and storage.
  4. Haar Cascade: Used for frontal face detection.

How to Run the Project

  1. Prerequisites:

    • Ensure Python 3.x is installed on your system.
    • Install the required libraries using the following command: pip install -r requirements.txt

  2. Steps to Execute:

    • Navigate to the project directory.
    • Run the main.py file using the command: python main.py

  3. Face Recognition Configuration:

    • The system uses haarcascade_frontalface_default.xml for face detection. Ensure this file is in the project directory.

Download the Project

To download the complete source code, click the button below:


 

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