Face Recognition Based Attendance Management System – A Complete Python Project

Face Recognition Based Attendance Management System

Overview

The Face Recognition Attendance System is a desktop app made with Python and OpenCV. It basically takes attendance by recognizing faces, so you don’t have to call out names one by one in class or at work.

It has a pretty simple interface using Tkinter, where you can add your face, train it, and then it’ll start marking attendance on its own. It’s actually a best project, and it’s good for college submissions or even small places that wanna use it for real.

Project Summary

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Code Requirements

Before running the project, ensure the following Python libraries are installed:

• OpenCV (pip install opencv-python)
• Tkinter (built-in with Python)
• Pillow (pip install Pillow)
• Pandas (pip install pandas)

Additionally, if database integration is required, set up WAMP Server and configure MySQL.

Project Structure

The project is structured with clarity to allow easy navigation and setup:

• AMS_Run.py: Main application file with the GUI
• TrainingImage/: Stores user face images (automatically created)
• TrainingImageLabel/Trainner.yml: Trained face data
• StudentDetails/StudentDetails.csv: Contains user records
• Attendance/: Stores attendance logs
• haarcascade_frontalface_default.xml: Face detection model

Functional Flow

1. Image Capture:
   Users enter their ID and name, then click on Take Images. The system captures 200 facial images and stores them in TrainingImage/.
2. Model Training:
   After collecting data, clicking Train Image trains the face recognizer using OpenCV’s LBPH algorithm. This creates the trained model in TrainingImageLabel/.
3. Automatic Attendance:
   Clicking on Automatic Attendance activates the camera, recognizes faces in real time, and marks attendance into a .csv file based on time and subject.
4. Manual Attendance Option:
   A button is available for Manually Fill Attendance to record attendance without facial recognition.
5. Database Integration (Optional):
   Attendance records can be stored in a MySQL database by configuring the DB name in AMS_Run.py and using WAMP Server.

Available Features

• Face data capture and storage
• Real-time face recognition and attendance logging
• CSV-based attendance report generation
• Manual attendance support
• Optional MySQL database storage
• Simple and user-friendly Tkinter GUI
• Customizable subject and session timing
• Optimized for training up to 10 users

How to Use

1. Download and extract the ZIP file.
2. Install all required dependencies.
3. Create a TrainingImage folder in the root directory if not already present.
4. Open AMS_Run.py and configure your system paths and database credentials (if needed).
5. Run AMS_Run.py and use the UI for registration, training, and attendance.

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