Face Recognition Attendance System

A real-time, ML-based facial recognition system for automated attendance logging, built with Python, OpenCV, and MySQL.

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⭐ Overview

This project automates the process of attendance marking using computer vision. It leverages OpenCV for face detection and recognition and logs all attendance events in a MySQL database. The system reduces manual errors and enables secure, contactless attendance for classrooms or office environments.

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🛠 Tech Stack

• Language: Python 3
• Libraries: OpenCV, NumPy, MySQL Connector
• Database: MySQL
• Algorithms: Haar Cascade (face detection), LBPH (face recognition)

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🚀 Features

• Face Detection: Uses Haar Cascade classifier for real-time face detection via webcam.
• Face Recognition: Employs the LBPH algorithm to recognize faces from a trained dataset.
• Attendance Logging: Stores recognized faces and timestamps directly in a MySQL database.
• Contactless Attendance: Enables secure, efficient, and paperless attendance taking.
• Modular Structure: Includes separate modules for data collection, training, and recognition.

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📷 Demo

Screenshots incoming

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📦 How to Run

1. Clone this repository:

   git clone https://github.com/sharma021/facial-recogniton.git
   cd facial-recogniton

2. Install Python dependencies:

   pip install -r requirements.txt

   (If requirements.txt is missing, list your main dependencies: opencv-python, numpy, mysql-connector-python)

3. Configure MySQL Database:

   • Create a new database in MySQL (e.g., attendance_db).
   • Update your database connection details in the code (typically in db_config.py or wherever credentials are set).

4. Collect Training Data:

   • Run the data collection script to capture and store images of each person for training.
   • Example:

     python dataset_collector.py

5. Train the Model:

   • Run the training script to process the images and create the LBPH model.
   • Example:

     python trainer.py

6. Start Attendance Recognition:

   • Run the main attendance script. It will use the webcam for real-time recognition and log entries to the database.
   • Example:

     python main.py

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🗃️ Folder Structure

facial-recogniton/ │ ├── dataset_collector.py # Script to collect training images ├── trainer.py # Script to train LBPH face recognizer ├── main.py # Real-time recognition & attendance logging ├── requirements.txt # Python dependencies ├── README.md # Project overview (this file) └── ... # Other support files