Identity Gaurd

Facial Recognition system aimed at capturing and recognising user's face and diplaying their name.

Face Recognition Attendance System

About the Project

This project is a face recognition-based attendance system designed to detect and recognize faces in real-time using a webcam. The system marks attendance by identifying known faces from a pre-encoded dataset and records the attendance details into a CSV file.

Features

  • Real-time Face Detection: Utilizes a webcam to detect faces in real-time.
  • Face Recognition: Matches detected faces with a pre-encoded dataset to recognize known individuals.
  • Attendance Marking: Records attendance details such as name and time into a CSV file for each recognized individual.
  • Historical Data: Saves attendance data in a daily CSV file.

How It Works

  1. Encoding Faces: Pre-processes and encodes faces from a dataset of images.
  2. Face Detection: Uses the webcam to detect faces in real-time.
  3. Face Recognition: Compares detected faces with the encoded dataset to identify known individuals.
  4. Mark Attendance: Records the attendance by saving the name and time in a CSV file.

Tech Stack

  • Python
  • OpenCV
  • Face Recognition Library
  • CVZone
  • Pickle
  • NumPy

GitHub Repository

Explore the source code and contribute to the project on GitHub: View on GitHub