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FacePulse: Facial Recognition-Based Attendance System

FacePulse is an AI-driven facial recognition-based attendance system developed using Python, Streamlit, and OpenCV. This system allows users to register with their ID and name, capture their images via webcam, train a machine learning model to recognize faces, and track attendance in real time.

Features

  • User Registration: Capture images through webcam and associate them with a user ID and name.

  • Model Training: Train a facial recognition model on the captured images.

  • Real-Time Attendance: Detect and track attendance using the trained model.

  • Streamlit User Interface (UI): Easy-to-use web interface for registration, model training, and attendance tracking.

Technologies Used

  • Python: Core language for the application.

  • Streamlit: This is for building the interactive web interface.

  • OpenCV: For image capture and processing.

  • Pyngrok: For tunneling the local application to the web.

  • Facial Recognition Libraries: These are for identifying and verifying registered faces.

Installation

  1. Clone the repository: 
    git clone https://github.com/vignesh1507/FacePulse.git
cd FacePulse