https://github.com/vignesh1507/facepulse

FacePulse is a cutting-edge facial recognition-based attendance system designed to streamline and automate attendance tracking. Using AI-powered technology, FacePulse captures, registers, and verifies users' identities in real-time, providing a seamless and efficient solution for modern organizations.
https://github.com/vignesh1507/facepulse

ai opencv python streamlit

Last synced: 2 months ago
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FacePulse is a cutting-edge facial recognition-based attendance system designed to streamline and automate attendance tracking. Using AI-powered technology, FacePulse captures, registers, and verifies users' identities in real-time, providing a seamless and efficient solution for modern organizations.

• Host: GitHub
• URL: https://github.com/vignesh1507/facepulse
• Owner: vignesh1507
• License: gpl-3.0
• Created: 2024-09-21T18:35:06.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-04-19T04:28:58.000Z (2 months ago)
• Last Synced: 2025-04-22T19:06:29.455Z (2 months ago)
• Topics: ai, opencv, python, streamlit
• Language: Jupyter Notebook
• Homepage:
• Size: 626 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

        
## FacePulse: Facial Recognition-Based Attendance System 

FacePulse is an AI-driven facial recognition-based attendance system developed using Python language, Streamlit application, 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:

   ```bash

   git clone https://github.com/vignesh1507/FacePulse.git

   cd FacePulse