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.
GPL-3.0 License
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, captures their images via webcam, trains a machine learning model to recognize faces, and tracks attendance in real-time.
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.
Python: Core language for the application.
Streamlit: For building the interactive web interface.
OpenCV: For image capture and processing.
Pyngrok: For tunneling the local application to the web.
Facial Recognition Libraries: For identifying and verifying registered faces.
git clone https://github.com/vignesh1507/FacePulse.git
cd FacePulse