This project is a real-time computer vision web application built using Flask, OpenCV, and MediaPipe. It uses MediaPipe’s advanced hand-tracking model to detect hands from a live webcam stream and accurately count the number of raised fingers.
The system continuously processes video frames, identifies hand landmarks, determines whether each finger is raised, and sends the total count to the frontend through a lightweight JSON API. The interface displays the live camera feed along with dynamic finger-count updates, enabling responsive real-time interaction.
This project demonstrates practical skills in computer vision, real-time video streaming, backend API development, and integrated Flask-based web application design.
Cutting-edge UI/UX
Works on all devices
Enterprise-grade security
24/7 customer support
