An openCV application that uses Python and MediaPipe to detect hands, hand landmarks, and then use them to paint on a live webcam.
The use of a physical device for human-computer interaction, such as a mouse or keyboard, hinders natural interface since it creates a significant barrier between the user and the machine. However, new sorts of HCI solutions have been developed as a result of the rapid growth of technology and software. In this project , I have made use of a robust hand and finger tracking system ,which can efficiently track both hand and hand landmarks features , in order to make a fun Virtual Painter.
Python 3.9
A python IDE , in my case I used VS code.
OpenCV : OpenCV is the world's largest and most popular computer vision library . The library is cross-platform and free for use.
MediaPipe : MediaPipe offers cross-platform, customizable ML solutions for live and streaming media. it will help us detect and track hands and handlandmarks features.
Numpy : introducing support for large, multi-dimensional arrays and matrices, as well as a vast set of high-level mathematical functions to manipulate them.