Virtuality Keyboard by AI

Abstract

As everyone knows, computer vision is used to process images in machine learning. Today, for this wonderful task, we are using OpenCV and the cv-zone library in Python. Everyone is familiar with OpenCV, and the cv-zone is essentially a library for hand detection, pose detection, face detection, and other related tasks. By this, we created a keyboard named as “Virtuality Keyboard”. It is just another example of today's computer trend of making things smaller and faster. Computing is no longer limited to desktops and laptops; it has also made its way into mobile devices such as palmtops and cell phones. But the input device, the good old QWERTY keyboard, has not changed in the last 50 years or so. The most recent advancement is virtuality keyboard technology. The virtuality keyboard technology uses computer vision technology and artificial intelligence to let users work in air, by just navigating fingers in air to access keyboard keys. OpenCV is the most popular library for the task of computer vision; it is a cross-platform open-source library for machine learning, image processing, and other tasks that is used to develop real-time computer vision applications. CVzone is a computer vision package that uses the OpenCV and Media Pipe libraries as its core, making it simple to run applications such as hand tracking, face detection, facial landmark detection, pose estimation, and so on, as well as image processing and other computer vision-related applications. The modules that were required were then installed. The CVzone Hand Detector module, Hand Tracking Module, and then import Controller from Pynput keyboard to make the virtual keyboard work. Hand detector was assigned to the detector after we initialised it with a detection confidence of 0.8. Then, based on the layout of our keyboard, we created an array of lists and defined an empty string to store the typed keys.