Hand Gesture Enabled Operation for Computer Using Deep Learning

This project aims to develop a system that detects hand gestures and prints corresponding instructions for computer operators. The system utilizes Deep learning algorithms CNN and mediapipe to recognize hand gestures, and then prints instructions for the operator to perform specific computer operations.Operations like Notepad Open,Shutdown,Volume Up,Volume Down etc.The system will consist of a webcam, a Deep learning model, and a printer. The webcam will capture images of hand gestures, which will be processed using the Deep learning model to identify the specific gesture. The system will then print the corresponding instruction on the printer. The system will be designed to be user-friendly and adaptable to different environments and hardware configurations.The system aims to improve efficiency, reduce errors, and enhance accessibility for computer operators. The proposed system consists of a hand gesture detection module, instruction printing module, and computer operation module. The system is trained using a dataset of hand gestures and corresponding computer operations. Experimental results show that the system achieves high accuracy in gesture recognition and instruction printing. The system has potential applications in various fields, including gaming, education, and healthcare. Key Words: Hand gesture detection, Deep learning, instruction printing, computer operation, accessibility, Mediapipe, CNN.