本项目计划用于2024成都理工大学CDUT人工智能协会技术培训使用

✌️Using this you can control your PC/Laptop volume by Hand Gestures created with Python.

Control the volume up and down using the hand gesture with the OpenCV

A Hand Gesture Volume Control application made using OpenCV & Mediapipe

Using mediapipe library to control system volume

An AI-based application which let us do tasks by moving our Hand in Air .It is developed in python using OpenCv and MediaPipe

A Hand Gesture Volume Control application made using OpenCV & MediaPipe

ControlMicTray is a Windows application that enables you to monitor and control your microphone seamlessly. It features an icon in the system tray to display the current status of your microphone, and offers a customizable hotkey for quick access and control.

Magic Session Mixer is a gui tool for live audio control and viewing of active audio sessions

AI hand gester mouse project is a AI based project in which you can assess the volume control with gestures without physically touching the mouse or the system. This project detects the hand and counts the fingers with the first finger up and thumb up all fingers down you can change the volume up and down and with pink finger up with index finge…

This project uses MediaPipe's Hand Landmarks for hand tracking and pycaw for audio control to adjust the system's volume by tracking the distance between the thumb and index finger.

🔉 Change the volume of your computer with your hands using Open Cv.

Used OpenCV , Google's mediapipe to Track Hand Gesture to Control System Volume

This project aims at building a 100% touchless desktop controller using gesture recognition, with initial functionalities like touchless mouse and keyboard, and gesture-based volume adjustement

Control The Volume of System using Gesture with the help of open-cv

An image processing project to control the volume bar using hand gestures.

Android remote control for Windows volume mixer

A Mini-Project, in which we control PC volume by hand gestures using OpenCV and Mediapipe.

This is an innovative project on hand gesture recognition using machine learning techniques to control media playback functions. The project utilizes the MediaPipe framework for real-time hand detection and tracking, along with pyautogui and pycaw libraries for controlling keyboard, mouse, and audio functions. They provide Real-Time Processing.