A dataset for estimation of hand pose and shape from single color images.

Hand detection using OpenCV

Estimate 2D Hand Pose from RGB image by top-down method using Stacked Hourglass Network and Hand Detector module - SSD (single-shot detector)

An application that enables one to virtually paint in the air using their fingers. It is developed in python using Open Cv and MediaPipe

Python script to recognize human hand in video feed.

This Program helps to identify 9 different human body poses with a frame rate of upto 15 frames per second on a i-5 4110 CPU.

An extensive API for hand recognition, built on OpenCV (under development)

This project is a robotic hand controlled by AI. Hand mimmicks the user's finger gestures through a camera.

An AI-based application which let us control the mouse cursor by moving finger in Air .

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

This project demonstrates a real-time hand gesture recognition system using Python, OpenCV, and Gemini AI by Google.

Realtime hand gesture recognition to control your window manager

A Python script for Finger Counting in real-time (using OpenCV and Mediapipe). 🐍

A module to detect hand gestures on live feed of a camera using ML techniques to possibly control and navigate a system interface

Computer vision project that I worked on as part of my 'AI and Data Engineering' training at AiCore.

OpenCV hand recognition

A Hand Gesture Volume Control application made using OpenCV & MediaPipe

Auto-learning search framework based on a weighted double Q-learning algorithm:"Integrated block-wise neural network with auto-learning search framework for finger gesture recognition using sEMG signals"

Virtual zoom AI hand gestuer project is a AI based project in which you can detect hand and fingers and with the help of your index finger and thumb you can zoom in and out. The project is made using python language.

This project is a presentation slideshow application that uses hand gestures for navigation and annotation. It tracks the user's hand to move between images and create annotations. Real-time feedback is provided through annotated images and live camera feed, offering an interactive and intuitive presentation experience.