handtracking

A library for prototyping realtime hand detection (bounding box), directly in the browser.

Pose authoring using handtrackingon Quest

这是一个 Flutter Packge 以实现摄像头精确追踪并识别十指的运动路径/轨迹和手势动作, 且输出22个手部关键点以支持更多手势自定义. 基于这个包可以编写业务逻辑将手势信息实时转化为指令信息: 一二三四五, rock, spiderman...还可以对不同手势编写不同特效. 可用于短视频直播特效, 智能硬件等领域, 为人机互动带来更自然丰富的体验

A pre-trained YOLO based hand detection network.

Oculus Quest hand tracking directly in Unity Editor for fast iteration.

A python wrapper for Mediapipe's Multi-Hand Tracking

Add touch gesture-like hand gestures in your app; based on Handtrack.js + Hammer.js

package google mediapipe hand and holistic tracking into a dynamic link library

HolisticBarracuda is the Unity Package that simultaneously estimates 33 pose, 21 per-hand, and 468 facial landmarks with a monocular color camera only.

AI在前端领域应用的Demo集合

Handtracking mediapipe sample with bitmap RGB input

implemented some computer vision problems

Handtracking using MediaPipe HandPose. Runs as an Electron app and outputs OSC

Hand tracking with Google Mediapipe and Tensorflow demo app

Draw on Screen using Webcam , Built using JS No GPU or Pre-request needed. Easy to integrate on your own apps.

Simple Hand Tracking module and Controlling Volume through gesture

Documentación final del proyecto PointCloudLM

Hand tracking application developed in Pytorch

Hand Detection using TFLite in Android. Uses Victor Dibia's model checkpoints.

Play different sounds with your hand, using the webcam.

A hand detector application built in Javascript using handTrack.js

Use your webcam to identify gestures and trigger any script

Control mouse without touching it!

In this project we will be using the live feed coming from the webcam to create a virtual mouse with complete functionalities.

A simple python program that detects hand and track it using support vector machine file

Learn everything around ML

Mechanical keyboard controlled by Oculus Quest Hand Tracking in VR.

This is Hand Tracking project using python by Spider Developer

This project aims to control the system volume and screen brightness using hand gestures. Use your left hand for brightness control and right hand for volume control. For detection of hand landmarks, mediapipe library is used.