mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

🏆 WebRTC - SFU - Simple, Secure, Scalable Real-Time Video Conferences Up to 8k, compatible with all browsers and platforms.

Web Augmented Reality. Image Tracking, Face Tracking. Tensorflow.js

JS Expert Week 7.0 - 🙅🤏🏻 Controlling Streaming Platforms using Eye and Hand Detection 👁🖐

Unity plugin to run MediaPipe

A full-body keyboard using gestures to type through computer vision

Faking your webcam background under GNU/Linux, now supports background blurring, animated background, colour map effect, hologram effect and on-demand processing.

GPU Accelerated MediaPipe Plugin for TouchDesigner

An awesome list of TensorFlow Lite models, samples, tutorials, tools and learning resources.

This is a Computer vision package that makes its easy to run Image processing and AI functions. At the core it uses OpenCV and Mediapipe libraries.

Lazyeat｜手势隔空控制，比划就行！Lazyeat is a touch-free controller for use while eating! Don't want greasy hands while watching shows or browsing the web during meals? You can pause videos/full screen/switch videos just by gesturing to the camera!

XR Animator, AI-based Full Body Motion Capture and Extended Reality (XR) solution, powered by System Animator Online

realtime motion tracking in blender using mediapipe and rigify

TensorFlow Lite Samples on Unity

Virtual Video Device for Background Replacement with Deep Semantic Segmentation

Virtually controlling computer using hand-gestures and voice commands. Using MediaPipe, OpenCV Python.

Real-time portrait segmentation for mobile devices

MediaPipe(Python版)を用いて手の姿勢推定を行い、検出したキーポイントを用いて、簡易なMLPでハンドサインとフィンガージェスチャーを認識するサンプルプログラムです。（Estimate hand pose using MediaPipe(Python version). This is a sample program that recognizes hand signs and finger gestures with a simple MLP using the detected key points.）

Add filters (background blur, etc) to your webcam on Linux.