Quickly add MediaPipe Pose Estimation and Detection to your React Native app. Enable powerful features in your app powered by the body or hand.
Examples for Websocket CAM app
Real-Time AI Gym Trainer: AI-powered real-time fitness coaching system using MediaPipe & OpenCV for pose estimation, rule-based biomechanical analysis for exercise tracking, and LLM-based feedback (Groq API) with voice coaching (gTTS), built with Streamlit-WebRTC and SQLite.
Multimodal mobile sensing framework and public sample dataset for environmental context understanding, including transportation mode, pose mode, motion mode, indoor–outdoor inference, and transition-zone ambiguity.
Real-Time AI Gym Trainer: AI-powered real-time fitness coaching system using MediaPipe & OpenCV for pose estimation, rule-based biomechanical analysis for exercise tracking, and LLM-based feedback (Groq API) with voice coaching (gTTS), built with Streamlit-WebRTC and SQLite.
This app is used for Human pose Detection with more advanced pose estimation models !
Enriching Diversity of Synthetic Images for Person Detection
Python3 library for estimating a human pose from an image using machine learning techniques.
Project developed as part of the Artificial Intelligence undergraduate program at FIAP, featuring an algorithm for detecting body ergonomics points.
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