A self contained example demonstrating how to use Mediapipe Pose Landmarker with Max's `jweb`

🧘‍♂️🤖 Flask, OpenCV, and MediaPipe power this yoga project for real-time pose detection. Using a webcam feed, it dynamically classifies poses with MediaPipe, while Flask enables web deployment. OpenCV manages video streaming and image processing, creating an interactive platform for yoga enthusiasts to practice effectively.

Build an AI fitness counter and timer app with our end-to-end demo using QuickPose iOS SDK for Pose Estimation/Detection.

GymJam is an innovative AI gym assistant designed to revolutionize the fitness experience. Utilizing cutting-edge artificial intelligence technology, GymJam offers personalized guidance and support to users during their workouts.

Push-up-Counter-with-Python-Mediapipe

This project leverages OpenCV and Mediapipe for real-time pose detection, transforming a workout into a tech-driven exercise. Users perform 16 pullups on each arm, tracked by angle detection algorithms. The system visualizes angles and counts, enhancing engagement and accuracy in physical health routines.

Real-time Body Pose Estimation A Program That Detects With The Support Of Artificial Intelligence And Design

Demo showcasing Federated Learning with Flower for yoga pose classification, enabling collaborative training across distributed datasets while preserving data privacy.

This repository contains code for collecting pose data of various yoga poses using the MediaPipe Pose model. The collected data includes the angles of different body joints in each yoga pose.