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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.
This repository contains an implementation of a deep learning approach for yoga pose classification using Convolutional Neural Networks (CNN) and MediaPipe for body keypoint detection. The project aims to classify various yoga poses with high accuracy and low latency, making it suitable for real-world applications.
This repository focuses on the Jeevit project, which offers users assistance with medical reports and dosage recommendations based on genetic data while also providing a personalized exercise trainer.
Yoga-Pose_Predict is a Flask web app for predicting yoga poses in images. It uses YOLO for keypoint detection and a custom PyTorch model for classification. Users can upload an image to view the predicted pose.
AsanaAi is not just another fitness app; it's a comprehensive tool designed to cater to various aspects of holistic health, ranging from yoga practice to cardiovascular workouts, and even mental well-being. It's a one stop solution for both Physical and Mental Health
Demo showcasing Federated Learning with Flower for yoga pose classification, enabling collaborative training across distributed datasets while preserving data privacy.
This project combines Flask, OpenCV, and MediaPipe to create a real-time yoga pose detection application! 🧘♀️📹 Using your webcam, it analyzes your yoga poses and provides real-time feedback, helping you perfect your practice. 🚀