shub-garg/Yoga-Pose-Classification-and-Skeletonization
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 project helps yoga instructors or fitness app developers accurately identify and classify various yoga poses from images. It takes raw images of someone performing a yoga pose as input and outputs the specific yoga pose detected. This is ideal for anyone looking to build or enhance systems that can automatically recognize yoga positions with high accuracy.
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Use this if you need a reliable way to automatically classify yoga poses from visual data, for applications like guided yoga sessions or pose correction.
Not ideal if you are looking for a fully-fledged, ready-to-deploy application rather than a foundational classification model.
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MIT
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Last pushed
Jul 24, 2024
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