Yoga Pose Accuracy Detection By using deep learning
Updated 42 days ago
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Updated 42 days ago
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Growing popularity of yoga, as it is referred as a holistic approach to physical and mental well-being. However, many practitioners face challenges in achieving proper pose alignment and balance, which can hinder the full benefits of their yoga practice and may lead to injuries
Description
Developing an application using Mediapipe and Opencv that accurately detects, estimates, and assesses the accuracy of yoga poses in real-time video streams, empowering yoga practitioners with instant feedback, analysis to improve their yoga practice and achieve optimal pose alignment. Yog self-guidance frameworks convey the potential to make yoga famous along side ensuring it is acted in the correct way. Yoga pose accuracy detection by using deep learning helps people to practice yoga in more correct way, for taking live input in the form of video. Open-CV library is used along with Mediapipe which help to detect the accuracy of the taking input. Lightning AI link:LightningAI
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Siddhi Sonawane-Backend(python code with flask, dataset, mediapipe) Pratiksha Patil - Backend(python code with flask, OpenCV, CNN, LSTM) Vibhuti Patil - Frontend( HTML, css, mongodb connectivity, Intregration) Vaishnavi Gilbile - Frontend (HTML, CSS )
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