Yoga Posture Analysis and Feedback System Using Mediapipe
D. Snigdha, S. Tejasree, N. Rithvik, Hariharan Shanmuagasundaram, Siddharth Motikar, Siddharth Reddy · 2025
This project integrates Mediapipe with Python to implement a yoga posture analysis system for evaluating and providing efficacious feedback on human poses. The system establishes ideal joint landmarks using reference images, which are compared with uploaded analysis images over multiple simulated epochs. Angles of key joints, such as the elbow, shoulder, hip and knee are calculated and annotated onto the analyzed images for visual feedback. Deviations of analyzed images are identified and corrective suggestions are provided. Comprehensive graphs of accuracy and loss for each epoch are displayed to visualize the trends in accuracy and pose improvement. Accuracy reflects how well the model predicts the correct output, while loss indicates areas for improvement. In addition, for easy reference, all epoch data are tabulated to summarize overall performance, and a final model accuracy percentage is computed. The project also gives visual presentations of accuracy and loss over each epoch. The system serves as an effective tool for posture correction, making it suitable for fitness applications, physiotherapy, and ergonomic evaluations, with its detailed visual and numerical feedback.