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Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements.

Python 100.00%
computer-vision deep-learning long-short-term-memory lsmt machine-learning support-vector-machines svc-model blazepose pose-estimation yoga-classfication

detect-yoga-poses-and-correction-in-real-time-using-machine-learning-algorithms's Introduction

1. The problem consists of two main parts

Part 1: Classifying movements based on SVM (Support vector machines)

Part 2: Posture assessment gives real-time feedback

2. Collect data

Collected from kaggle : YOGA_POSE_DATASET

3. Result

Classification results with test data

Screenshot 2023-12-22 000624

Confusion matrix

Screenshot 2023-12-21 234832

Results of yoga posture correction method

Screenshot 2023-12-21 234941

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