Pose Detection Using OpenCV and Media Pipe

Whether doing out at home or at a gym, users can follow the computer vision-based program recommended in this study report. The software estimates user-body landmarks using OpenCV and Media Pipe to compute body angles and other numerical data in real time and determine the best posture for each workout. If a user assumes the wrong posture, the application provides guidance on how to fix it; if a user assumes the right posture, the application provides guidance and increases the quantity of exercises. The model will give you visual feedback and shows you how to adjust your posture on the screen so we can do it more accurately. This helps people prevent from any injury while doing any wrong exercise. Basically, this model will work as an instructor for the user and maintain their posture according to the exercise and prevent injury. All things considered, pose estimation whether it is for posture detection, hand tracking, holistic tracking and many more are very useful tools which help to meet individuals to their fitness goals. The application is also used in healthcare like hand gesture tracking such as in grabbling exercise for tracking patients hand movement by providing real time feedback.