Abstract
Abstract: With the growing demand in personalised fitness experiences, this paper takes a fresh look at home workouts by creating a Personalised Gym Trainer with the Mediapipe library. This sophisticated device combines pose detection technology with voice assistance to provide users with real-time feedback and personalised instruction while exercising. The system identifies various exercises accurately and leverages torso point detection for greater precision by leveraging the capabilities of the Mediapipe library and OpenCV for camera tasks. Individual Python modules for certain workouts such as pull-ups and bench press are written to support a flexible and scalable solution. Python, Git, GitHub, and Jenkins are among the tools and technologies used in the process. Furthermore, the Findpose library is used to calculate angles between torso locations, resulting in Providing a quantitative assessment of proper posture. The suggested Personalised Gym Trainer is a promising leap in home fitness solutions, integrating cutting-edge pose detection with voice assistance for an interactive and personalised workout experience.
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