In the sphere of fitness and exercise, the correct performing of exercises plays an important role in acquiring desired results and preventing injuries. A brief study of various Machine learning frameworks is mentioned below, which help us understand the inner workings of the various exercise tracking application models present currently. This research paper presents an application that avails this functionality using Python, providing real-time assistance for users to exercise. It will be done via displaying visual cues on the screen while the user is exercising. Integration of live web-cam or camera-enabled devices with the model, which captures the user’s movements and analyzes their postures in real-time to provide feedback. The purpose of the model is mainly to understand the working of Media pipe and OpenCV in practical and real-life problem statements, instead of just Object detection and pose estimation [1]. The paper contains technical implementation of the exercise model using Python code, including the process of capturing and processing video input, performing pose estimation and movement analysis and rendering interactive visual feedback to the user. The results demonstrate how basic Python-based applications can provide practical help for users in the domain of exercise and health. Further the future scope of the project has been discussed, the idea of its conversion into a mobile application, and to add voice assistance to the application to improve user experience.