In this liveProject, you’ll test the functionality of a TensforFlow.js based fitness assistant and assess its capabilities of pose estimation for workout sessions. You’ll move data from a PoseNet model to a TensorFlow.js inference function that can recognize a workout type and add delays to prevent unnecessary logging duplication. You’ll then utilize TensorFlow.js’s prediction functionalities to get prediction results for your recognized workouts, pick top scores, and return the recognized workout type. Finally, you’ll use Material UI and React.JS to display a complete workout history to the user.
This project is designed for learning purposes and is not a complete, production-ready application or solution.