The goal of the project is to improve fitness activities and encourage users to maintain their workout routines. This could be achieved through various means such as providing personalized workout plans, tracking progress, setting achievable goals, and offering rewards or incentives for reaching milestones. The aim is to make fitness more engaging and enjoyable for users, so they are more likely to stick with their routine and achieve their fitness goals.
The app features a user-friendly Human 2D Clickable Diagram. Users can easily select exercises and yoga poses by clicking on specific body parts, making it simple to customize their fitness routines and target specific muscle groups. The interactive diagram enhances accessibility and empowers users to create personalized workout regimens.
Integrated ML technology accurately detects users' exercise forms in real-time. It provides instant feedback on proper alignment, reducing the risk of injuries. The system also tracks reps and sets completed, enabling users to monitor progress and make informed adjustments to their training routine.
A voice assistant allows users to navigate the app through voice commands, providing a convenient and hands-free experience. Users can access different sections, select exercises, and gather information without manual interaction, ideal for users during workouts.
The virtual trainer feature delivers personalized voice feedback during workouts, providing guidance, instructions, and motivation. Users receive real-time support, ensuring proper form and technique, and maximizing their training results.
Using individual data, the app generates customized diet and exercise plans. Personalized recommendations for caloric intake, macronutrient distribution, and specific workouts help users optimize their fitness journey and achieve their goals effectively.
The community forum fosters social interaction, allowing users to connect, share experiences, ask questions, and receive advice from peers and experts. It promotes a supportive environment, providing users with inspiration, motivation, and valuable information for their fitness and wellness endeavours.
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Challenges we ran into TensorFlow Lite has scarce resources online and it was a major challenge to build a model that is fast for mobile applications. Integrating a model on React and Dekstop is easy as you don't have to look out for processing power constraints.
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In scrapping the data from the web and cleaning it for proper usage for the users. The data scraping was a challenge and deploying it on replit too, as this was my first time using replit and there are not a lot of resources to deploy Django on replit.
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Making an all round fitness app that encompasses all the areas whether it be exercise, yoga or diet was a major challenge to do in 24 hours.