People struggle to stay fit due to our heavy schedules. There is a lack of resources in hand all in one place and a lack of guidance on fitness. When people speak of fitness, they only mention their physical appearance. However, you need a comprehensive guide to your physical fitness as well as overall holistic well-being. And Yoga is the way to achieve this, It brings together physical and mental disciplines to achieve a peaceful body and mind. AI can help in this domain but has not been fully implemented to a scale incorporating all these factors into one resource. And we are aiming to achieve this with the help of our Solution (AI Fitness Assistance)
Our projectelaborates numerous methodologies for the evaluation and detection of poses and utilizes various deep learning models for the classification of postures. FREAK effortlessly tracks the Yoga patterns by giving guidance while doing the exercise and focuses on all aspects of fitness which are a Healthy and nutritious diet, accurate knowledge of the fitness activities, body assessments, and more to the users, It then guides them towards their fitness destinations after processing information obtained. To give precise results, AI and machine learning solutions are connected to smartphones. FREAK seeks to refine the health and intelligence of its consumers.
As of today, the app contains 29 basic and intermediate yoga asanas. intends to differentiate the material according to the goals–such as flexibility, endurance, and muscular strengthening–as well as personal preferences, which will change depending on the mood. The software also analyses a person's speed and adapts itself, making it simpler for the user to fully adapt to yoga.
Freak uses the neural network, and classic computer vision algorithms, with a 95% accuracy of recognition of asanas, which includes a data set of more than a thousand images. This dataset acts as training for the neural network and therefore is the most important aspect of the app. These representative datasets are hard to create, particularly when it comes to finding several images of people in a particular pose. These images should contain different angles, and because different people in their ordinary lives have performed different yoga poses, it becomes difficult to sync them with the existing systems. Along with the representative dataset, another problem faced by the app is the visibility of the body. Now, if a person is standing near a window or bright light, it might be difficult for the camera to catch certain parts of the body or it might blend the body’s outline with a large object behind. So, while using Freak, it is not recommended to keep the camera against bright light or close to a window.
Now we are confident that Fitness exercises are very beneficial to personal health and fitness; however, they can also be ineffective and potentially dangerous if performed incorrectly by the user. Half knowledge is risky and Exercise mistakes are made due to the same reason when the user does not perform the proper form or pose. To overcome such a massive problem we introduce Pose Trainer, an application that detects the user's exercise pose and provides personalized, detailed recommendations on how the user can rectify their form.
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