Deployed on: https://compulsory-gussie-fit-ai-1df0789c.koyeb.app/ (as of Feb 2025)

FitAI

Python lab project involving GenAI as well as classical ML algorithms for fitness related predictions.

Welcome to our Fitness Tracker and Predictor project! This project aims to help you track your fitness activities and predict future goals with ease. Whether you're a fitness enthusiast or just starting your journey towards a healthier lifestyle, our app has got you covered.

Features

• Activity Tracking: Keep track of your daily activities including steps taken, calories burned, and distance covered.
• Goal Setting: Set personalized fitness goals based on your current activity levels and desired outcomes.
• Predictive Analysis: Utilize machine learning algorithms to predict future fitness achievements and milestones.
• User-Friendly Interface: Enjoy a sleek and intuitive interface designed for seamless navigation and usage.
• CS50 Integration: Built using concepts learned in Harvard's CS50 course to ensure robustness and reliability.
• Flask Framework: Powered by Flask, a lightweight and efficient web framework for Python.
• Flask-Session: Store session variables securely to maintain user state across requests.
• Requests: Interact with external APIs to fetch data and enhance user experience.
• Cachelib: Implement caching mechanisms to optimize performance and reduce latency.
• Google Generative AI: Leverage cutting-edge AI technology for generating personalized fitness recommendations.
• Pillow: Perform image processing tasks such as resizing and cropping for enhanced visual appeal.
• Matplotlib: Generates visually appealing plots for smooth data visualisation.

Installation

1. Clone the repository:

   git clone https://github.com/soumyasavarn/FitAI.git
   

2. Install the dependencies

   pip install -r requirements.txt
   

3. Paste your Google API in genai.py (line 3)

4. Run the application:

   flask run
   

Getting Started

1. Register or login to your account.
2. Start tracking your activities by entering relevant data.
3. Set your fitness goals based on your preferences.
4. Explore the predictive analysis feature to get insights into your future achievements.
5. Share your progress with friends and stay motivated on your fitness journey!

Contributors:

Saptarshi Mukherjee

Ishan Chandra Gupta

Soumya Savarn