https://github.com/shiva2806/fithub
FitHub is your personal AI fitness companion. This full-stack MERN project leverages a Python backend with TensorFlow & MediaPipe to offer AI body type analysis, personalized diet plans, and a workout trainer with real-time pose correction.
https://github.com/shiva2806/fithub
ai express machine-learning mediapipe mongodb nodejs opencv react tensorflow
Last synced: 3 months ago
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FitHub is your personal AI fitness companion. This full-stack MERN project leverages a Python backend with TensorFlow & MediaPipe to offer AI body type analysis, personalized diet plans, and a workout trainer with real-time pose correction.
- Host: GitHub
- URL: https://github.com/shiva2806/fithub
- Owner: Shiva2806
- Created: 2025-08-24T16:18:00.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-08-24T16:52:53.000Z (10 months ago)
- Last Synced: 2025-08-24T17:12:07.757Z (10 months ago)
- Topics: ai, express, machine-learning, mediapipe, mongodb, nodejs, opencv, react, tensorflow
- Language: TypeScript
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# FitHub: Your Personal AI Fitness Companion
Transform your fitness journey with the power of AI. FitHub is a modern, full-stack web application designed to provide personalized workout guidance, real-time pose correction, and intelligent nutrition planning, all tailored to your unique body type and goals.
Key Features •
AI Models •
Tech Stack •
Getting Started •
Screenshots
---
## ✨ Key Features
- **Three Core AI Models**: Specialized modules for body type analysis, diet planning, and real-time workout training.
- **User Authentication**: Secure user registration and login system to manage your personal dashboard and track progress.
- **Interactive Dashboard**: A central hub to view your stats, access AI models, and get workout recommendations.
- **Fully Responsive Design**: A sleek, modern, and dark-themed UI that looks great on any device, from mobile phones to desktops.
---
## 🤖 AI Models & Technology
FitHub's intelligence is powered by a suite of specialized machine learning models running on a Python backend. Each model is designed to tackle a specific aspect of your fitness journey.
### 1. AI Body Type Analyzer
- **Purpose**: To classify a user's physique into one of the three main somatotypes: Ectomorph, Mesomorph, or Endomorph.
- **How it Works**: The model is a **Convolutional Neural Network (CNN)** trained on a large dataset of body images. It analyzes a user-submitted photo to identify key physical features and predicts the most likely body type, providing a confidence score for its classification.
- **Technology**: **Python**, **TensorFlow/Keras**, **OpenCV** for image preprocessing.
### 2. AI Diet Planner
- **Purpose**: To generate personalized meal plans based on user-provided data.
- **How it Works**: This model uses a combination of rule-based algorithms and machine learning to create a diet plan. It considers the user's body type, BMI, fitness goals (e.g., weight loss, muscle gain), and dietary preferences to recommend meals that meet specific caloric and macronutrient targets.
- **Technology**: **Python**, **Scikit-learn**, **Pandas** for data manipulation.
### 3. AI Workout Trainer
- **Purpose**: To provide real-time feedback on exercise form during a workout session.
- **How it Works**: This feature utilizes a **real-time pose estimation model**. It processes the user's webcam feed to map out 33 key body landmarks (joints, limbs, etc.). By analyzing the angles and positions of these landmarks, it can determine if an exercise is being performed correctly and provide instant corrective feedback.
- **Technology**: **Python**, **OpenCV**, **MediaPipe** for pose estimation.
---
## 🛠️ Tech Stack
This project is a full-stack application built with the MERN stack and other modern technologies.
| Category | Technology |
|-------------------------|-------------------------------------------------------------------------------------------------------------|
| **Frontend** | **React**, **TypeScript**, **Vite**, **Tailwind CSS**, **Shadcn/UI** |
| **Backend** | **Node.js**, **Express.js** |
| **Database** | **MongoDB** with **Mongoose** |
| **AI / Machine Learning** | **Python**, **TensorFlow**, **OpenCV**, **MediaPipe** |
| **Auth** | **JSON Web Tokens (JWT)**, **bcrypt.js** for password hashing |
| **Styling** | **Tailwind CSS**, **Lucide React** for icons |
---
## 🚀 Getting Started
Follow these instructions to get a copy of the project up and running on your local machine for development and testing purposes.
### Prerequisites
- [Node.js](https://nodejs.org/) (v18.x or later)
- [npm](https://www.npmjs.com/) (usually comes with Node.js)
- [MongoDB](https://www.mongodb.com/try/download/community) installed and running locally.
- [Python](https://www.python.org/downloads/) (v3.8 or later) with relevant ML libraries.
### Installation & Setup
1. **Clone the repository:**
```bash
git clone [https://github.com/Shiva2806/FitHub.git](https://github.com/Shiva2806/FitHub.git)
cd FitHub
```
2. **Set up the Backend Server:**
- Navigate to the `server` directory:
```bash
cd server
```
- Install the dependencies:
```bash
npm install
```
- Create a `.env` file in the `server` directory and add your MongoDB connection string:
```env
MONGODB_URI=mongodb://localhost:27017/fithub
JWT_SECRET=your_jwt_secret_key_here
```
- Start the backend server:
```bash
npm run dev
```
Your backend should now be running on `http://localhost:5000`.
3. **Set up the Frontend Client:**
- Open a **new terminal** and navigate to the `client` directory:
```bash
cd client
```
- Install the dependencies:
```bash
npm install
```
- Start the frontend development server:
```bash
npm run dev
```
Your frontend should now be running on `http://localhost:3000` (or another port if 3000 is busy).
4. **You're all set!** Open your browser and navigate to the frontend URL to start using FitHub.
---
## 📸 Screenshots
Homepage
AI Models Selection Page
User Dashboard