{"id":30626442,"url":"https://github.com/shiva2806/fithub","last_synced_at":"2026-04-11T09:07:23.321Z","repository":{"id":311428312,"uuid":"1043790445","full_name":"Shiva2806/FitHub","owner":"Shiva2806","description":"FitHub is your personal AI fitness companion. 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FitHub: Your Personal AI Fitness Companion\n\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/Shiva2806/FitHub/main/client/src/assets/FitHub.png\" alt=\"FitHub Logo\" width=\"100\"/\u003e\n\u003c/div\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cstrong\u003eTransform your fitness journey with the power of AI.\u003c/strong\u003e 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.\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"#-key-features\"\u003eKey Features\u003c/a\u003e •\n  \u003ca href=\"#-ai-models--technology\"\u003eAI Models\u003c/a\u003e •\n  \u003ca href=\"#-tech-stack\"\u003eTech Stack\u003c/a\u003e •\n  \u003ca href=\"#-getting-started\"\u003eGetting Started\u003c/a\u003e •\n  \u003ca href=\"#-screenshots\"\u003eScreenshots\u003c/a\u003e\n\u003c/p\u003e\n\n---\n\n## ✨ Key Features\n\n- **Three Core AI Models**: Specialized modules for body type analysis, diet planning, and real-time workout training.\n- **User Authentication**: Secure user registration and login system to manage your personal dashboard and track progress.\n- **Interactive Dashboard**: A central hub to view your stats, access AI models, and get workout recommendations.\n- **Fully Responsive Design**: A sleek, modern, and dark-themed UI that looks great on any device, from mobile phones to desktops.\n\n---\n\n## 🤖 AI Models \u0026 Technology\n\nFitHub'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.\n\n### 1. AI Body Type Analyzer\n- **Purpose**: To classify a user's physique into one of the three main somatotypes: Ectomorph, Mesomorph, or Endomorph.\n- **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.\n- **Technology**: **Python**, **TensorFlow/Keras**, **OpenCV** for image preprocessing.\n\n### 2. AI Diet Planner\n- **Purpose**: To generate personalized meal plans based on user-provided data.\n- **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.\n- **Technology**: **Python**, **Scikit-learn**, **Pandas** for data manipulation.\n\n### 3. AI Workout Trainer\n- **Purpose**: To provide real-time feedback on exercise form during a workout session.\n- **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.\n- **Technology**: **Python**, **OpenCV**, **MediaPipe** for pose estimation.\n\n---\n\n## 🛠️ Tech Stack\n\nThis project is a full-stack application built with the MERN stack and other modern technologies.\n\n| Category                | Technology                                                                                                  |\n|-------------------------|-------------------------------------------------------------------------------------------------------------|\n| **Frontend** | **React**, **TypeScript**, **Vite**, **Tailwind CSS**, **Shadcn/UI** |\n| **Backend** | **Node.js**, **Express.js** |\n| **Database** | **MongoDB** with **Mongoose** |\n| **AI / Machine Learning** | **Python**, **TensorFlow**, **OpenCV**, **MediaPipe** |\n| **Auth** | **JSON Web Tokens (JWT)**, **bcrypt.js** for password hashing                                                 |\n| **Styling** | **Tailwind CSS**, **Lucide React** for icons                                                                |\n\n---\n\n## 🚀 Getting Started\n\nFollow these instructions to get a copy of the project up and running on your local machine for development and testing purposes.\n\n### Prerequisites\n\n- [Node.js](https://nodejs.org/) (v18.x or later)\n- [npm](https://www.npmjs.com/) (usually comes with Node.js)\n- [MongoDB](https://www.mongodb.com/try/download/community) installed and running locally.\n- [Python](https://www.python.org/downloads/) (v3.8 or later) with relevant ML libraries.\n\n### Installation \u0026 Setup\n\n1.  **Clone the repository:**\n    ```bash\n    git clone [https://github.com/Shiva2806/FitHub.git](https://github.com/Shiva2806/FitHub.git)\n    cd FitHub\n    ```\n\n2.  **Set up the Backend Server:**\n    - Navigate to the `server` directory:\n      ```bash\n      cd server\n      ```\n    - Install the dependencies:\n      ```bash\n      npm install\n      ```\n    - Create a `.env` file in the `server` directory and add your MongoDB connection string:\n      ```env\n      MONGODB_URI=mongodb://localhost:27017/fithub\n      JWT_SECRET=your_jwt_secret_key_here\n      ```\n    - Start the backend server:\n      ```bash\n      npm run dev\n      ```\n    Your backend should now be running on `http://localhost:5000`.\n\n3.  **Set up the Frontend Client:**\n    - Open a **new terminal** and navigate to the `client` directory:\n      ```bash\n      cd client\n      ```\n    - Install the dependencies:\n      ```bash\n      npm install\n      ```\n    - Start the frontend development server:\n      ```bash\n      npm run dev\n      ```\n    Your frontend should now be running on `http://localhost:3000` (or another port if 3000 is busy).\n\n4.  **You're all set!** Open your browser and navigate to the frontend URL to start using FitHub.\n\n---\n\n## 📸 Screenshots\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/Shiva2806/FitHub/main/client/src/assets/HomePage.png\" alt=\"Hero Section\" width=\"600\"/\u003e\n  \u003cem\u003eHomepage\u003c/em\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/Shiva2806/FitHub/main/client/src/assets/AiModels.png\" alt=\"AI Models\" width=\"600\"/\u003e\n  \u003cem\u003eAI Models Selection Page\u003c/em\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/Shiva2806/FitHub/main/client/src/assets/Dashboard.png\" alt=\"Dashboard\" width=\"600\"/\u003e\n  \u003cem\u003eUser Dashboard\u003c/em\u003e\n\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshiva2806%2Ffithub","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshiva2806%2Ffithub","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshiva2806%2Ffithub/lists"}