🧠 Body Fat Track AI

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🧾 Example: Input Form for Body Metrics

This image shows the simple and clean form where users can input key body metrics like weight, height, and waist size. The system uses this structured data to generate analysis and predictions.

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📊 Example: Progress Dashboard

After submitting their data, users get a visual summary of their body composition analysis, including charts and trends over time. The dashboard helps users track progress and stay motivated.

FatTrack_AI is an intelligent body composition tracker that helps users monitor their body fat percentage over time using AI-driven analysis — all through simple text input forms. No images required!

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🚀 Project Goal

• Track and analyze body fat percentage and muscle mass using user-provided data.
• Offer visual reports and progress tracking.
• Generate personalized recommendations based on input.
• Provide a clean, fast web experience using modern frontend and backend technologies.

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✨ Features

• 📝 Text-based input: Users enter their data (weight, height, Age, etc.) through a clean form.
• 📊 Dynamic dashboard: Visualize progress with charts and summaries.
• 🤖 AI-Powered advice: Receive smart suggestions tailored to your metrics.
• 🎨 Modern UI: Built with Tailwind CSS & JavaScript.
• 🐍 Python backend: Powered by Flask for fast processing.
• 🚀 Deployment-ready: Easy to run locally or deploy online.

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🛠️ Tech Stack

Layer	Tech
Frontend	HTML, JavaScript, Tailwind CSS
Backend	Python, Flask
Deployment	GitHub Actions (optional)

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📥 Installation & Run Instructions

🔗 Step 1: Clone the repository

git clone https://github.com/mohamedsherif301/FatTrack_AI.git
cd FatTrack_AI

📦 Step 2: (Optional but recommended) Create a virtual environment

python -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate

🔧 Step 3: Install all required dependencies

pip install -r requirements.txt

▶️ Step 4: Run the application

python app.py

🌐 Step 5: Open the app in your browser

Go to:

http://127.0.0.1:5000/

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