GutFood is a web application that provides food insights from images, including health risks, recipes, and ingredients. It leverages advanced technologies to offer a comprehensive food analysis platform.
- Image Analysis: Get detailed insights about food from uploaded images.
- Health Risk Assessment: Evaluate potential health risks associated with food items.
- Recipe Suggestions: Discover recipes based on analyzed food images.
- Ingredient Breakdown: Get a detailed list of ingredients for analyzed food items.
- Disease Prediction: Utilize custom ML models for disease prediction based on food habits.
- Interactive Chatbot: Engage with an AI-powered chatbot for additional food-related insights.
- Django
- Google Gemini for information retrieval
- Custom ML models (joblib and pickle) for disease prediction
- React
- Framer Motion
- Material-UI
- Tailwind CSS
- Shadcn UI
- Chart.js for data visualization
# Clone the repository
git clone https://github.com/your-username/gutfood.git
cd gutfood/backend
# Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
# Install dependencies
pip install -e .
# Run migrations
python manage.py migrate
# Start the Django server
python manage.py runserver# Navigate to the frontend directory
cd ../frontend
# Install dependencies
npm install
# Start the development server
npm run dev- Open your browser and navigate to
http://localhost:5173(or the port specified by Vite). - Upload a food image to get insights.
- Explore the various features like health risk assessment, recipe suggestions, and more.
- Interact with the chatbot for additional information.
Homepage of GutFood
Webapp main page
Dark mode if only
Food Image Analysis Results
This project is licensed under the MIT License - see the LICENSE file for details.