{"id":24024637,"url":"https://github.com/adsh16/dish-nutrient-simplifier","last_synced_at":"2026-02-15T14:38:45.271Z","repository":{"id":268197043,"uuid":"903496947","full_name":"adsh16/dish-nutrient-simplifier","owner":"adsh16","description":"It provides a collection of ingredient from diverse cuisines worldwide including their enhanced profile (like gluten-free, raw, cooked). 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By leveraging a robust dataset from the USDA FoodData Central and integrating advanced algorithms, DishIT empowers users to analyze recipes, explore nutrient-dense ingredients, and optimize their dietary choices.\n\n## Features\n\n1. **Nutritional Data Collection**  \n   - A comprehensive dataset from USDA FoodData Central containing food descriptions and macronutrient profiles.  \n\n2. **Nutritional Analysis Engine**  \n   - Analyze the nutritional profile of recipes based on user inputs like protein, carbohydrate, and sugar requirements.\n\n3. **Ingredient Substitution Logic**  \n   - Suggest alternative ingredients that align with user dietary preferences or restrictions.\n\n4. **Interactive Web Interface**  \n   - Built with React.js for a dynamic and user-friendly experience.  \n\n5. **Recipe Improvement Suggestions**  \n   - Recommend ingredients or recipes to meet specific nutrient goals.\n\n## Technology Stack\n\n- **Frontend:** React.js (hosted on Vercel)  \n- **Backend:** Flask (hosted on Render)  \n- **Database:** CSV dataset preprocessed using Pandas and NumPy  \n\n## Methodology\n\n1. **Preprocessing and Cleaning**  \n   - Removed invalid entries, handled missing values, and standardized columns.  \n   - Extracted relevant macronutrient data (protein, carbohydrates, sugars).  \n\n2. **Nutritional Profile Analysis**  \n   - Identify top ingredients based on user-input nutrient requirements.  \n   - Dynamic search for nutrient-dense options.  \n\n3. **Ingredient Substitution**  \n   - Recommend alternatives considering nutritional equivalence and dietary restrictions.  \n\n4. **Frontend and Backend Integration**  \n   - API endpoints built with Flask serve nutritional data and handle ingredient recommendations.  \n   - React-bootstrap-typeahead enhances search functionality on the user interface.\n\n## How to Use\n\n1. Input your daily nutrient intake goals (e.g., protein, carbohydrates, sugars).  \n2. Explore ingredient suggestions tailored to your needs.  \n3. Get recipe improvement suggestions for healthier alternatives.  \n\n## Results\n\n- Accurate analysis of ingredient and recipe nutritional profiles.  \n- Personalized dietary recommendations for various dietary needs and preferences.  \n- A seamless, intuitive user experience bridging data-driven insights and culinary exploration.\n\n## Future Scope\n\n- Expand the dataset to include regional and rare ingredients.  \n- Integrate machine learning models for personalized recipe suggestions.  \n- Add dietary filters like vegan, gluten-free, or low-fat options.  \n- Develop a mobile application for wider accessibility.\n\n## Installation\n\n### Prerequisites\n- Node.js and npm\n- Python 3.x\n- Flask\n\n### Steps\n1. Clone this repository:  \n   ```bash\n   git clone https://github.com/yourusername/DishIT.git\n   ```\n2. Install frontend dependencies:  \n   ```bash\n   cd frontend\n   npm install\n   ```\n3. Install backend dependencies:  \n   ```bash\n   cd backend\n   pip install -r requirements.txt\n   ```\n4. Run the backend server:  \n   ```bash\n   python app.py\n   ```\n5. Run the frontend application:  \n   ```bash\n   cd frontend\n   npm start\n   ```\n\n## Contributors\n\n- **Aditya Sharma**  \n  - Preprocessing, Nutritional Analysis, Flask API Development, Deployment\n- **Akshat Raj Saxena**  \n  - Frontend Development, React Components, Implementing Algorithmic Logic \n- **Kanishk Kumar Meena**  \n  - Dataset Management, Algorithm Design, Testing, Frontend\n\n## References\n\n- [USDA FoodData Central](https://fdc.nal.usda.gov/)  \n- [Python Documentation](https://docs.python.org/3/)  \n- [React Bootstrap Typeahead](https://github.com/ericgio/react-bootstrap-typeahead)\n\n---\n\n### Hosted Application Links\n- **Frontend**: [Vercel](https://your-vercel-link.com)  \n- **Backend**: [Render](https://your-render-link.com)\n\n### License\nThis project is open source and available under the [MIT License](LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadsh16%2Fdish-nutrient-simplifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadsh16%2Fdish-nutrient-simplifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadsh16%2Fdish-nutrient-simplifier/lists"}