AI Room Recommendations is a web application that utilizes artificial intelligence to offer personalized decor and color palette suggestions based on uploaded room photos. This project integrates Flask as the backend framework and leverages AI models for image analysis and recommendation systems.
- Effortless Design Inspiration: Users can upload a photo of their room, and the AI analyzes it to suggest stunning color palettes and decor ideas.
- Personalized Recommendations: AI tailors suggestions to user style, preferences, and room characteristics.
- User-friendly Interface: Intuitive web interface designed with HTML, CSS, and JavaScript.
- Dynamic Updates: Recommendations are dynamically updated using AJAX, ensuring a seamless user experience.
- Secure User Authentication: Flask handles user authentication to manage sessions and access personalized recommendations securely.
- Backend: Python, Flask
- Frontend: HTML, CSS, JavaScript
- Database: SQLite (for development), PostgreSQL/MySQL (for production)
- Deployment: Heroku (cloud deployment), AWS/GCP (scalability)
AI Room Recommendations integrates advanced AI technologies to provide personalized decor and color palette suggestions:
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Gemini API: Utilizes Gemini's advanced image analysis capabilities to extract room features and generate detailed recommendations based on uploaded photos.
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Google Cloud Vision: Harnesses Google Cloud Vision for image recognition, allowing the AI to identify furniture, decor items, and color schemes within room photos.
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Dynamic Recommendations: Powered by TensorFlow, the AI dynamically updates and refines decor suggestions based on user preferences and room characteristics.