Rafiki is a mobile application designed to assist farmers in identifying plant diseases and providing recommendations for appropriate agrochemicals. The app aims to empower farmers with information to enhance crop health and improve agricultural practices.
- Plant Disease Identification: Upload images of plants and receive real-time identification of diseases using machine learning.
- Agrochemical Recommendations: Get personalized recommendations for agrochemicals based on identified plant diseases.
- Educational Resources: Access educational content on plant diseases, prevention, and sustainable farming practices.
- User-Friendly Interface: Simple and intuitive interface for seamless user experience.
- Flutter: Frontend development for cross-platform mobile applications.
- Flask (Python): Backend development for handling image processing, machine learning model integration, and serving API requests.
- TensorFlow: Machine learning framework for plant disease identification.
- PIL (Pillow): Python Imaging Library for image processing.
- HTML/CSS: Frontend design and styling.