Rwanda Crop Doctor is a comprehensive web application designed to assist farmers in diagnosing and managing crop diseases. The application leverages machine learning and cloud-based vision APIs to analyze crop images and provide actionable insights.
The frontend is built with React and Bootstrap, while the backend utilizes Flask and several other Python libraries.
rwanda-crop-doctor/
├── backend/
│ ├── app/
│ ├── libs/
│ ├── venv/
│ └── requirements.txt
├── frontend/
│ ├── public/
│ ├── src/
│ └── libs/
├── .gitignore
├── setup_project_dependencies.sh
└── README.md
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backend/: Contains the Flask application and its dependencies.
- app/: The main application code for the backend.
- libs/: Locally installed Python packages.
- venv/: Python virtual environment.
- requirements.txt: List of backend dependencies.
-
frontend/: Contains the React application and its dependencies.
- public/: Public assets for the frontend.
- src/: Source code for the React application.
- libs/: Locally downloaded frontend libraries.
-
setup_project_dependencies.sh: Script to set up project dependencies.
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README.md: Project documentation.
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Create and activate a virtual environment:
python3 -m venv backend/venv source backend/venv/bin/activate
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Install backend dependencies:
pip install -r backend/requirements.txt
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Run the backend server:
export FLASK_APP=backend/app flask run
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Install frontend dependencies:
cd frontend npm install
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Run the frontend development server:
npm start
- Flask
- Flask-RESTful
- Flask-CORS
- Requests
- SQLAlchemy
- Blinker
- Google Cloud Vision
- Google Cloud Translate
- React
- React-DOM
- Bootstrap
- React-Bootstrap
We welcome contributions from the community! To contribute, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Commit your changes.
- Push your branch and create a pull request.
This project is licensed under the MIT License. See the LICENSE file for more details.
For any questions or suggestions, please contact us at agabaolivier85@gmail.com