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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.

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Rwanda Crop Doctor

Overview

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.

Project Structure

rwanda-crop-doctor/
├── backend/
│   ├── app/
│   ├── libs/
│   ├── venv/
│   └── requirements.txt
├── frontend/
│   ├── public/
│   ├── src/
│   └── libs/
├── .gitignore
├── setup_project_dependencies.sh
└── README.md
  • 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.

  • README.md: Project documentation.

Setup Instructions

Backend

  1. Create and activate a virtual environment:

    python3 -m venv backend/venv
    source backend/venv/bin/activate
  2. Install backend dependencies:

    pip install -r backend/requirements.txt
  3. Run the backend server:

    export FLASK_APP=backend/app
    flask run

Frontend

  1. Install frontend dependencies:

    cd frontend
    npm install
  2. Run the frontend development server:

    npm start

Dependencies

Backend

  • Flask
  • Flask-RESTful
  • Flask-CORS
  • Requests
  • SQLAlchemy
  • Blinker
  • Google Cloud Vision
  • Google Cloud Translate

Frontend

  • React
  • React-DOM
  • Bootstrap
  • React-Bootstrap

Contributing

We welcome contributions from the community! To contribute, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature or bug fix.
  3. Commit your changes.
  4. Push your branch and create a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

For any questions or suggestions, please contact us at agabaolivier85@gmail.com

About

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.

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