🌿 LeafGuard

LeafGuard is an AI-powered mobile application designed to help users detect apple plant diseases using image classification. By leveraging machine learning and deep learning, the app provides accurate predictions along with confidence scores and recommended measures for apple plant health management. The supported diseases trained on are Apple Scab, Apple Black rot and Apple Cedar Rust.

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🚀 Features

• 📷 Image Upload: Users can upload or capture images of plant leaves for disease detection.
• 🤖 AI-Powered Predictions: Uses a trained deep learning model to identify plant diseases.
• 📊 Confidence Score: Displays the accuracy level of predictions.
• 💡 Recommended Measures: Provides actionable steps to manage and prevent plant diseases.
• 🎮 User-Friendly UI: Designed with an intuitive and modern interface using Flutter.

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🧑‍💻 Tech Stack

• Frontend: Flutter (Dart)
• Backend: FastAPI (Python)
• Machine Learning: TensorFlow h5 Model
• Artificial Intelligence: Google Gemini

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📸 Screenshots

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👥 Installation & Setup

Prerequisites

• Flutter SDK installed (Download Flutter)
• Python installed (Download Python)

Clone the Repository

git clone https://github.com/Dbriane208/LeafGuard.git
cd LeafGuard/leafguard

Install Dependencies

flutter pub get

Run the App

flutter run

For backend setup: To get the backend project follow this link

cd backend
pip install -r requirements.txt
uvicorn main:app --reload

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🔬 Model & API Integration

LeafGuard utilizes a deep learning model optimized for mobile using TensorFlow Lite. The backend API processes image uploads and returns predictions in JSON format:

{
  "predictedClass": "Apple Black Rot",
  "confidence": 0.99999,
  "symptoms": "Brown spots with yellow halos",
  "measures": "Use fungicides and remove affected leaves"
}

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📝 License

This project is licensed under the MIT License.

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🤝 Contributing

We welcome contributions! To contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-name).
3. Make your changes and commit (git commit -m 'Add new feature').
4. Push to the branch (git push origin feature-name).
5. Open a Pull Request.

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📩 Contact

For inquiries, reach out via email: 📧 db9755949@gmail.com

Or connect on LinkedIn: Daniel Brian Gatuhu

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🌟 If you like this project, don't forget to give it a star on GitHub! 🌟