GUVI_HACAKTHON

HACKACTHON_BY_THE _HCL_GUVI

🌱 Plant Disease Detector

This project is a Flask web app that predicts whether a plant leaf is Healthy or has Leaf Blight, and provides remedies for the detected condition.

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🚀 Features

• Upload a plant leaf image.
• Deep learning model predicts health status.
• Shows remedies for plant diseases from a JSON file.
• Clean UI using Flask templates.

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📂 Project Structure

plant-disease-detector/
│── app.py               # Main Flask app
│── test_image.py        # Image preprocessing test script
│── Requirements.txt     # Dependencies
│── README.md            # Documentation
│
│── model/
│   └── model.h5         # Pre-trained model (not included in repo)
│
│── data/
│   └── remedies.json    # Remedies info in JSON format
│
│── templates/
│   ├── index.html       # Upload form
│   └── result.html      # Result display
│
└── static/              # Stores uploaded images

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⚙️ Installation & Setup

1. Clone this repo:

   git clone https://github.com/your-username/plant-disease-detector.git
   cd plant-disease-detector

2. Create virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate   # Mac/Linux
   venv\Scripts\activate      # Windows

3. Install dependencies:

   pip install -r Requirements.txt

4. Add the trained model:

   • Place model.h5 inside the model/ directory.
   • Place remedies.json inside the data/ directory.

5. Run the Flask app:

   python app.py

6. Open your browser and go to:

   http://127.0.0.1:5000/
   

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🧪 Testing Image Preprocessing

Run:

python test_image.py

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📌 Notes

• Update the labels inside app.py if you add more classes.
• Make sure remedies.json contains mappings like:

{
  "Healthy": "No action needed.",
  "Leaf Blight": "Apply fungicide spray and remove infected leaves."
}

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👨‍💻 Author

Developed with BY using Flask + TensorFlow