🌱 Plant Disease Prediction A deep learning web app to classify plant diseases from leaf images

📌 About

Plant Disease Prediction is a deep learning project that classifies plant diseases from leaf images, using convolutional neural networks and a deployable web interface.
Early detection of plant diseases is vital in agriculture — farmers worldwide lose significant yield each year due to disease spread. With this tool, users (farmers, agronomists, researchers) can upload a leaf image and instantly obtain a diagnosis, helping mitigate losses.

The model is trained on the PlantVillage dataset and wrapped in a Streamlit app for ease of use.

✨ Features

✅ User-facing

• Upload a leaf image (JPG/PNG) via web app → get disease prediction + confidence score
• Visualize training history (accuracy & loss plots)

🛠 Developer / Backend

• CNN-based model trained on the PlantVillage dataset (38 classes)
• Saved model (.h5) + class_indices.json for mapping
• Support for retraining / extending to new classes

📂 Project Structure Plant_disease_prediction/ │── app/ # Streamlit app files │── model_training_notebook/ # Jupyter notebooks for training │── test_images/ # Sample test images │── Plant-Model/ # Trained models & class indices │ ├── plant_disease_prediction_model.h5 │ ├── class_indices.json │ ├── model-training.py │── README.md │── LICENSE

🚀 Getting Started ✅ Prerequisites

Python 3.7+

TensorFlow / Keras

NumPy, Pandas

Matplotlib, Pillow

Streamlit

⚙️ Setup Instructions

Clone the repository:

git clone https://github.com/shraddhagreddy/Plant_disease_prediction.git cd Plant_disease_prediction

Install dependencies:

pip install -r requirements.txt

Download the PlantVillage Dataset and place it inside your working directory.

🏋️ Model Training

Run the training script:

python Plant-Model/model-training.py

This will:

Train the CNN on the dataset

Save the trained model as plant_disease_prediction_model.h5

Generate class_indices.json for mapping predictions

🌐 Running the Streamlit App

Run the web app with:

streamlit run app/app.py

Upload a leaf image (.jpg, .jpeg, .png)

Get instant disease predictions 🎉

📊 Example Results Training Performance

Model achieves ~92% validation accuracy (update after training).

Sample Prediction

Upload a leaf image → Prediction: Apple Scab 🍏🍂

🔮 Future Improvements

Add Grad-CAM visualizations for explainable AI

Deploy model to cloud (AWS/GCP/Heroku)

Improve accuracy with transfer learning (ResNet, EfficientNet)

Add mobile app integration for farmers

🛠 Tech Stack

Language: Python

Frameworks: TensorFlow, Keras, Streamlit

Data: PlantVillage Dataset

Libraries: NumPy, Pandas, Matplotlib, Pillow

👩‍💻 Author

Shraddha Reddy 📧 shraddhagreddy@gmail.com

💡 Always open to collaboration & feedback!

📜 License

This project is licensed under the MIT License © 2025 Shraddha Reddy. See the LICENSE file for details.