This repository contains a Streamlit web application for classifying plant diseases using deep learning models. The app allows users to upload an image of a plant leaf and select from multiple pre-trained models to classify the disease present in the leaf. Each pre-trained model was trained using transfer learning on the plant village dataset and an ensemble technique called differential evolution was used to combine the models to get a better prediction and also to make the predictions stable.
- Interactive Map: Displays locations on a map using Folium.
- Model Selection: Choose between EfficientNet, MobileNet, Inception, and Differential Evolution for classification.
- Image Upload: Upload a plant disease image for classification.
- Prediction Display: Shows the predicted class and confidence score.
- Clone the repository:
git clone https://github.com/Tobsky/Plant_disease_app.git
- Navigate to the project directory:
cd plant-disease-classification - Install the required packages:
pip install -r requirements.txt
- Run the Streamlit app:
streamlit run main.py
The following models are used in this app:
- EfficientNet
- MobileNet
- Inception
- Differential Evolution
Each model can be selected from the sidebar in the app for classification.
Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.
This project is licensed under the MIT License.