Cotton Plant Disease Detection

This repository contains a Flask web application that predicts diseases in cotton plants based on uploaded images using a pre-trained deep learning model. The model identifies the disease from a set of predefined classes and provides the corresponding disease name.

Features

• Upload cotton plant images for disease prediction.
• View the result with the predicted disease class and the uploaded image.
• Displays the prediction on a web page after processing the image.

Requirements

To run the project, you need to have the following installed:

• Python 3.x
• Flask
• TensorFlow (for loading the .h5 model)
• Keras
• PIL (Pillow for image handling)

You can install the necessary Python packages using pip:

pip install -r requirements.txt

Setup

1. Clone the repository and navigate to the project directory:

git clone "https://github.com/sonalisrisivani/cotton-plant-disease-detection"
cd cotton-plant-disease-detection

2. Install Virtual Environment Packages

python -m venv venv 

3. Activate Virtual Environment # For Windows

venv\Scripts\activate

4. Install dependencies

pip install -r requirements.txt

5. Run application

python app.py 

or

flask run 

Go to - localhost/5000

6. deactivate

deactivate

License

This project is licensed under the MIT License - see the LICENSE file for details.