Plant Disease Detection

Overview

The Plant Disease Detection project utilizes Convolutional Neural Networks (CNN) to identify diseases in plant leaves based on images. This deep learning model analyzes leaf images to detect potential diseases, providing an efficient solution for farmers, gardeners, and researchers to monitor plant health.

Features

• Classifies plant leaf images as healthy or diseased.
• Identifies the type of disease affecting the plant.
• Utilizes a Convolutional Neural Network (CNN) for image classification.

Prerequisites

• Python 3.x

Libraries:

• numpy
• pickle-mixin
• streamlit
• seaborn
• pandas
• matplotlib
• scikit_learn
• tensorflow
• keras
• opencv_python_headless

🚀 Running the Streamlit App

To run the Streamlit app from this repository, follow these steps:

1. Clone the repository:

git clone https://github.com/your-username/your-repo-name.git

cd your-repo-name

2. Install the required dependencies:

If you haven’t already, install the necessary Python packages by running:

pip install -r requirements.txt

3. Run the Streamlit App

To start the Streamlit app, run the following command:

streamlit run main.py

4. Open app in browser

Once the app is running, open your browser and go to:

http://localhost:8501

Now, you should be able to interact with the Streamlit app!