Potato Disease Classification

This project implements a FastAPI-based web application for classifying potato plant diseases using deep learning. The application can identify three conditions:

• Potato Early Blight
• Potato Late Blight
• Healthy Potato Plant

Features

• Web interface for image upload
• Real-time disease classification
• REST API endpoint for predictions
• Docker support for easy deployment

Setup and Installation

Using Docker (Recommended)

1. Clone the repository:

git clone https://github.com/Atasatti/Potato_disease_Classification.git
cd Potato_disease_Classification

2. Build and run using Docker Compose:

docker-compose up --build

The application will be available at http://localhost:8000

Manual Setup

1. Create a virtual environment:

python -m venv env
source env/bin/activate  # On Windows: env\Scripts\activate

2. Install dependencies:

pip install -r requirements.txt

3. Run the application:

uvicorn main:app --host 0.0.0.0 --port 8000

API Endpoints

• GET /: Web interface
• POST /predict/: Upload an image for disease classification

Technologies Used

• FastAPI
• TensorFlow/Keras
• OpenCV
• Docker
• Python 3.10