Banana Leaf Disease Detection using CNN

This project presents an automated system for detecting diseases in banana leaves using Convolutional Neural Networks (CNN) implemented on a Raspberry Pi platform. A camera connected to the Raspberry Pi captures images of banana leaves, which are then processed using a trained CNN model based on a curated dataset of healthy and diseased leaf images. The system analyzes the leaf images to accurately classify and identify various diseases, enabling early diagnosis and timely intervention. Results and disease status are displayed on an attached LCD screen, providing farmers with immediate, easy-to-understand feedback. This approach leverages deep learning and edge computing to offer a cost-effective, portable, and real-time solution for improving banana crop health and yield.