Tomato Leaf Disease Detection Using Deep Learning and Flask.

Tomato plants are vulnerable to various leaf diseases that reduce crop yield and quality. This project uses deep learning, specifically a Convolutional Neural Network (CNN), to detect and classify tomato leaf diseases accurately. A dataset containing images of healthy and diseased leaves is used for training and validation. The model is deployed via a Flask web application, enabling users to upload leaf images and receive instant diagnosis. This system provides an accessible and cost-effective tool for early disease detection. It aims to support farmers and improve tomato crop management efficiently.