Tomato Leaf Disease Detection Using Deep Learning

Abstract: This project will build a machine learning solution for Detection of common diseases of tomatoes from a strong dataset of leaf photographs. We train deep models such as Convolutional from Kaggle. CNNs, MobileNet, and ResNet are employed for leaf condition classification. The system detects diseases such as Tomato Mosaic Virus, Target Spot, Early Blight, and Late Blight, Bacterial Spot and Septoria Leaf Spot with healthy leaves. The backend, Pythonbased, processes the user images and offers real-time Predictions. The frontend, which is built with HTML, CSS, and JavaScript, is intuitive. Interface that allows farmers and gardeners to monitor and diagnose easily tomato plant health, increasing crop management and yield.