Plant Leaf Disease Detection Using Machine Learning Algorithm

This project focuses on detecting plant leaf diseases using machine learning. Farmers often face crop loss due to diseases, and early detection can help prevent this. The system takes images of plant leaves, processes them to extract important features (like color and shape), and then uses a machine learning model to identify if the leaf is healthy or has a disease. We use algorithms like Support Vector Machine (SVM) or Convolutional Neural Network (CNN) to train the model with examples of diseased and healthy leaves. Once trained, the system can accurately predict the disease from a new leaf image. This tool can be used in mobile or web apps to help farmers quickly detect plant diseases and take action. It saves time, reduces manual work, and supports better crop health and production.