Leaf Disease Detection using Machine Learning

This project focuses on developing a machine learning model that can accurately detect and classify diseases in plant leaves based on image data. The aim is to provide an automated solution for farmers and agricultural professionals to quickly identify plant diseases, which can lead to timely intervention and improved crop yields.

Features Image Processing: Utilizes advanced image processing techniques to enhance and prepare leaf images for analysis. Deep Learning Model: Implements a convolutional neural network (CNN) to classify leaf diseases with high accuracy. Training and Evaluation: Provides scripts to train the model on custom datasets and evaluate its performance. Dataset Management: Includes tools to handle large datasets, with options for data augmentation to improve model robustness. User-Friendly Interface: A simple interface (could be CLI or GUI) for users to upload images and receive predictions. This application is designed to be a scalable and efficient tool for detecting various plant diseases, potentially helping to mitigate the spread of diseases and reduce agricultural losses.