AI-Driven Plant Health Diagnostic App : Source code for a mobile app using AI to identify 38 plant diseases in crops like apples, tomatoes, and corn. Built with Flutter for both Android and more, it aims to enhance farming decisions and secure food supplies by applying cutting-edge AI in agriculture.
Below are screenshots of the LeafGuard application in action, showcasing its user-friendly interface and powerful features designed to help identify plant diseases effectively.
Our models of choice, MobileNetV2 and TensorFlow Lite, were selected for their lightweight architecture and efficient processing, which make them ideal for deployment on devices with limited resources while maintaining high accuracy.
The PlantVillage Dataset on Kaggle is an extensive collection of 54,306 images of healthy and diseased crop leaves across 38 classes, including various diseases affecting crops like Apple, Tomato, and Corn. It's designed for training machine learning models to detect and classify plant diseases effectively, helping to advance agricultural practices through AI. This dataset is essential for developers aiming to create tools that support farmers in early disease detection and management.
link: https://www.kaggle.com/datasets/abdallahalidev/plantvillage-dataset
LeafGuard Folder: Containes the flutter application folder
ModelApi Folder: Containes the api code using Flask
Notebook.ipynb: The Model's Notebook file