Tomato Disease Prediction System In Python

It is an intelligent, web-based Tomato Leaf Disease Prediction System built in Python with Streamlit and integrated with SQL for history management. It helps farmers and users detect tomato plant diseases quickly and accurately using an image-based machine learning model.

With a simple and user-friendly interface, TomatoGuard not only predicts diseases but also stores historical results, provides detailed disease information, and generates graphical analysis for better crop monitoring.

🚀 Key Features & Modules:

✔ Register & Login Module – Secure authentication with farmer type, area type, and state details.
✔ Upload & Predict Disease – Upload tomato leaf images to get instant predictions with confidence scores.
✔ View Results – See detected disease names with clear outputs.
✔ History Management – Track all past predictions, images, and timestamps using SQL database.
✔ Disease Information – Learn symptoms, causes, prevention, and treatments of tomato leaf diseases.
✔ Graphical Analysis – Visualize your prediction history with interactive charts.
✔ Logout Module – Ensures secure session handling.

🛠️ Technical Details:

• Frontend: Streamlit (Python-based web framework)

• Backend: ML Model for image classification (deep learning-based)

• Database: SQL for storing users & prediction history

• Deployment: Easy to run locally

🎯 Why Choose TomatoGuard?

• Easy-to-use web-based interface

• Fast and accurate predictions with ML model

• Stores and manages user history for future analysis

• Provides disease insights & prevention methods

• Ready-to-use project with source code – ideal for academic submissions and practical applications

📦 Package Includes:

• Complete Source Code (Python + ML Model)

• Database file (SQL)

• Instructions for running with Streamlit👉 A perfect choice for students, researchers, and developers looking for an advanced Python machine learning project with Streamlit. Farmers can also benefit from accurate detection and better crop management.