Nakabale001/BEAN_DISEASE_PREDICTION_IN_EAST-AFRICA
Domaine:
agriculturenatural language processingType de record:
softwaremodel
Créateur:
Nak
Hôte:
# Smart Bean Disease Prediction System
## Overview
The Smart Bean Disease Prediction System is an offline agricultural decision-support application developed using PHP, Python, TensorFlow Lite, SQLite, HTML, CSS, and JavaScript.
The system helps farmers identify bean leaf diseases by uploading an image of a bean leaf. After prediction, the system provides treatment recommendations, causes, and prevention measures in:
* English
* Luganda
* Kiswahili
The application works completely offline after installation.
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## Supported Diseases
The TensorFlow Lite model predicts the following classes:
| Class Index | Disease |
| ----------- | ------------------------ |
| 0 | Minor Angular Leaf Spot |
| 1 | Minor Bean Rust |
| 2 | Healthy |
| 3 | Severe Angular Leaf Spot |
| 4 | Severe Bean Rust |
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## Technologies Used
### Frontend
* HTML5
* CSS3
* JavaScript
### Backend
* PHP 8+
* Python 3.10+
### Machine Learning
* TensorFlow Lite
* NumPy
* Pillow
### Database
* SQLite
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## Project Structure
BeanDiseaseSystem/
├── assets/
│ ├── css/
│ │ └── style.css
│ ├── js/
│ │ └── script.js
│ └── images/
│ └── farm.jpg
├── languages/
│ ├── en.php
│ ├── lg.php
│ └── sw.php
├── uploads/
├── model/
│ └── bean_disease_model.tflite
├── python/
│ └── predict.py
├── database/
│ ├── create_database.php
│ └── bean_disease.db
├── index.php
├── predict.php
├── history.php
├── config.php
└── README.md
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## Installation
### Step 1: Install XAMPP
Install XAMPP and start:
* Apache
* MySQL (optional)
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### Step 2: Copy Project
Place the project inside:
htdocs/
Example:
C:\xampp\htdocs\BeanDiseaseSystem
---
### Step 3: Install Python Packages
Open Command Prompt:
pip in …