H-lamba/Plant-Disease-Detection-for-Sustainable-Development

Training an AI model from scratch for the plant disease detection # 🌱 Plant Disease Detection Model for Sustainable Agriculture ## 📌 Project Overview This project aims to detect plant diseases using Artificial Intelligence and Machine Learning techniques to help farmers make informed decisions and improve crop yield. Early detection of plant diseases is crucial to preventing the spread and minimizing losses. By leveraging a Convolutional Neural Network (CNN), this model classifies plant diseases based on leaf images and provides actionable insights for sustainable farming practices. **DropBox Link** : Plant Disease Detection Model ## 🚀 Features * 🌿 Image-Based Disease Detection using CNN * 📊 High Accuracy in identifying multiple plant diseases * 🌍 Sustainable Farming Support by reducing pesticide usage * 📲 Future Scope: Development of a mobile application for farmers * 📖 Table of Contents * Problem Statement * Methodology * Installation * Usage * Results * Future Improvements * Contributors ## 🔬 Problem Statement Plant diseases threaten global food security, and traditional disease detection methods are slow, expensive, and require expert knowledge. This project provides an automated system that enables farmers to detect diseases early and take preventive measures. ## ⚙️ Methodology **Data Collection**: Images of healthy and diseased plant leaves are gathered from public datasets and real-world sources. **Data Preprocessing**: Cleaning and augmenting data to improve model accuracy. **Model Development**: Training a CNN model to classify plant diseases. **Evaluation**: Testing the model’s performance on unseen data. **Recommendations**: Providing actionable insights for farmers. ## 🛠️ Installation **Prerequisites** * Python * TensorFlow/Keras * OpenCV * Jupyter Notebook * Setup ### Clone the repository: ``` git clone github.com cd plant-disease-detection ``` ### Install dependencies: ``` pip install - …