ashetuasefa80-netizen/plant-disease-detection

Plant Disease Detection System - Madda Walabu University # 🌿 Plant Disease Detection System **Madda Walabu University — College of Computing** **Department of Computer Science** **Course:** Artificial Intelligence Project **Author:** Morketa Negash (Ugrr/51983/15) **Instructor:** Shume. B --- ## 📋 Project Overview An end-to-end AI system that detects plant diseases from leaf images using a **Convolutional Neural Network (CNN)** trained on 16,000 images from the PlantVillage dataset. The model is deployed via a **Streamlit** web interface that provides instant diagnosis, confidence scores, and treatment recommendations. **Supported Crops:** Apple · Corn · Potato · Tomato **Total Disease Classes:** 21 (including healthy classes) --- ## 🗂️ Project Structure ``` Plant disease detection system/ │ ├── app.py ← Main Streamlit web application ├── requirements.txt ← Python dependencies ├── setup.bat ← One-click setup script (Windows) ├── run_app.bat ← Launch the web app ├── run_training.bat ← Start model training │ ├── model/ │ ├── train_model.py ← CNN training script (Chapter 4.4) │ ├── predictor.py ← Inference / prediction module │ ├── disease_info.py ← Disease database + treatment advice │ ├── plant_disease_cnn.h5 ← Saved model (created after training) │ └── class_names.json ← Class index map (created after training) │ ├── utils/ │ ├── download_dataset.py ← Kaggle dataset downloader │ ├── evaluate_model.py ← Metrics + confusion matrix (Table 4.1) │ └── demo_mode.py ← Simulated predictions for UI testing │ └── dataset/ ← PlantVillage images (you add this) ├── Apple___Apple_scab/ ├── Apple___healthy/ ├── Tomato___Late_blight/ └── ... ``` --- ## 🚀 Quick Start (Windows) ### Step 1 — Install & Setup Double-click **`setup.bat`** or run in CMD: ```cmd setup.bat ``` This creates a virtual environment and installs all dependencies …