Sghaier04Mouhanned/ghana-crop-disease-detection

# Ghana Crop Disease Detection This project trains a YOLO model to detect crop diseases using object detection. It includes **training, inference, and CSV-to-YOLO format conversion** for further fine-tuning. ## 🚀 Features - YOLO-based crop disease detection - CUDA-accelerated inference - Outputs predictions as CSV (**filename, confidence, bounding boxes, class**) - Converts CSV results into **YOLO-supported annotation format** ## 📂 Directory Structure - `src/train.py` → Train YOLO model - `src/predict.py` → Run inference & save CSV - `src/csv_to_yolo.py` → Convert predictions CSV to YOLO annotation format - `configs/data.yaml` → Dataset paths & class names - `models/best.pt` → Trained YOLO model ## 🔧 Installation ```bash pip install -r requirements.txt