Overview
Automated detection and classification of 10 tomato leaf diseases from camera images, with a comprehensive comparison between YOLOv8s and YOLOv9s.
Results
| Model | Precision | Recall | F1-Score | Training Time |
|---|---|---|---|---|
| YOLOv8s | 89.50% | 90.10% | 89.80% | 77.11 min |
| YOLOv9s | 92.74% | 92.88% | 92.81% | 175.83 min |
- Dataset: 10,825 images augmented to 15,154 training images across 10 disease classes.
- YOLOv9s outperformed YOLOv8s across all metrics at the cost of ~2x training time.
Tech Stack: Python, YOLOv8, YOLOv9, Streamlit, OpenCV
Last updated on September 16, 2026 at 12:23 PM UTC+7. See Changelog