metadata
license: apache-2.0
tags:
- object-detection
- road-damage
- yolo
- computer-vision
datasets:
- RDD2022
SABIQ — Road Damage Detection Model
Proactive road defect detection system.
Model Details
- Architecture: YOLO26m
- Base Model: yolo26m.pt (Ultralytics)
- Dataset: RDD2022 (Road Damage Detection 2022)
- Classes: crack, other, pothole
- mAP50: 0.636
- Epochs: 65
- Image Size: 640
- Training Hardware: NVIDIA A100
Validation Results
| Class | Images | Instances | Precision | Recall | mAP50 | mAP50-95 |
|---|---|---|---|---|---|---|
| all | 5758 | 9737 | 0.687 | 0.585 | 0.636 | 0.349 |
| crack | 3266 | 7209 | 0.714 | 0.520 | 0.605 | 0.321 |
| other | 1093 | 1563 | 0.714 | 0.745 | 0.792 | 0.493 |
| pothole | 544 | 965 | 0.635 | 0.491 | 0.512 | 0.233 |
Classes
| ID | Label | Description |
|---|---|---|
| 0 | crack | Longitudinal, transverse and alligator cracks |
| 1 | other | Other road corruption |
| 2 | pothole | Road potholes |