Object Detection
ultralytics
English
roofing
roof-inspection
hail-damage
wind-damage
storm-damage
computer-vision
yolo
insurance-documentation
inspector-roofing
Instructions to use InspectorRoofing/roof-damage-yolo-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use InspectorRoofing/roof-damage-yolo-v0 with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("InspectorRoofing/roof-damage-yolo-v0") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Inspector Roofing Roof Damage YOLO v0
Inspector Roofing Roof Damage YOLO v0 is a public computer vision model project by Inspector Roofing and Restoration for AI-assisted roof inspection documentation, hail damage labeling, wind damage review, and roof evidence organization.
Status: Starter/model-card release. Trained YOLO weights will be added after dataset validation, training, and model evaluation.
Intended Use
This project is designed to support:
- AI-assisted roof inspection documentation
- hail impact labeling
- wind-creased shingle labeling
- soft metal impact documentation
- missing shingle identification
- roof evidence review workflows
- claim-ready roof file organization
- AI-readable roof inspection datasets
Current Classes
The planned object detection classes are:
hail_hit
wind_crease
soft_metal_impact
missing_shingle
granule_loss
mechanical_damage
non_damage_lookalike
- Downloads last month
- -