Instructions to use Samdutse/pothole-yolov8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Samdutse/pothole-yolov8 with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("Samdutse/pothole-yolov8") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Pothole Detector (YOLOv8)
Fine-tuned yolov8s.pt on the Smartathon pothole dataset (Roboflow Universe) for road pothole detection.
- mAP50: 0.816
- mAP50-95: 0.518
Usage
from ultralytics import YOLO
from huggingface_hub import hf_hub_download
weights_path = hf_hub_download(repo_id="samdutse/pothole-yolov8", filename="best.pt")
model = YOLO(weights_path)
results = model.predict("road.jpg")
- Downloads last month
- 52