Image Segmentation
ultralytics
TensorBoard
PyTorch
v8
ultralyticsplus
yolov8
yolo
vision
awesome-yolov8-models
Eval Results (legacy)
Instructions to use keremberke/yolov8s-pothole-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use keremberke/yolov8s-pothole-segmentation with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("keremberke/yolov8s-pothole-segmentation") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e354edec6e28be90981c5272e89d2a5433d024f75f5f07f6257d915aa3b4f3f4
- Size of remote file:
- 465 kB
- SHA256:
- 041c7418e06eaeba6ba1939425de60af4334082b775c234deba5b4c4f7dae962
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