ModelAufgelistetExtern

Pothole Yolov8

Fine-tuned yolov8s.pt on the Smartathon pothole dataset (Roboflow Universe) for road pothole detection.

Quellehuggingface.co/Samdutse/pothole-yolov8/tree/80c43b9a2ef0f5c2aed48914041bac8191351e17

ArtOtherVersionRevision 80c43b9BBewertung

Modellquelle

Art: Other
Dateigröße: 21,5 MB
Version: vRevision 80c43b9
Aktualisiert: 16. Sept. 2026
Downloads: 268
Quelle: Hugging Face

Quellenbeschreibung

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")

Quellen

1 Quelle

Hugging FacePrimärVersion 80c43b9a2ef0f5c2aed48914041bac8191351e17

huggingface.co/Samdutse/pothole-yolov8/tree/80c43b9a2ef0f5c2aed48914041bac8191351e17

Verifiziert 1. Sept.

Modellartefakte

1 Artefakt

best.pt

pt · 21,5 MB · SHA-256 1067a09d37e4…4aa2 · Hugging Face

Herunterladen

Quellenauszüge

2 Auszüge

Readme1. Sept.huggingface.co/Samdutse/pothole-yolov8

--- tags: - yolov8 - object-detection - pothole-detection - ultralytics --- # 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 ```python 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") ```

Note1. Sept.huggingface.co/Samdutse/pothole-yolov8

Source context: 268 downloads · 1 likes · Pipeline object-detection · Library ultralytics · Repo Samdutse/pothole-yolov8