Instructions to use lowunderabove/Ocean-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use lowunderabove/Ocean-router with ultralytics:
from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("lowunderabove/Ocean-router") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Ocean-router: Marine Image Routing Classifiers
Two-stage lightweight classifiers used to dynamically route marine images to specialized detectors based on image modality and content.
Model Files & Tasks
| File | Task | Architecture | Input/Output |
|---|---|---|---|
cls_bio_sonar/best.pt |
Sonar vs. Biological routing | YOLOv11-cls | Image → [sonar_prob, bio_prob] |
fish_coral_cls/best.pt |
Fish vs. Coral routing | YOLOv5 | Image → [fish_prob, coral_prob] |
Usage
1. Sonar/Biological Router
from ultralytics import YOLO
router = YOLO("cls_bio_sonar/best.pt")
results = router.predict("input.jpg")
2. Fish/Coral Classifier (YOLOv5)
Requires the official YOLOv5 repo
import torch
model = torch.hub.load("ultralytics/yolov5", "custom", path="fish_coral_cls/best.pt", force_reload=True)
results = model("input.jpg")
cls_bio_sonar decides if input is sonar or biological. If biological, fish_coral_cls routes to the appropriate species detector.
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