Instructions to use aurascoper/bacilli-yolov8n with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use aurascoper/bacilli-yolov8n with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("aurascoper/bacilli-yolov8n") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
bacilli-yolov8n
YOLOv8n detector for the Microscopy Bacilli Localization And Counting quest (Shipd.ai / Project Eris).
Single class bacillus, trained imgsz=640 on 1632x1224 stained fields (epoch-48, val mAP50 ~0.69).
Validated recipe: conf=0.25, iou(NMS)=0.45. Box encoding: normalized xyxy conf x_min y_min x_max y_max.
from huggingface_hub import hf_hub_download
w = hf_hub_download("aurascoper/bacilli-yolov8n", "best.pt")
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