Instructions to use Ashgibbs/Cosmetic_Defect_Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Ashgibbs/Cosmetic_Defect_Detection with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("Ashgibbs/Cosmetic_Defect_Detection") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- d4dfd437eae0ad4325816393d607bf84858efcb415298a41a43151a8042a746a
- Size of remote file:
- 107 kB
- SHA256:
- 4638bb227b74aa78c7b9ac936eb987de148156c6a942632dc13a5469674bb533
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.