Instructions to use AlessandroFerrante/StreetSignSenseY12s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use AlessandroFerrante/StreetSignSenseY12s with ultralytics:
from ultralytics import YOLOvv12 model = YOLOvv12.from_pretrained("AlessandroFerrante/StreetSignSenseY12s") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 33e6f7aa7301b8f4b8831bb5cf7687b896861d6da0bb8fa7bfbf88fe48a74100
- Size of remote file:
- 553 kB
- SHA256:
- fc9caedf9c3c6fb80e55b0a375e4399b20ea40c2bc5ace74b96cff0743def437
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.