Object Detection
ultralytics
Tibetan
yolo
yolo26
tibetan
document-layout-analysis
bounding-box
BDRC
Eval Results (legacy)
Instructions to use BDRC/Tibetan_Modern_Book_Layout_Detection_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use BDRC/Tibetan_Modern_Book_Layout_Detection_Model with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("BDRC/Tibetan_Modern_Book_Layout_Detection_Model") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b54299289abcf25f9c745c1f62dd5aa9293a44f21aa120a874ee4e95ebaa3ed
- Size of remote file:
- 44 MB
- SHA256:
- 684ce3b6aec562bb2785909bfbf79c9d456d898b7ff5991dee8f239db6148e25
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.