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
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README.md
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name: Recall
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---
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#
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A fine-tuned **YOLO26m** object-detection model for **Tibetan
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## Model Description
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```bibtex
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@dataset{bdrc_tdla_2025,
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title = {
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author = {Buddhist Digital Resource Center (BDRC)},
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year = {2025},
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url = {https://huggingface.co/
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license = {CC0-1.0}
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}
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```
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name: Recall
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---
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# TMBLD-YOLO26m — Tibetan Modern book layout dection
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A fine-tuned **YOLO26m** object-detection model for **Tibetan Modern book layout dection**. The model detects four layout classes in Tibetan modern book page images: **header**, **Text area**, **footnote**, and **footer**.
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## Model Description
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```bibtex
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@dataset{bdrc_tdla_2025,
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title = {Tibetan Modern book layout dection},
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author = {Buddhist Digital Resource Center (BDRC)},
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year = {2025},
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url = {https://huggingface.co/BDRC/Tibetan_Modern_Book_Layout_Detection_Model},
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license = {CC0-1.0}
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}
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```
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