---
license: apache-2.0
library_name: libreyolo
pipeline_tag: object-detection
tags:
- libreyolo
- object-detection
- document-layout
- reading-order
- pp-doclayout
base_model:
- PaddlePaddle/PP-DocLayoutV3_safetensors
---

# LibrePPDocLayoutV3l

PP-DocLayoutV3 (HGNetV2-L backbone, RT-DETR-style decoder with
mask-enhanced queries and a global-pointer reading-order head) converted to the
LibreYOLO checkpoint format. It detects 25 document layout classes (text,
titles, tables, images, formulas, headers, footers, seals, ...) and ranks the
regions in reading order.

```python
from libreyolo import LibreYOLO

model = LibreYOLO("LibrePPDocLayoutV3l.pt")
r = model("page.png", conf=0.5)
for order, box, cls in zip(r.reading_order, r.boxes.xyxy, r.boxes.cls):
    print(int(order), r.names[int(cls)], box.tolist())
```

## Source

Derived from
[PaddlePaddle/PP-DocLayoutV3_safetensors](https://huggingface.co/PaddlePaddle/PP-DocLayoutV3_safetensors)
at revision `e4f489dc536556fc1be02b973ba06756e0d4a2ac` (`model.safetensors`),
released by the [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) project.
Copyright (c) PaddlePaddle Authors. Licensed under the Apache License 2.0.

## Modifications

State-dict key prefix removal (`model.`) and LibreYOLO v1.0 metadata only.
Learned parameters are unchanged. Class names follow the release's
`inference.yml` `label_list`. See `weights/convert_ppdoclayoutv3_weights.py` in
the [LibreYOLO source repository](https://github.com/LibreYOLO/libreyolo).
Raw head outputs (class logits, boxes, reading-order logits, masks) match the
reference PyTorch implementation bit for bit on identical inputs.

This file: `LibrePPDocLayoutV3l.pt`, SHA-256
`347f3f60e03a4ecc64184085709180b094df4c27345b3a97fd9ec1b4f78a1ef4`.

## License

Apache License 2.0. See the [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE)
files in this repository.