---
title: PP-DocLayoutV3_onnx
canonical_url: "https://www.modelscope.cn/models/PaddlePaddle/PP-DocLayoutV3_onnx"
md_url: "https://www.modelscope.cn/models/PaddlePaddle/PP-DocLayoutV3_onnx.md"
repository: PaddlePaddle/PP-DocLayoutV3_onnx
last_updated: 2026-06-12
license: apache-2.0
base_model:
- PaddlePaddle/PP-DocLayoutV3
base_model_relation: finetune
library_name:
- onnx
language:
- en
- zh
- multilingual
downloads: 24401
stars: 4
tags:
- PaddleOCR
- PaddlePaddle
- image-segmentation
- ocr
- layout
- layout_detection
---
# PP-DocLayoutV3_onnx
> PP-DocLayoutV3_onnx - PaddlePaddle 在 ModelScope 开源的模型。Layout Analysis Module of PaddleOCR-VL-1.5
PaddlePaddle/PP-DocLayoutV3_onnx 是 ModelScope 魔搭社区上的机器学习模型，采用 apache-2.0 许可，基于 PaddlePaddle/PP-DocLayoutV3 构建。
- **Repository**: PaddlePaddle/PP-DocLayoutV3_onnx
- **License**: apache-2.0
- **Base model**: PaddlePaddle/PP-DocLayoutV3
- **Tags**: PaddleOCR, PaddlePaddle, image-segmentation, ocr, layout, layout_detection
- **Downloads**: 24401
- **Stars**: 4
- **Last updated**: 2026-06-12
Source: https://www.modelscope.cn/models/PaddlePaddle/PP-DocLayoutV3_onnx
---
Layout Analysis Module of PaddleOCR-VL-1.5
[](https://github.com/PaddlePaddle/PaddleOCR)
[](https://huggingface.co/PaddlePaddle/PP-DocLayoutV3)
[](https://modelscope.cn/models/PaddlePaddle/PP-DocLayoutV3)
[](https://huggingface.co/spaces/PaddlePaddle/PaddleOCR-VL-1.5_Online_Demo)
[](https://modelscope.cn/studios/PaddlePaddle/PaddleOCR-VL-1.5_Online_Demo/summary)
[](https://discord.gg/JPmZXDsEEK)
[](https://x.com/PaddlePaddle)
[](./LICENSE)
**🔥 [Official Website](https://www.paddleocr.com)** |
**📝 [Technical Report](https://arxiv.org/pdf/2601.21957)**
## Introduction
This is the model weights for PP-DocLayoutv3 in ONNX format. Get PaddlePaddle weights at [PP-DocLayoutV3](https://huggingface.co/PaddlePaddle/PP-DocLayoutV3)
**PP-DocLayoutV3 is specifically engineered to handle non-planar document images. It can directly predict multi-point bounding boxes for layout elements—as opposed to standard two-point boxes—and determine logical reading orders for skewed and curved surfaces within a single forward pass, significantly reducing cascading errors.** This model is an essential component of PaddleOCR-VL-1.5, providing crucial layout analysis for the high-precision parsing of various real-world documents in PaddleOCR-VL.
### **Model Architecture**
## Model Usage
### Install Dependencies
```shell
pip install -U paddleocr
pip install -U onnxruntime-gpu
```
### CLI Usage
```shell
paddleocr layout_detection -i ./demo.jpg --model_name PP-DocLayoutV3 --engine onnxruntime
```
### Python API Usage
```python
from paddleocr import LayoutDetection
model = LayoutDetection(
model_name="PP-DocLayoutV3",
engine="onnxruntime",
)
output = model.predict("./demo.jpg", batch_size=1)
for res in output:
res.print()
res.save_to_img(save_path="./output/")
res.save_to_json(save_path="./output/res.json")
```
## Visualization
### Light Variation
### Skewing
### Screen-photo
### Curving
## Citation
If you find PP-DocLayoutV3 helpful, feel free to give us a star and citation.
```bibtex
@misc{cui2026paddleocrvl15multitask09bvlm,
title={PaddleOCR-VL-1.5: Towards a Multi-Task 0.9B VLM for Robust In-the-Wild Document Parsing},
author={Cheng Cui and Ting Sun and Suyin Liang and Tingquan Gao and Zelun Zhang and Jiaxuan Liu and Xueqing Wang and Changda Zhou and Hongen Liu and Manhui Lin and Yue Zhang and Yubo Zhang and Yi Liu and Dianhai Yu and Yanjun Ma},
year={2026},
eprint={2601.21957},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2601.21957},
}
```