---
language:
- en
- fr
license: apache-2.0
tags:
- ocr
- onnx
- onnxtr
- table_structure
---

<p align="center">
<img src="https://github.com/felixdittrich92/OnnxTR/raw/main/docs/images/logo.jpg" width="40%">
</p>

**Optical Character Recognition made seamless & accessible to anyone, powered by Onnxruntime**

## Task: table_structure

https://github.com/felixdittrich92/OnnxTR

### Example usage:

```python
>>> from onnxtr.io import DocumentFile
>>> from onnxtr.models import ocr_predictor, from_hub

>>> img = DocumentFile.from_images(['<image_path>'])
>>> # Load your model from the hub
>>> model = from_hub('onnxtr/my-model')

>>> # Pass it to the predictor
>>> # If your model is a recognition model:
>>> predictor = ocr_predictor(det_arch='db_mobilenet_v3_large',
>>>                           reco_arch=model)

>>> # If your model is a detection model:
>>> predictor = ocr_predictor(det_arch=model,
>>>                           reco_arch='crnn_mobilenet_v3_small')

>>> # Get your predictions
>>> res = predictor(img)
```

### Layout / table structure models

```python
>>> from onnxtr.models import from_hub, layout_predictor, table_predictor

>>> model = from_hub('onnxtr/my-model')
>>> # If your model is a layout model:
>>> predictor = layout_predictor(arch=model)
>>> # If your model is a table structure model:
>>> predictor = table_predictor(arch=model)
```