---
license: apache-2.0
---

# OCRFlux-pubtabnet-single
OCRFlux-pubtabnet-single is a benchmark of 9064 table images and their corresponding ground-truth HTML, which are derived from the public [PubTabNet](https://github.com/ibm-aur-nlp/PubTabNet) benchmark with some format transformations.

This dataset can be used to measure the performance of OCR systems in single-page table parsing.

Quick links:
- 🤗 [Model](https://huggingface.co/ChatDOC/OCRFlux-3B)
- 🛠️ [Code](https://github.com/chatdoc-com/OCRFlux)

## Data Mix

## Table 1: Tables breakdown by complexity (whether they contain rowspan or colspan cells)
| Complexity | Number |
|--------|-------------|
| Simple | 4623 |
| Complex | 4441 |
| **Total** | **9064** |


## Data Format

Each row in the dataset corresponds to a table image and its corresponding ground-truth HTML.

Different from the original PubTabNet dataset, we do not distinguish cells in the table headers and table bodies, which means there are no `<thead>` and `<tbody>` tags, and all `<th>` tags are replaced by `<td>` tags.

### Features:
```python
{
    'image_name': string,         # Name of the table image
    'type': string,         # "simple" or "complex"
    'gt_table': string,           # Ground-truth HTML of the table
}
```

## License
This dataset is licensed under Apache-2.0.