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---
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.
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