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. | |