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---
license: mit
task_categories:
- table-question-answering
language:
- en
tags:
- OCR
- Tables
- IDP
size_categories:
- n<1K
---
This dataset is generated syhthetically to create tables with following characteristics:
1. Empty cell percentage in following range [40,70] (Sparse)
2. There is no seperator between rows and columns (un-structured).
3. 4 <= num rows <= 10, 2 <= num columns <= 6 (Small)
### Load the dataset
```python
import io
import pandas as pd
from PIL import Image
def bytes_to_image(self, image_bytes: bytes):
return Image.open(io.BytesIO(image_bytes))
def parse_annotations(self, annotations: str) -> pd.DataFrame:
return pd.read_json(StringIO(annotations), orient="records")
test_data = load_dataset('nanonets/small_sparse_unstructured_table', split='test')
data_point = test_data[0]
image, gt_table = (
bytes_to_image(data_point["images"]),
parse_annotations(data_point["annotation"]),
)
```
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