nanonets/small_sparse_unstructured_table

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

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"]),
)