README.md

metadata

license: mit
task_categories:
  - table-question-answering
language:
  - en
tags:
  - IDP
  - Tables
  - OCR
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 clear seperator between rows and columns (Structured).
3. 15 <= num rows <= 30, 7 <= num columns <= 15 (Long)

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/long_sparse_structured_table', split='test')
data_point = test_data[0]
image, gt_table = (
    bytes_to_image(data_point["images"]),
    parse_annotations(data_point["annotation"]),
)