README.md

metadata

dataset_info:
  features:
    - name: filename
      dtype: string
    - name: split
      dtype: string
    - name: imgid
      dtype: int64
    - name: dataset
      dtype: string
    - name: cells
      list:
        list:
          - name: tokens
            sequence: string
          - name: bbox
            sequence: int64
    - name: otsl
      sequence: string
    - name: html
      sequence: string
    - name: html_restored
      sequence: string
    - name: cols
      dtype: int64
    - name: rows
      dtype: int64
    - name: html_len
      dtype: int64
    - name: otsl_len
      dtype: int64
    - name: image
      dtype: image
  splits:
    - name: train
      num_bytes: 12249491432.02
      num_examples: 388002
    - name: val
      num_bytes: 221045220.768
      num_examples: 6942
  download_size: 8864819995
  dataset_size: 12470536652.788

Dataset Card for PubTabNet_OTSL

Dataset Description

• Homepage: https://ds4sd.github.io
• Paper: https://arxiv.org/pdf/2305.03393

Dataset Summary

This dataset is a conversion of the original PubTabNet into the OTSL format presented in our paper "Optimized Table Tokenization for Table Structure Recognition". The dataset includes the original annotations amongst new additions.

Dataset Structure

• cells: origunal dataset cell groundtruth (content).
• otsl: new reduced table structure token format
• html: original dataset groundtruth HTML (structure).
• html_restored: generated HTML from OTSL.
• cols: grid column length.
• rows: grid row length.
• image: PIL image

Data Splits

The dataset provides three splits

• train
• val

Additional Information

Dataset Curators

The dataset is converted by the Deep Search team at IBM Research. You can contact us at [email protected].

Curators:

• Maksym Lysak, @ maxmnemonic
• Ahmed Nassar, @nassarofficial
• Christoph Auer, @cau-git
• Nikos Livathinos, @nikos-livathinos
• Peter Staar, @PeterStaar-IBM

Citation Information

@misc{lysak2023optimized,
      title={Optimized Table Tokenization for Table Structure Recognition}, 
      author={Maksym Lysak and Ahmed Nassar and Nikolaos Livathinos and Christoph Auer and Peter Staar},
      year={2023},
      eprint={2305.03393},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}```