README.md

metadata

license: other
task_categories:
  - image-to-text
tags:
  - table-recognition
  - table-structure-recognition
  - document-ai
  - ocr

Rebuilt Table Sources — OmniDocBench / CC-OCR / OCRBench-v2

1,635 table images with OTSL and HTML ground truth, covering the four sources of the merged benchmark whose tables had to be rebuilt from upstream annotations rather than read from a published image+html pair.

benchmark	rows	origin
omnidocbench16	665	OmniDocBench v1.6
omnidocbench15	512	OmniDocBench v1.5
ccocr	300	CC-OCR
ocrbenchv2	158	OCRBench-v2 table-parsing tasks with an explicit bbox
total	1,635

Provenance

OmniDocBench v1.5 / v1.6 — the releases ship page images plus a JSON whose table entries carry a poly and an html field. Every entry with category_type == "table" contributes one crop, taken with its poly plus a 10px margin so cell borders survive. Ground truth is the entry's own html; OTSL is derived from it. Note that opendatalab/OmniDocBench on Hugging Face publishes only the v1.5 JSON — v1.6 was built from the local copy.

CC-OCR — 300 tables, four subsets of 75: photo_chn, photo_eng, scan_chn, scan_eng. HTML ships with the release; OTSL is derived from it.

OCRBench-v2 — this is a general document-VQA benchmark, so most of it is unusable for table recognition. Of its 700 table parsing tasks, the ones that name an explicit region in the prompt ("... in the region [x1,y1,x2,y2] of the image", normalised to 0–1000) are the only ones with a croppable table — 158 of them, which is this set. The other 542 say "all tables in the image" and were left out.

Ground truth is the answers[0] field. 19 of the 158 rows are Markdown tables rather than HTML; for those the html column holds the source text verbatim and otsl was produced from it with a Markdown-aware converter.

Schema

column	type	meaning
bytes	binary	the cropped table image
source	string	original dataset name
benchmark	string	one of the four above
sample_id	string	upstream identifier
rows / cols	int64	table grid dimensions
otsl	string	OTSL ground truth
html	string	HTML ground truth
resolution	string	WIDTHxHEIGHT
width / height	int64	image dimensions
structure_only	bool	true when the table has no cell text at all

Scoring

TEDS = 1 - TD / max(N_pred, N_gt) over the table tree; TEDS-S is the structure-only variant. When structure_only is true every cell is empty and only the grid is annotated, so TEDS is not computed for those rows — only TEDS-S is.

Related

• CheneyWong/table_recognition_eval — the full merged benchmark, 184,074 tables across 17 sources
• Cheney20/paddleocr-vl-table-recognition — scoring code and GT converters

Citation

Please cite the original datasets. This repository only repackages them under a unified schema.