Datasets:
Download README.md from researchgroup542/Table_Dataset: direct link, hf CLI and curl.
- Browser
- Download file 2.21 kB
-
https://huggingface.co/datasets/researchgroup542/Table_Dataset/resolve/main/README.md
- Command line
-
hf download hf://datasets/researchgroup542/Table_Dataset/README.md
-
curl -L -o README.md https://huggingface.co/datasets/researchgroup542/Table_Dataset/resolve/main/README.md
license: cc-by-4.0
task_categories:
- image-to-text
language:
- en
tags:
- table-structure-recognition
- table-recognition
- html
- document-understanding
pretty_name: CompTSRBench
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: id
dtype: string
- name: split
dtype: string
- name: pattern
dtype: int64
- name: image
dtype: image
- name: html
dtype: string
splits:
- name: train
num_examples: 8000
- name: test
num_examples: 2000
CompTSRBench
CompTSRBench is a benchmark of 10,000 structurally complex synthetic tables for table structure recognition (image → HTML). Each table pairs a rendered image with its ground-truth HTML. The tables cover 25 canonical structural patterns (hierarchical headers, row and column spans, gridless regions and more) across application domains such as finance, science, education and healthcare.
| Split | Tables |
|---|---|
| train | 8,000 |
| test | 2,000 |
Every pattern appears in both splits, with at least 40 test tables per pattern.
Fields
| Field | Type | Description |
|---|---|---|
id |
string | Table identifier |
split |
string | train or test |
pattern |
int | Canonical structural pattern (1–25) |
image |
image | Rendered table image |
html |
string | Ground-truth table HTML (minified, no styling); headers are marked with <th> |
Structural statistics (all 10K tables)
- 81.4% contain column spans, 89.5% row spans, 58.4% multi-level headers
- On average 17.3 merged cells per table
Usage
from datasets import load_dataset
ds = load_dataset("researchgroup542/Table_Dataset")
example = ds["test"][0]
example["image"] # PIL image
example["html"] # ground-truth HTML
Evaluation
We report TEDS, TEDS-Struct and the Triple Metric Score (TMS), a structure-first metric that checks each cell's position, header context and content in that order. See the paper for details.
License
CC BY 4.0. All table content is synthetically generated and does not refer to real individuals or organizations.