Datasetpublic

Extend-AI/RealDoc-Bench-Layout

RealDocBench-Layout A 1,500-page document-layout benchmark for evaluating layout-detection models on real-world documents. COCO-style annotations across 9 block classes. Contents images/ — 1,500 page images (PNG / JPG / occasional WebP-as-PNG; see Caveats). annotations/<pageId>.json — per-page COCO files, each with a single image record, an annotations list, a categories list, and a page_info block. manifest.csv — pageId → domain + source URLs. The canonical row… See the full description on the dataset page: https://huggingface.co/datasets/Extend-AI/RealDoc-Bench-Layout.

sourceHugging Facecc-by-4.0updated 4mo agoView on Hugging Face

5likes430downloads

Dataset Card

RealDocBench-Layout

A 1,500-page document-layout benchmark for evaluating layout-detection models on real-world documents. COCO-style annotations across 9 block classes.

—images/ — 1,500 page images (PNG / JPG / occasional WebP-as-PNG; see Caveats).
—annotations/<pageId>.json — per-page COCO files, each with a single image record, an annotations list, a categories list, and a page_info block.
—manifest.csv — pageId → domain + source URLs. The canonical row list.

Block classes (9)

text, heading, section_heading, header, footer, page_number,
figure, table, key_value

class	what it covers
`text`	body text and other inline content
`heading`	document title
`section_heading`	section / subsection titles
`header`	running page header
`footer`	running page footer
`page_number`	page-number indicators
`figure`	images, diagrams, charts, barcodes, QR codes
`table`	tabular data
`key_value`	form fields / key-value pairs

The companion benchmark loader at `extend-hq/realdoc-bench` walks each annotation file and produces 9-class block predictions; see realdoc_bench/layout/normalizers/coco.py.

Loading

python

from huggingface_hub import snapshot_download
path = snapshot_download(repo_id="Extend-AI/RealDocBench-Layout", repo_type="dataset")

License

Annotations: CC-BY-4.0. Page images carry their original per-source licenses; the manifest's sourceUrl column points back to each one.

Takedown and Opt-out requests

If you are the owner of a document included in this dataset and would like it removed, you can submit a takedown request. We process requests on a monthly cadence and maintain a public manifest of removed records at takedowns/removed_ids.jsonl.

To request removal, open an issue in the Community tab or email [support@extend.ai] with:

A document identifier (filename, URL, or row ID if known), and the scope of removal (specific rows, an entire source document, or all documents from a given source)