Soxavin/ardb-layout-coco-v2

ARDB Daily Bulletin Layout Detection (COCO)

A document-layout object-detection dataset built from ARDB (Agricultural and Rural Development Bank of Cambodia) daily market-price bulletins — born-digital Khmer-language PDFs, one price table per page. Every page is annotated with bounding boxes for five layout regions (table, text, section header, page furniture, picture).

Each row is a full page image rendered at 200 DPI (2000 × 2000 px, JPG) with its box annotations embedded, so the Dataset Viewer shows the image beside its labels.

Dataset structure

Split	Pages	Boxes	Source documents
train	73	341	24 bulletins
validation	9	42	3 bulletins
test	9	42	3 bulletins
total	91	425	30 bulletins

Fields

Column	Type	Description
image	image	Embedded page image (JPG, 2000 × 2000).
image_id	int64	Row index within the split.
file_name	string	Source image file name.
doc_id	string	Identifier of the originating bulletin.
source	string	Originating PDF (provenance).
width	int64	Image width in pixels.
height	int64	Image height in pixels.
objects	struct of lists	Per-box annotations (see below).

objects is a struct of parallel lists carrying the full COCO annotation fields:

• id — annotation id
• bbox — [x, y, width, height] in pixels (COCO convention)
• category_id — class index (0–4, see below)
• category — human-readable class name
• area — box area in px²
• iscrowd — always 0
• score — annotation confidence (1.0, human-verified)

Classes

id	name	Boxes	Notes
0	Table	91	The price table — exactly one per page, covering the full table including header row and label columns.
1	Text	30	Body / paragraph text.
2	Section-Header	31	Headings and titles.
3	Page-Furniture	182	Page headers and footers.
4	Picture	91	Logos and stamps.

Usage

from datasets import load_dataset

ds = load_dataset("Soxavin/ardb-layout-coco-v2")   # splits: train / validation / test
row = ds["train"][0]
row["image"]          # PIL image
row["objects"]["bbox"]        # list of [x, y, w, h]
row["objects"]["category"]    # list of class names

Data collection & annotation

1. Source. Publicly published ARDB daily market-price bulletins, rendered page-by-page at 200 DPI.
2. Pre-annotation. Candidate boxes were generated automatically with a document-layout detector and confidence-filtered, then mapped to the five-class set above.
3. Human correction. Every page was reviewed and corrected in Roboflow: fragmented table regions merged to one box per page, box edges tightened, mislabels fixed, and spurious boxes removed. All final annotations carry score = 1.0.
4. Splitting. Splits are assigned by document (no bulletin's pages appear in more than one split) to prevent near-duplicate-page leakage. Assignment is deterministic.

Limitations

• Single template. All bulletins share one recurring page layout, so the validation and test splits measure annotation quality rather than generalization across document designs.
• Small scale. 91 pages / 30 documents; suitable for fine-tuning and evaluation on this document family, not as a general-purpose layout corpus.

License

The annotations in this dataset (bounding boxes, class labels, and metadata) are released under CC BY-NC 4.0 — free to use for non-commercial research with attribution. The page images are reproductions of bulletins published by ARDB; they are included for research use only, and users are responsible for complying with the source documents' terms. This dataset is not affiliated with or endorsed by ARDB.