ardb-layout-coco-v5 / README.md
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---
license: cc-by-nc-4.0
task_categories:
- object-detection
language:
- km
tags:
- document-layout
- khmer
- coco
- object-detection
pretty_name: ARDB Daily Bulletin Layout (COCO)
size_categories:
- n<1K
dataset_info:
features:
- name: image
dtype: image
- name: image_id
dtype: int64
- name: file_name
dtype: string
- name: doc_id
dtype: string
- name: source
dtype: string
- name: width
dtype: int64
- name: height
dtype: int64
- name: objects
struct:
- name: id
list: int64
- name: bbox
list:
list: float32
length: 4
- name: category_id
list: int64
- name: category
list: string
- name: area
list: float32
- name: iscrowd
list: int64
- name: score
list: float32
splits:
- name: train
num_bytes: 44962530
num_examples: 136
- name: validation
num_bytes: 2984508
num_examples: 9
- name: test
num_bytes: 7316400
num_examples: 21
download_size: 55251553
dataset_size: 55263438
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
# 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 with its box annotations embedded, so the Dataset Viewer shows
the image beside its labels.
The source corpus spans a multi-year range (2022–2026), covering both structural bulletin
templates in circulation over that period. Supersedes `ardb-layout-coco-v4` (same annotations;
that card documents the split-assignment issue this version fixes).
## Dataset structure
| Split | Pages | Boxes | Source documents |
|------------|------:|------:|------------------:|
| train | 136 | 636 | 45 bulletins (14 retail_only + 31 wholesale_retail) |
| validation | 9 | 42 | 3 bulletins (1 retail_only + 2 wholesale_retail) |
| test | 21 | 98 | 7 bulletins (1 retail_only + 6 wholesale_retail) |
| **total** | **166**| **776**| **55 bulletins** |
Splits are assigned by document, clustered by issue date (documents dated within 1 day of each
other are kept in the same split) and stratified by template era (each era's clusters are split
independently, then merged), so no bulletin's pages appear in more than one split, no near-
duplicate adjacent-day bulletin straddles a split boundary, and both structural templates are
represented in every split.
### Fields
| Column | Type | Description |
|-------------|-----------------|-------------|
| `image` | image | Embedded page image (JPG). |
| `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 (unique within its split; renumbered from v4 since pages moved
between splits — not semantically meaningful, no consumer reads it)
- `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 | Notes |
|----|------------------|------------------------------------------|
| 0 | `Table` | The price table — exactly one per page, covering the full table including header row and label columns. |
| 1 | `Text` | Body / paragraph text, including footer notes. |
| 2 | `Section-Header` | Headings and titles. |
| 3 | `Page-Furniture` | Page headers and footers (2 per page). |
| 4 | `Picture` | Logos and stamps (1 per page). |
## Usage
```python
from datasets import load_dataset
ds = load_dataset("Soxavin/ardb-layout-coco-v5") # 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 spanning 2022–2026,
rendered page-by-page at 200 DPI.
2. **Pre-annotation.** Candidate boxes were generated automatically with a document-layout
detector (Surya) 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, footer text unified under a single `Text` label, box
edges tightened, mislabels fixed, and spurious boxes removed. All final annotations carry
`score = 1.0`.
4. **Splitting.** Splits are assigned by document, clustered by issue date to avoid
adjacent-day near-duplicate leakage, and stratified by template era so both structural
templates are represented in every split. Assignment is deterministic.
## Limitations
- **Two structural templates.** The corpus spans two distinct bulletin layouts (a retail-only
6-column table pre-May 2024, and a combined wholesale/retail 9-column table from May 2024
onward). Both are represented in every split, though not in exactly proportional counts —
cluster integrity (no adjacent-day leakage) takes priority over exact proportionality.
- **Small scale.** 166 pages / 55 documents; suitable for fine-tuning and evaluation on this
document family, not as a general-purpose layout corpus.
- **Minority classes.** `Section-Header` and `Text` have substantially fewer boxes than the
other three classes, reflecting their genuine lower frequency per page (not every page has
a section header or footer text), rather than an annotation gap.
## 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.