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---
dataset_info:
features:
- name: image
dtype: image
- name: bboxes
sequence:
sequence: float64
- name: category_id
sequence: int64
- name: segmentation
sequence:
sequence:
sequence: float64
- name: area
sequence: float64
- name: pdf_cells
list:
list:
- name: bbox
sequence: float64
- name: font
struct:
- name: color
sequence: int64
- name: name
dtype: string
- name: size
dtype: float64
- name: text
dtype: string
- name: metadata
struct:
- name: coco_height
dtype: int64
- name: coco_width
dtype: int64
- name: collection
dtype: string
- name: doc_category
dtype: string
- name: image_id
dtype: int64
- name: num_pages
dtype: int64
- name: original_filename
dtype: string
- name: original_height
dtype: float64
- name: original_width
dtype: float64
- name: page_hash
dtype: string
- name: page_no
dtype: int64
- name: pdf
dtype: binary
- name: modalities
sequence: string
splits:
- name: train
num_bytes: 35626146180.25
num_examples: 69375
- name: validation
num_bytes: 3090589267.941
num_examples: 6489
- name: test
num_bytes: 2529339432.131
num_examples: 4999
download_size: 39770621829
dataset_size: 41246074880.322
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
# Dataset Card for Docling-DocLayNet dataset
## Dataset Description
- **Homepage:** https://developer.ibm.com/exchanges/data/all/doclaynet/
- **Repository:** https://github.com/DS4SD/DocLayNet
- **Paper:** https://doi.org/10.1145/3534678.3539043
### Dataset Summary
This dataset is an extention of the [original DocLayNet dataset](https://github.com/DS4SD/DocLayNet) which embeds the PDF files of the document images inside a binary column.
DocLayNet provides page-by-page layout segmentation ground-truth using bounding-boxes for 11 distinct class labels on 80863 unique pages from 6 document categories. It provides several unique features compared to related work such as PubLayNet or DocBank:
1. *Human Annotation*: DocLayNet is hand-annotated by well-trained experts, providing a gold-standard in layout segmentation through human recognition and interpretation of each page layout
2. *Large layout variability*: DocLayNet includes diverse and complex layouts from a large variety of public sources in Finance, Science, Patents, Tenders, Law texts and Manuals
3. *Detailed label set*: DocLayNet defines 11 class labels to distinguish layout features in high detail.
4. *Redundant annotations*: A fraction of the pages in DocLayNet are double- or triple-annotated, allowing to estimate annotation uncertainty and an upper-bound of achievable prediction accuracy with ML models
5. *Pre-defined train- test- and validation-sets*: DocLayNet provides fixed sets for each to ensure proportional representation of the class-labels and avoid leakage of unique layout styles across the sets.
## Dataset Structure
### Data Fields
* image: PIL image of all pages, resized to square 1025 x 1025px.
* bboxes: Bounding-box annotations in COCO format for each PNG image.
* category_id: integer representations of the segmentation labels (see below).
* segmentation:
* area:
* pdf_cells:
* metadata:
* pdf: Binary blob with the original PDF image.
This is the mapping between the labels and the `category_id`:
```
1: "caption"
2: "footnote"
3: "formula"
4: "list_item"
5: "page_footer"
6: "page_header"
7: "picture"
8: "section_header"
9: "table"
10: "text"
11: "title"
```
The COCO image record are defined like this example
```js
...
{
"id": 1,
"width": 1025,
"height": 1025,
"file_name": "132a855ee8b23533d8ae69af0049c038171a06ddfcac892c3c6d7e6b4091c642.png",
// Custom fields:
"doc_category": "financial_reports" // high-level document category
"collection": "ann_reports_00_04_fancy", // sub-collection name
"doc_name": "NASDAQ_FFIN_2002.pdf", // original document filename
"page_no": 9, // page number in original document
"precedence": 0, // Annotation order, non-zero in case of redundant double- or triple-annotation
},
...
```
The `doc_category` field uses one of the following constants:
```
financial_reports,
scientific_articles,
laws_and_regulations,
government_tenders,
manuals,
patents
```
### Data Splits
The dataset provides three splits
- `train`
- `val`
- `test`
## Additional Information
### Citation Information
"DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis" (KDD 2022).
Birgit Pfitzmann ([email protected])
Christoph Auer ([email protected])
Michele Dolfi ([email protected])
Ahmed Nassar ([email protected])
Peter Staar ([email protected])
ArXiv link: https://arxiv.org/abs/2206.01062
```bib
@article{doclaynet2022,
title = {DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis},
doi = {10.1145/3534678.353904},
url = {https://arxiv.org/abs/2206.01062},
author = {Pfitzmann, Birgit and Auer, Christoph and Dolfi, Michele and Nassar, Ahmed S and Staar, Peter W J},
year = {2022}
}
``` |