|
--- |
|
annotations_creators: |
|
- crowdsourced |
|
license: other |
|
pretty_name: DocLayNet |
|
size_categories: |
|
- 10K<n<100K |
|
tags: |
|
- layout-segmentation |
|
- COCO |
|
- document-understanding |
|
- PDF |
|
task_categories: |
|
- object-detection |
|
- image-segmentation |
|
task_ids: |
|
- instance-segmentation |
|
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 |
|
splits: |
|
- name: train |
|
num_bytes: 28172005254.125 |
|
num_examples: 69375 |
|
- name: test |
|
num_bytes: 1996179229.125 |
|
num_examples: 4999 |
|
- name: val |
|
num_bytes: 2493896901.875 |
|
num_examples: 6489 |
|
download_size: 7766115331 |
|
dataset_size: 32662081385.125 |
|
--- |
|
|
|
# Dataset Card for DocLayNet v1.1 |
|
|
|
## Table of Contents |
|
- [Table of Contents](#table-of-contents) |
|
- [Dataset Description](#dataset-description) |
|
- [Dataset Summary](#dataset-summary) |
|
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
|
- [Dataset Structure](#dataset-structure) |
|
- [Data Fields](#data-fields) |
|
- [Data Splits](#data-splits) |
|
- [Dataset Creation](#dataset-creation) |
|
- [Annotations](#annotations) |
|
- [Additional Information](#additional-information) |
|
- [Dataset Curators](#dataset-curators) |
|
- [Licensing Information](#licensing-information) |
|
- [Citation Information](#citation-information) |
|
- [Contributions](#contributions) |
|
|
|
## 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 |
|
|
|
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 |
|
|
|
This dataset is structured differently from the other repository [ds4sd/DocLayNet](https://huggingface.co/datasets/ds4sd/DocLayNet), as this one includes the content (PDF cells) of the detections, and abandons the COCO format. |
|
|
|
* `image`: page PIL image. |
|
* `bboxes`: a list of layout bounding boxes. |
|
* `category_id`: a list of class ids corresponding to the bounding boxes. |
|
* `segmentation`: a list of layout segmentation polygons. |
|
* `pdf_cells`: a list of lists corresponding to `bbox`. Each list contains the PDF cells (content) inside the bbox. |
|
* `metadata`: page and document metadetails. |
|
|
|
Bounding boxes classes / categories: |
|
|
|
``` |
|
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 `["metadata"]["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` |
|
|
|
## Dataset Creation |
|
|
|
### Annotations |
|
|
|
#### Annotation process |
|
|
|
The labeling guideline used for training of the annotation experts are available at [DocLayNet_Labeling_Guide_Public.pdf](https://raw.githubusercontent.com/DS4SD/DocLayNet/main/assets/DocLayNet_Labeling_Guide_Public.pdf). |
|
|
|
|
|
#### Who are the annotators? |
|
|
|
Annotations are crowdsourced. |
|
|
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
The dataset is curated by the [Deep Search team](https://ds4sd.github.io/) at IBM Research. |
|
You can contact us at [deepsearch-core@zurich.ibm.com](mailto:deepsearch-core@zurich.ibm.com). |
|
|
|
Curators: |
|
- Christoph Auer, [@cau-git](https://github.com/cau-git) |
|
- Michele Dolfi, [@dolfim-ibm](https://github.com/dolfim-ibm) |
|
- Ahmed Nassar, [@nassarofficial](https://github.com/nassarofficial) |
|
- Peter Staar, [@PeterStaar-IBM](https://github.com/PeterStaar-IBM) |
|
|
|
### Licensing Information |
|
|
|
License: [CDLA-Permissive-1.0](https://cdla.io/permissive-1-0/) |
|
|
|
|
|
### Citation Information |
|
|
|
|
|
```bib |
|
@article{doclaynet2022, |
|
title = {DocLayNet: A Large Human-Annotated Dataset for Document-Layout Segmentation}, |
|
doi = {10.1145/3534678.353904}, |
|
url = {https://doi.org/10.1145/3534678.3539043}, |
|
author = {Pfitzmann, Birgit and Auer, Christoph and Dolfi, Michele and Nassar, Ahmed S and Staar, Peter W J}, |
|
year = {2022}, |
|
isbn = {9781450393850}, |
|
publisher = {Association for Computing Machinery}, |
|
address = {New York, NY, USA}, |
|
booktitle = {Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining}, |
|
pages = {3743–3751}, |
|
numpages = {9}, |
|
location = {Washington DC, USA}, |
|
series = {KDD '22} |
|
} |
|
``` |
