Datasets:

creative-graphic-design
/

PubLayNet

	---
	annotations_creators:
	- machine-generated
	language_creators:
	- found
	language:
	- en
	license:
	- cdla-permissive-1.0
	multilinguality:
	- monolingual
	size_categories: []
	source_datasets:
	- original
	task_categories:
	- image-classification
	- image-segmentation
	- image-to-text
	- question-answering
	- other
	- multiple-choice
	- token-classification
	- tabular-to-text
	- object-detection
	- table-question-answering
	- text-classification
	- table-to-text
	task_ids:
	- multi-label-image-classification
	- multi-class-image-classification
	- semantic-segmentation
	- image-captioning
	- extractive-qa
	- closed-domain-qa
	- multiple-choice-qa
	- named-entity-recognition
	pretty_name: PubLayNet
	tags:
	- graphic design
	- layout-generation
	dataset_info:
	features:
	- name: image_id
	dtype: int32
	- name: file_name
	dtype: string
	- name: width
	dtype: int32
	- name: height
	dtype: int32
	- name: image
	dtype: image
	- name: annotations
	sequence:
	- name: annotation_id
	dtype: int32
	- name: area
	dtype: float32
	- name: bbox
	sequence: float32
	length: 4
	- name: category
	struct:
	- name: category_id
	dtype: int32
	- name: name
	dtype:
	class_label:
	names:
	'0': text
	'1': title
	'2': list
	'3': table
	'4': figure
	- name: supercategory
	dtype: string
	- name: category_id
	dtype: int32
	- name: image_id
	dtype: int32
	- name: iscrowd
	dtype: bool
	- name: segmentation
	dtype: image
	splits:
	- name: train
	num_bytes: 99127922734.771
	num_examples: 335703
	- name: validation
	num_bytes: 3513203604.885
	num_examples: 11245
	- name: test
	num_bytes: 3406081626.495
	num_examples: 11405
	download_size: 107597638930
	dataset_size: 106047207966.15099
	configs:
	- config_name: default
	data_files:
	- split: train
	path: data/train-*
	- split: validation
	path: data/validation-*
	- split: test
	path: data/test-*
	---

	# Dataset Card for PubLayNet

	[![CI](https://github.com/shunk031/huggingface-datasets_PubLayNet/actions/workflows/ci.yaml/badge.svg)](https://github.com/shunk031/huggingface-datasets_PubLayNet/actions/workflows/ci.yaml)

	## Table of Contents
	- [Dataset Card Creation Guide](#dataset-card-creation-guide)
	- [Table of Contents](#table-of-contents)
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
	- [Who are the source language producers?](#who-are-the-source-language-producers)
	- [Annotations](#annotations)
	- [Annotation process](#annotation-process)
	- [Who are the annotators?](#who-are-the-annotators)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [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/publaynet/
	- Repository: https://github.com/shunk031/huggingface-datasets_PubLayNet
	- Paper (Preprint): https://arxiv.org/abs/1908.07836
	- Paper (ICDAR2019): https://ieeexplore.ieee.org/document/8977963

	### Dataset Summary

	PubLayNet is a dataset for document layout analysis. It contains images of research papers and articles and annotations for various elements in a page such as "text", "list", "figure" etc in these research paper images. The dataset was obtained by automatically matching the XML representations and the content of over 1 million PDF articles that are publicly available on PubMed Central.

	### Supported Tasks and Leaderboards

	[More Information Needed]

	### Languages

	[More Information Needed]

	## Dataset Structure

	### Data Instances

	```python
	import datasets as ds

	dataset = ds.load_dataset(
	path="shunk031/PubLayNet",
	decode_rle=True, # True if Run-length Encoding (RLE) is to be decoded and converted to binary mask.
	)
	```

	### Data Fields

	[More Information Needed]

	### Data Splits

	[More Information Needed]

	## Dataset Creation

	### Curation Rationale

	[More Information Needed]

	### Source Data

	[More Information Needed]

	#### Initial Data Collection and Normalization

	[More Information Needed]

	#### Who are the source language producers?

	[More Information Needed]

	### Annotations

	[More Information Needed]

	#### Annotation process

	[More Information Needed]

	#### Who are the annotators?

	[More Information Needed]

	### Personal and Sensitive Information

	[More Information Needed]

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed]

	### Discussion of Biases

	[More Information Needed]

	### Other Known Limitations

	[More Information Needed]

	## Additional Information

	### Dataset Curators

	[More Information Needed]

	### Licensing Information

	- [CDLA-Permissive](https://cdla.io/permissive-1-0/)

	### Citation Information


	```bibtex
	@inproceedings{zhong2019publaynet,
	title={Publaynet: largest dataset ever for document layout analysis},
	author={Zhong, Xu and Tang, Jianbin and Yepes, Antonio Jimeno},
	booktitle={2019 International Conference on Document Analysis and Recognition (ICDAR)},
	pages={1015--1022},
	year={2019},
	organization={IEEE}
	}
	```

	### Contributions

	Thanks to [ibm-aur-nlp/PubLayNet](https://github.com/ibm-aur-nlp/PubLayNet) for creating this dataset.