| --- |
| 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 |
|
|
| [](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. |
|
|
