---
annotations_creators:
  - machine-generated
language:
  - en
language_creators:
  - found
license:
  - cdla-permissive-1.0
pretty_name: PubLayNet
size_categories:
  - 100K<n<1M
source_datasets:
  - original
tags:
  - document-layout-analysis
  - object-detection
  - segmentation
task_categories:
  - object-detection
  - image-segmentation
task_ids: []
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
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
---

# Dataset Card for PubLayNet

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## Dataset Description

- **Homepage:** https://developer.ibm.com/exchanges/data/all/publaynet/
- **Repository:** https://github.com/creative-graphic-design/huggingface-datasets/tree/main/datasets/PubLayNet
- **Hugging Face Dataset:** https://huggingface.co/datasets/creative-graphic-design/PubLayNet
- **Paper (arXiv):** https://arxiv.org/abs/1908.07836
- **Paper (ICDAR 2019):** https://ieeexplore.ieee.org/document/8977963

### Dataset Summary

PubLayNet is a large document layout analysis dataset built by automatically matching XML representations and PDF content from more than one million PubMed Central Open Access articles. It contains more than 360,000 document images with COCO-style annotations for common layout elements such as text, title, list, table, and figure regions.

### Supported Tasks and Leaderboards

The dataset supports document layout object detection and segmentation. No leaderboard is bundled with this Hugging Face packaging.

### Languages

Document content is primarily English (`en`), but the task is visual document layout analysis.

## Dataset Structure

### Data Fields

Rows contain `image_id`, `file_name`, `width`, `height`, `image`, and COCO-style `annotations`.

### Data Splits

| Split | Rows |
| --- | ---: |
| train | 335,703 |
| validation | 11,245 |
| test | 11,405 |

## Dataset Creation

PubLayNet was created from automatically parsed document layouts and released for large-scale document layout analysis.

## Considerations for Using the Data

The dataset is document-centric and may not represent all document domains or non-English layout conventions.

## Additional Information

### Licensing Information

This dataset card uses the CDLA Permissive 1.0 license metadata from the local loader.

### 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}
}
```