README.md

---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories: []
source_datasets:
- original
task_categories:
- image-to-image
- text-to-image
- unconditional-image-generation
task_ids: []
pretty_name: Magazine
tags:
- graphic design
- layout
- content-aware
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: filename
    dtype: string
  - name: category
    dtype:
      class_label:
        names:
          '0': fashion
          '1': food
          '2': news
          '3': science
          '4': travel
          '5': wedding
  - name: size
    struct:
    - name: width
      dtype: int64
    - name: height
      dtype: int64
  - name: elements
    sequence:
    - name: label
      dtype:
        class_label:
          names:
            '0': text
            '1': image
            '2': headline
            '3': text-over-image
            '4': headline-over-image
    - name: polygon_x
      sequence: float32
    - name: polygon_y
      sequence: float32
  - name: keywords
    sequence: string
  - name: images
    sequence: image
  splits:
  - name: train
    num_bytes: 4655342211.434
    num_examples: 3919
  download_size: 4652903538
  dataset_size: 4655342211.434
---

# Dataset Card for Magazine dataset

[![CI](https://github.com/shunk031/huggingface-datasets_Magazine/actions/workflows/ci.yaml/badge.svg)](https://github.com/shunk031/huggingface-datasets_Magazine/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://xtqiao.com/projects/content_aware_layout/
- **Repository:** https://github.com/shunk031/huggingface-datasets_Magazine
- **Paper (SIGGRAPH2019):** https://dl.acm.org/doi/10.1145/3306346.3322971

### Dataset Summary

A large-scale magazine layout dataset with fine-grained layout annotations and keyword labeling.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

<!-- To use Magazine dataset, you need to download the image and layout annotations from the [OneDrive](https://portland-my.sharepoint.com/:f:/g/personal/xqiao6-c_my_cityu_edu_hk/EhmRh5SFoQ9Hjl_aRjCOltkBKFYefiSagR6QLJ7pWvs3Ww?e=y8HO5Q) in the [official page](https://xtqiao.com/projects/content_aware_layout/).
Then place the downloaded files in the following structure and specify its path.

```shell
/path/to/datasets
├── MagImage.zip
└── MagLayout.zip
```

```python
import datasets as ds

dataset = ds.load_dataset(
    path="shunk031/Magazine",
    data_dir="/path/to/datasets/", # Specify the path of the downloaded directory.
)
``` -->

```python
import datasets as ds

dataset = ds.load_dataset("creative-graphic-design/Magazine")
```

### 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

```
Copyright (c) 2019, Xiaotian Qiao
All rights reserved.

This code is copyrighted by the authors and is for non-commercial research
purposes only.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this
  list of conditions and the following disclaimer.

* Redistributions in binary form must reproduce the above copyright notice,
  this list of conditions and the following disclaimer in the documentation
  and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
```

### Citation Information

```bibtex
@article{zheng2019content,
  title={Content-aware generative modeling of graphic design layouts},
  author={Zheng, Xinru and Qiao, Xiaotian and Cao, Ying and Lau, Rynson WH},
  journal={ACM Transactions on Graphics (TOG)},
  volume={38},
  number={4},
  pages={1--15},
  year={2019},
  publisher={ACM New York, NY, USA}
}
```

### Contributions

Thanks to [Xinru Zheng and Xiaotian Qiao](https://xtqiao.com/projects/content_aware_layout/) for creating this dataset.