Update CGLDataset dataset card

README.md

@@ -1,25 +1,45 @@
 ---
 annotations_creators:
-- crowdsourced
+  - crowdsourced
 language:
-- zh
+  - zh
 language_creators:
-- found
+  - found
 license:
-- cc-by-nc-sa-4.0
+  - cc-by-nc-sa-4.0
 multilinguality:
-- monolingual
+  - monolingual
 pretty_name: CGL-Dataset
-size_categories: []
+size_categories:
+  - 10K<n<100K
 source_datasets:
-- original
+  - original
 tags:
-- graphic-design
-- layout-generation
-- poster-generation
+  - graphic-design
+  - poster
+  - layout-generation
 task_categories:
-- other
+  - image-to-image
 task_ids: []
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/train-*
+      - split: validation
+        path: data/validation-*
+      - split: test
+        path: data/test-*
+  - config_name: ralf-style
+    data_files:
+      - split: train
+        path: ralf-style/train-*
+      - split: validation
+        path: ralf-style/validation-*
+      - split: test
+        path: ralf-style/test-*
+      - split: no_annotation
+        path: ralf-style/no_annotation-*
 dataset_info:
 - config_name: default
   features:
@@ -120,168 +140,66 @@ dataset_info:
     num_examples: 1000
   download_size: 37543869068
   dataset_size: 37707823779.125
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
-- config_name: ralf-style
-  data_files:
-  - split: train
-    path: ralf-style/train-*
-  - split: validation
-    path: ralf-style/validation-*
-  - split: test
-    path: ralf-style/test-*
-  - split: no_annotation
-    path: ralf-style/no_annotation-*
 ---
 
 # Dataset Card for CGL-Dataset
 
-
-## 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)
+[![CI](https://github.com/creative-graphic-design/huggingface-datasets/actions/workflows/ci.yaml/badge.svg)](https://github.com/creative-graphic-design/huggingface-datasets/actions/workflows/ci.yaml)
+[![Sync HF](https://github.com/creative-graphic-design/huggingface-datasets/actions/workflows/push_to_hub.yaml/badge.svg)](https://github.com/creative-graphic-design/huggingface-datasets/actions/workflows/push_to_hub.yaml)
 
 ## Dataset Description
 
 - **Homepage:** https://github.com/minzhouGithub/CGL-GAN
 - **Repository:** https://github.com/creative-graphic-design/huggingface-datasets/tree/main/datasets/CGLDataset
 - **Hugging Face Dataset:** https://huggingface.co/datasets/creative-graphic-design/CGL-Dataset
-- **Paper (Preprint):** https://arxiv.org/abs/2205.00303
-- **Paper (IJCAI2022):** https://www.ijcai.org/proceedings/2022/692
+- **Paper (arXiv):** https://arxiv.org/abs/2205.00303
+- **Paper (IJCAI 2022):** https://www.ijcai.org/proceedings/2022/692
 
 ### Dataset Summary
 
-The CGL-Dataset is a dataset used for the task of automatic graphic layout design for advertising posters. It contains 61,548 samples and is provided by Alibaba Group.
+CGL-Dataset is a poster layout dataset released with *Composition-aware Graphic Layout GAN for Visual-Textual Presentation Designs*. The paper studies layout generation for a given image, emphasizing that both global semantics and spatial image composition affect where graphic elements should be placed. The original dataset contains 60,548 advertising posters with annotated layout information.
 
 ### Supported Tasks and Leaderboards
 
-The task is to generate high-quality graphic layouts for advertising posters based on clean product images and their visual contents. The training set and validation set are collections of 60,548 e-commerce advertising posters, with manual annotations of the categories and positions of elements (such as logos, texts, backgrounds, and embellishments on the posters). Note that the validation set also consists of posters, not clean product images. The test set contains 1,000 clean product images without graphic elements such as logos or texts, consistent with real application data.
+The dataset supports poster layout generation and layout-conditioned graphic design modeling. No public leaderboard is bundled with this Hugging Face dataset.
 
 ### Languages
 
-[More Information Needed]
-
+Poster text is primarily Chinese (`zh`).
 
 ## Dataset Structure
 
-### Data Instances
-
-[More Information Needed]
-
-
 ### Data Fields
 
-[More Information Needed]
+The `default` config contains `image_id`, `file_name`, `width`, `height`, `image`, and COCO-style `annotations`.
 
+The `ralf-style` config provides original posters, inpainted posters, saliency maps, and annotations for layout-generation pipelines.
 
 ### Data Splits
 
-[More Information Needed]
-
+| Config | Split | Rows |
+| --- | --- | ---: |
+| default | train | 54,546 |
+| default | validation | 6,002 |
+| default | test | 1,000 |
+| ralf-style | train | 48,438 |
+| ralf-style | validation | 6,055 |
+| ralf-style | test | 6,055 |
+| ralf-style | no_annotation | 1,000 |
 
 ## 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]
-
+The dataset was created for Composition-aware Graphic Layout GAN research. It provides visual element categories and positions for poster layout generation, enabling models to synthesize text and decorative layouts conditioned on image content rather than using template-only rules.
 
 ## Considerations for Using the Data
 
-### Social Impact of Dataset
-
-[More Information Needed]
-
-
-### Discussion of Biases
-
-[More Information Needed]
-
-
-### Other Known Limitations
-
-[More Information Needed]
-
+The data focuses on advertising poster layouts and may reflect the visual conventions of the source domain.
 
 ## Additional Information
 
-### Dataset Curators
-
-[More Information Needed]
-
-
 ### Licensing Information
 
-[More Information Needed]
-
+The dataset card uses the CC BY-NC-SA 4.0 metadata from the local loader.
 
 ### Citation Information
 
@@ -291,16 +209,13 @@ The task is to generate high-quality graphic layouts for advertising posters bas
   author    = {Zhou, Min and Xu, Chenchen and Ma, Ye and Ge, Tiezheng and Jiang, Yuning and Xu, Weiwei},
   booktitle = {Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, {IJCAI-22}},
   publisher = {International Joint Conferences on Artificial Intelligence Organization},
-  editor    = {Lud De Raedt},
   pages     = {4995--5001},
   year      = {2022},
-  month     = {7},
-  note      = {AI and Arts},
   doi       = {10.24963/ijcai.2022/692},
-  url       = {https://doi.org/10.24963/ijcai.2022/692},
+  url       = {https://doi.org/10.24963/ijcai.2022/692}
 }
 ```
 
 ### Contributions
 
-Thanks to [@minzhouGithub](https://github.com/minzhouGithub) for adding this dataset.
+Thanks to [minzhouGithub](https://github.com/minzhouGithub) for creating the original dataset.