Upload README.md with huggingface_hub

README.md

@@ -1,60 +1,300 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: int32
-  - name: background_image
-    dtype: image
-  - name: background_image_relpath
-    dtype: string
-  - name: psd_path
-    dtype: string
-  - name: regions
-    sequence:
-      sequence: int32
-      length: 4
-  - name: layers
-    sequence:
-    - name: layer_name
-      dtype: string
-    - name: text
-      dtype: string
-    - name: bbox
-      sequence: int32
-      length: 4
-    - name: angle
-      dtype: int32
-    - name: psd_size
-      sequence: int32
-      length: 2
-    - name: stroke_width
-      dtype: float32
-    - name: font
-      dtype: string
-    - name: font_size
-      dtype: float32
-    - name: tracking
-      dtype: float32
-    - name: justification
-      dtype: int32
-    - name: fill_color
-      sequence: float32
-      length: 4
-    - name: layer_image
-      dtype: image
-    - name: layer_image_relpath
-      dtype: string
-    - name: label
-      dtype: string
-  splits:
-  - name: train
-    num_bytes: 234187965023.898
-    num_examples: 102703
-  download_size: 227886221521
-  dataset_size: 234187965023.898
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+language:
+  - en
+license: cc-by-nc-4.0
+pretty_name: GenPoster100K
+tags:
+  - graphic-design
+  - layout-generation
+  - multimodal
+  - poster-design
+annotations_creators:
+  - machine-generated
+language_creators:
+  - found
+size_categories:
+  - 100K<n<1M
+source_datasets:
+  - original
+task_categories:
+  - text-to-image
+  - image-to-text
+task_ids:
+  - other:content-aware-layout-generation
 ---
+
+# Dataset Card for GenPoster100K
+
+[![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)
+
+## 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://huggingface.co/datasets/BruceW91/GenPoster-100K
+- **Repository:** https://github.com/creative-graphic-design/huggingface-datasets/tree/main/datasets/GenPoster100K
+- **Paper (Preprint):** https://arxiv.org/abs/2510.15749
+- **Paper (Conference):** https://openaccess.thecvf.com/content/ICCV2025/html/Wang_SEGA_A_Stepwise_Evolution_Paradigm_for_Content-Aware_Layout_Generation_with_ICCV_2025_paper.html
+- **Leaderboard:** No official public leaderboard URL is documented for GenPoster-100K.
+- **Point of Contact:** Original dataset/project authors (paper) and maintainers of the source HF dataset (`BruceW91/GenPoster-100K`).
+
+### Dataset Summary
+
+GenPoster-100K is a large-scale dataset for content-aware graphic layout generation introduced in the SEGA paper.
+The paper describes it as a high-quality poster dataset with layer-parseable source materials and rich metadata.
+
+This repository provides a Hugging Face `datasets` loader implementation that reads the source release (`BruceW91/GenPoster-100K`) and exposes normalized examples with:
+
+- poster background image (`background_image`)
+- PSD reference path (`psd_path`)
+- region boxes (`regions`)
+- layer-level annotations (`layers`) including text, bbox, typography, color, and per-layer rendered image
+
+Implementation note: this loader uses `0503_raw_offline.pkl` and `part_*.tar.gz`, yielding 102,703 rows in `train`.
+
+### Supported Tasks and Leaderboards
+
+- `other:content-aware-layout-generation`: Generate or refine poster element layouts conditioned on background imagery and textual element metadata.
+- `text-to-image`: Can be used in poster design workflows where textual content and structured attributes guide generated visual composition.
+- `image-to-text`: Can support structured extraction/understanding tasks over design layers and poster metadata.
+
+No official leaderboard URL specific to GenPoster-100K is currently provided in the public source materials.
+
+### Languages
+
+- Frontmatter language is set to English (`en`) because the released examples predominantly contain English poster text.
+- The dataset may include additional languages in real-world templates, but a full language distribution is not documented in the source materials.
+
+## Dataset Structure
+
+### Data Instances
+
+Each example includes image assets and structured layer metadata.
+
+```json
+{
+  "id": 0,
+  "background_image": "<image>",
+  "background_image_relpath": "big_poster/poster_metadata/3841272.psd_0_11775f75bf_bg.png",
+  "psd_path": "big_poster/meta_psd/3841272.psd",
+  "regions": [[1656, 481, 2545, 855]],
+  "layers": [
+    {
+      "layer_name": "&#wText&#wTitle",
+      "text": "Super price!",
+      "bbox": [1754, 573, 2423, 689],
+      "angle": 0,
+      "psd_size": [3508, 2480],
+      "stroke_width": 0.0,
+      "font": "Aftaserif",
+      "font_size": 113.29,
+      "tracking": 0.0,
+      "justification": 1,
+      "fill_color": [0.0, 0.0, 0.0, 1.0],
+      "layer_image": "<image>",
+      "layer_image_relpath": "big_poster/poster_metadata/3841272.psd_0_11775f75bf_3.png",
+      "label": "Calls to Action"
+    }
+  ]
+}
+```
+
+### Data Fields
+
+- `id` (`int32`): Example identifier assigned by loader order.
+- `background_image` (`Image`): Rendered background image for the poster.
+- `background_image_relpath` (`string`): Relative path of the background image in source assets.
+- `psd_path` (`string`): Relative PSD path recorded in annotations.
+- `regions` (`Sequence[Sequence[int32]]`): Region boxes as `[x1, y1, x2, y2]`.
+- `layers` (`Sequence[struct]`): Layer-level annotations.
+  - `layer_name` (`string`)
+  - `text` (`string`)
+  - `bbox` (`Sequence[int32]`, length=4)
+  - `angle` (`int32`)
+  - `psd_size` (`Sequence[int32]`, length=2)
+  - `stroke_width` (`float32`)
+  - `font` (`string`)
+  - `font_size` (`float32`)
+  - `tracking` (`float32`)
+  - `justification` (`int32`)
+  - `fill_color` (`Sequence[float32]`, length=4)
+  - `layer_image` (`Image`)
+  - `layer_image_relpath` (`string`)
+  - `label` (`string`)
+
+### Data Splits
+
+This implementation exposes a single `train` split from the upstream release.
+
+| Split | Rows |
+| --- | ---: |
+| train | 102,703 |
+
+Notes:
+
+- The paper reports 105,456 posters in the broader GenPoster-100K corpus.
+- The HF source release used by this loader provides `0503_raw_offline.pkl` with 102,703 records.
+- The original source data is `train`-only, but our Hugging Face Hub publication splits it into `train/validation/test = 8:1:1` and pushes that split dataset.
+
+## Dataset Creation
+
+### Curation Rationale
+
+According to the SEGA paper, GenPoster-100K was introduced to improve data quality and scale for content-aware layout generation.
+The paper highlights limitations in earlier datasets (for example, artifacts from inpainted backgrounds and less structured metadata) and positions GenPoster-100K as a higher-fidelity, large-scale alternative with rich component-level information.
+
+### Source Data
+
+The source release includes poster metadata archives (`part_*.tar.gz`) and annotation pickle files.
+A disclaimer in the source dataset indicates copyright belongs to the original owner (Freepik) and commercial use may require additional permission.
+
+#### Initial Data Collection and Normalization
+
+From public materials:
+
+- The paper describes data built from layer-parseable source materials with hierarchical metadata.
+- The source HF dataset release distributes image assets split across 79 archive parts (`part_0.tar.gz` ... `part_78.tar.gz`).
+
+In this loader implementation:
+
+- Annotation source is `0503_raw_offline.pkl`.
+- URL query strings are normalized/removed and image paths are resolved against extracted archive contents.
+- BBox/size/color fields are normalized to fixed lengths and numeric dtypes.
+
+#### Who are the source language producers?
+
+The textual content appears to originate from poster templates designed by content creators in the source design corpus.
+No demographic metadata for these creators is provided in the public release.
+
+### Annotations
+
+The release provides machine-readable layer metadata per poster example, including geometry and typography attributes.
+The dataset card metadata marks annotation creation as machine-generated.
+
+#### Annotation process
+
+Public paper/source materials indicate hierarchical metadata extracted from PSD-parseable design sources.
+The implementation-level annotation fields include:
+
+- text and layer names
+- bounding boxes and angle
+- typography attributes (font, size, tracking, justification, stroke)
+- RGBA fill color
+- region boxes
+- references to rendered background/layer images
+
+Detailed internal annotation tooling and QA workflow are not fully specified in the public documents.
+
+#### Who are the annotators?
+
+Annotations are primarily machine-generated from source design assets.
+Named individual annotators are not documented.
+
+### Personal and Sensitive Information
+
+The dataset is composed of poster design assets and textual elements.
+It is not released as a personal-data dataset, but real-world template text may include names, brands, or contact-like strings depending on source content.
+Users should perform downstream filtering/redaction if their use case requires stricter privacy constraints.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+Potential positive impact:
+
+- Enables research on automated graphic design and multimodal layout understanding.
+- Supports reproducible benchmarking for content-aware layout generation.
+
+Potential risks:
+
+- May be used to generate misleading or low-quality promotional content at scale.
+- Could be misused for style imitation or copyright-sensitive commercial outputs.
+
+### Discussion of Biases
+
+Likely biases include:
+
+- Domain/style bias toward stock-template aesthetics and marketing layouts.
+- Language/domain imbalance (predominantly English and commercial poster styles).
+- Visual-cultural bias inherited from source platforms and curation choices.
+
+No public bias audit report specific to this release is currently documented.
+
+### Other Known Limitations
+
+- The upstream source is train-only; this loader follows that source format, while our Hub publication additionally provides an `8:1:1` split.
+- Paper-level total (105,456) and loader-level total (102,703) differ due to release artifacts used by this loader.
+- `psd_path` is recorded as metadata path, but only a limited subset of raw PSD files is present in the public source release.
+- License constraints limit direct commercial usage without additional permission from the copyright owner.
+
+## Additional Information
+
+### Dataset Curators
+
+- Original dataset/paper authors: Wang et al. (SEGA, ICCV 2025).
+- Source HF release contributor: [@BruceW91](https://huggingface.co/BruceW91).
+- This repository contains a community-maintained Hugging Face dataset loader implementation.
+
+### Licensing Information
+
+- Dataset card license: `cc-by-nc-4.0`
+- Source disclaimer indicates use is intended for academic purposes, and commercial use may require prior permission from the copyright owner (Freepik): https://www.freepik.com/
+
+Always verify license compatibility with your intended use before redistribution or deployment.
+
+### Citation Information
+
+If your implementation is based on this dataset, please cite the original paper and the Hugging Face dataset implementation:
+
+```bibtex
+@inproceedings{wang2025sega,
+  title={SEGA: A Stepwise Evolution Paradigm for Content-Aware Layout Generation with Design Prior},
+  author={Wang, Haoran and Zhao, Bo and Wang, Jinghui and Wang, Hanzhang and Yang, Huan and Ji, Wei and Liu, Hao and Xiao, Xinyan},
+  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
+  pages={19321--19330},
+  year={2025}
+}
+```
+
+```bibtex
+@misc{genposter100kdataset,
+  title = {GenPoster100K dataset},
+  author = {{Creative Graphic Design Lab} and Kitada, Shunsuke},
+  howpublished = {Hugging Face dataset},
+  year = {2025},
+  note = {URL: https://huggingface.co/datasets/creative-graphic-design/GenPoster100K},
+}
+```
+
+### Contributions
+
+Thanks to the original GenPoster-100K authors and [@BruceW91](https://huggingface.co/BruceW91) for releasing the source dataset.
+This Hugging Face dataset implementation was created for the `creative-graphic-design/huggingface-datasets` monorepo.