CreativePSD is the PSD-derived graphic design dataset released with PSDesigner. Each example is a poster archive containing PSD tree text, structured layer metadata, tool-call trajectories, source image resources, and stepwise rendered images.
This loader keeps the contents of each poster_*.zip archive: all metadata text/JSON files, all raw_resource images, all rendering_imgs images, and a manifest of every member in the archive.
The dataset contains Chinese text in poster designs and metadata fields.
Each row corresponds to one poster_*.zip archive:
{
"id": "poster_000175",
"archive_filename": "poster_000175.zip",
"psd_info": {
"filename": "poster_000175.psd",
"width": 800,
"height": 800,
"resolution": 72,
"color_mode": "RGB"
},
"total_layers": 18,
"origin_psd_tree": "...",
"tool_trajectory_json": "[...]",
"raw_resources": [{"filename": "raw_resource/1_asset.png", "image": "<image>"}],
"rendering_images": [
{
"filename": "rendering_imgs/0_total.jpg",
"image_path": "poster_000175.zip/rendering_imgs/0_total.jpg",
"image_bytes": "<bytes>"
}
],
"final_rendering": "<image>"
}
id: Poster archive stem.archive_filename, archive_path, archive_size_bytes: Source archive metadata.psd_info: PSD filename, canvas size, resolution, color mode, and fill color.total_layers: Number of PSD layers from metadata/layer_info.json.origin_psd_tree, deleted_psd_tree, grouped_psd_tree: PSD tree text files.group_child_ids_json, layer_info_json, rendering_id_json, tool_trajectory_json, render_second_values_json: Original JSON files serialized as strings.metadata_files: All files under metadata/ as text.non_image_files: Every non-image file in the archive as text and bytes.raw_resources: All source images under raw_resource/.rendering_images: All images under rendering_imgs/, including 0_total.jpg and intermediate layer renders, stored as image bytes plus archive-relative paths.final_rendering: rendering_imgs/0_total.jpg when present.all_files: Manifest of every file member in the zip.The loader exposes a single train split. The PSDesigner paper reports 10,454 CreativePSD samples in Table 1, while the public ModelScope release currently exposes 7,978 root-level poster_*.zip archives through the file metadata API. This loader targets the public ModelScope archive release, not the unreleased remainder implied by the paper count.
When loading from an official ModelScope checkout, the loader validates the archive count and skips only the known unavailable source archives listed below. With the current source availability issue, non-streaming load_dataset(...) completes with 7,968 usable poster archives.
As of 2026-06-28, the paper-reported CreativePSD count, the public ModelScope release, and the loadable dataset rows differ:
poster_*.zip archives.load_dataset(...) result: 7,968 rows after skipping the 10 known unavailable archives below.Repeated downloads from the available ModelScope SDK, resolve/raw, Git LFS, and OSS access paths returned 10 of the public archives as 0-byte files in the local checkout. The loader skips these known unavailable archives when they are 0-byte or absent in an official ModelScope checkout. Any other invalid or missing poster archive still fails validation.
The currently unresolved 0-byte archives are:
poster_003266.zipposter_003281.zipposter_003287.zipposter_003288.zipposter_003294.zipposter_003296.zipposter_003299.zipposter_003302.zipposter_003305.zipposter_003306.zipDownload the dataset with ModelScope:
from modelscope.msdatasets import MsDataset
MsDataset.load("song322/CreativePSD")
Then load from the directory containing poster_*.zip files:
import datasets as ds
dataset = ds.load_dataset(
"datasets/CreativePSD/CreativePSD.py",
data_dir="/root/ghq/www.modelscope.cn/datasets/song322/CreativePSD",
trust_remote_code=True,
)
The ModelScope dataset card states that the dataset is for non-commercial research use only. Users should review the original dataset terms before redistribution or model training.
The source dataset card lists CC-BY-NC-4.0.
@InProceedings{Shuai_2026_CVPR,
title={PSDesigner: Automated Graphic Design with a Human-Like Creative Workflow},
author={Shuai, Xincheng and Tang, Song and Huang, Yutong and Ding, Henghui and Tao, Dacheng},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month={June},
year={2026},
pages={10165-10175},
}
Thanks to the PSDesigner and CreativePSD authors for creating and releasing this dataset.
500 commits
CreativePSD is the PSD-derived graphic design dataset released with PSDesigner. Each example is a poster archive containing PSD tree text, structured layer metadata, tool-call trajectories, source image resources, and stepwise rendered images.
This loader keeps the contents of each poster_*.zip archive: all metadata text/JSON files, all raw_resource images, all rendering_imgs images, and a manifest of every member in the archive.
The dataset contains Chinese text in poster designs and metadata fields.
Each row corresponds to one poster_*.zip archive:
{
"id": "poster_000175",
"archive_filename": "poster_000175.zip",
"psd_info": {
"filename": "poster_000175.psd",
"width": 800,
"height": 800,
"resolution": 72,
"color_mode": "RGB"
},
"total_layers": 18,
"origin_psd_tree": "...",
"tool_trajectory_json": "[...]",
"raw_resources": [{"filename": "raw_resource/1_asset.png", "image": "<image>"}],
"rendering_images": [
{
"filename": "rendering_imgs/0_total.jpg",
"image_path": "poster_000175.zip/rendering_imgs/0_total.jpg",
"image_bytes": "<bytes>"
}
],
"final_rendering": "<image>"
}
id: Poster archive stem.archive_filename, archive_path, archive_size_bytes: Source archive metadata.psd_info: PSD filename, canvas size, resolution, color mode, and fill color.total_layers: Number of PSD layers from metadata/layer_info.json.origin_psd_tree, deleted_psd_tree, grouped_psd_tree: PSD tree text files.group_child_ids_json, layer_info_json, rendering_id_json, tool_trajectory_json, render_second_values_json: Original JSON files serialized as strings.metadata_files: All files under metadata/ as text.non_image_files: Every non-image file in the archive as text and bytes.raw_resources: All source images under raw_resource/.rendering_images: All images under rendering_imgs/, including 0_total.jpg and intermediate layer renders, stored as image bytes plus archive-relative paths.final_rendering: rendering_imgs/0_total.jpg when present.all_files: Manifest of every file member in the zip.The loader exposes a single train split. The PSDesigner paper reports 10,454 CreativePSD samples in Table 1, while the public ModelScope release currently exposes 7,978 root-level poster_*.zip archives through the file metadata API. This loader targets the public ModelScope archive release, not the unreleased remainder implied by the paper count.
When loading from an official ModelScope checkout, the loader validates the archive count and skips only the known unavailable source archives listed below. With the current source availability issue, non-streaming load_dataset(...) completes with 7,968 usable poster archives.
As of 2026-06-28, the paper-reported CreativePSD count, the public ModelScope release, and the loadable dataset rows differ:
poster_*.zip archives.load_dataset(...) result: 7,968 rows after skipping the 10 known unavailable archives below.Repeated downloads from the available ModelScope SDK, resolve/raw, Git LFS, and OSS access paths returned 10 of the public archives as 0-byte files in the local checkout. The loader skips these known unavailable archives when they are 0-byte or absent in an official ModelScope checkout. Any other invalid or missing poster archive still fails validation.
The currently unresolved 0-byte archives are:
poster_003266.zipposter_003281.zipposter_003287.zipposter_003288.zipposter_003294.zipposter_003296.zipposter_003299.zipposter_003302.zipposter_003305.zipposter_003306.zipDownload the dataset with ModelScope:
from modelscope.msdatasets import MsDataset
MsDataset.load("song322/CreativePSD")
Then load from the directory containing poster_*.zip files:
import datasets as ds
dataset = ds.load_dataset(
"datasets/CreativePSD/CreativePSD.py",
data_dir="/root/ghq/www.modelscope.cn/datasets/song322/CreativePSD",
trust_remote_code=True,
)
The ModelScope dataset card states that the dataset is for non-commercial research use only. Users should review the original dataset terms before redistribution or model training.
The source dataset card lists CC-BY-NC-4.0.
@InProceedings{Shuai_2026_CVPR,
title={PSDesigner: Automated Graphic Design with a Human-Like Creative Workflow},
author={Shuai, Xincheng and Tang, Song and Huang, Yutong and Ding, Henghui and Tao, Dacheng},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month={June},
year={2026},
pages={10165-10175},
}
Thanks to the PSDesigner and CreativePSD authors for creating and releasing this dataset.
500 commits