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---
dataset_info:
features:
- name: id
dtype: string
- name: metadata
dtype: string
- name: original_image
dtype: image
- name: condition_gray_background
dtype: image
- name: condition_rgba
dtype: image
- name: subject_mask
dtype: image
- name: condition_rgba_variants
sequence: image
- name: condition_white_variants
sequence: image
splits:
- name: test
num_bytes: 3658370666
num_examples: 1000
download_size: 3621645033
dataset_size: 3658370666
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
license: apache-2.0
---
# CreatiDesign Benchmark
## Overview
CreatiDesign Benchmark is a comprehensive benchmark for evaluating multi-conditional graphic design generation models. It contains 1,000 carefully curated samples spanning real-world design scenarios, including movie posters, product advertisements, brand promotions, and social media content. The benchmark focuses on assessing models' fine-grained controllability over multiple heterogeneous conditions—such as primary visual elements (main images), secondary visual elements (decorative objects), and textual elements—while also measuring overall visual quality and strict adherence to user intent.
## Download and Usage
```python
from datasets import load_dataset
dataset_repo = 'HuiZhang0812/CreatiDesign_benchmark'
test_dataset = load_dataset(dataset_path, split='test')
```
To evaluate your model's graphic design generation capabilities using the CreatiDesign Benchmark, please follow [CreatiDesign](https://github.com/HuiZhang0812/CreatiDesign).
```
@article{zhang2025creatidesign,
title={CreatiDesign: A Unified Multi-Conditional Diffusion Transformer for Creative Graphic Design},
author={Zhang, Hui and Hong, Dexiang and Yang, Maoke and Chen, Yutao and Zhang, Zhao and Shao, Jie and Wu, Xinglong and Wu, Zuxuan and Jiang, Yu-Gang},
journal={arXiv preprint arXiv:2505.19114},
year={2025}
}
```
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