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---
language:
- en
license: cc-by-4.0
size_categories:
- 100K<n<1M
task_categories:
- text-to-image
dataset_info:
features:
- name: clip_sim_source
dtype: float64
- name: clip_sim_target
dtype: float64
- name: clip_sim_dir
dtype: float64
- name: clip_sim_image
dtype: float64
- name: dinov2_sim
dtype: float64
- name: ssim
dtype: float64
- name: source_caption
dtype: string
- name: target_caption
dtype: string
- name: idx
dtype: int64
- name: edit_prompt
dtype: string
- name: source_image
dtype: image
- name: edited_image
dtype: image
splits:
- name: FreeForm
num_bytes: 194880436920.0
num_examples: 500000
download_size: 194882628714
dataset_size: 194880436920.0
configs:
- config_name: default
data_files:
- split: FreeForm
path: data/FreeForm-*
tags:
- art
---
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
### Dataset Description
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- **Curated by:** [More Information Needed]
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### Dataset Sources [optional]
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- **Repository:** [More Information Needed]
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## Uses
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## Dataset Structure
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## Dataset Creation
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#### Data Collection and Processing
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#### Annotation process
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#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
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**BibTeX:**
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**APA:**
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## Bibtext citation
```bibtex
@misc{zhao2024ultraeditinstructionbasedfinegrainedimage,
title={UltraEdit: Instruction-based Fine-Grained Image Editing at Scale},
author={Haozhe Zhao and Xiaojian Ma and Liang Chen and Shuzheng Si and Rujie Wu and Kaikai An and Peiyu Yu and Minjia Zhang and Qing Li and Baobao Chang},
year={2024},
eprint={2407.05282},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2407.05282},
}
``` |