size_categories:n<1K format:parquet modality:image modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: original_image
    dtype: image
  - name: caption
    dtype: string
  - name: edited_image
    dtype: image
  splits:
  - name: val
    num_bytes: 142328486.0
    num_examples: 100
  download_size: 133432412
  dataset_size: 142328486.0
configs:
- config_name: default
  data_files:
  - split: val
    path: data/val-*
---

# Dataset Card for TEdBench

**TEdBench** (**T**extual **E**diting **Bench**mark) contains 100 images and text descriptions depicting edits to be applied.
It is intended as an evaluation dataset for the task of text-based real image editing.
This dataset was first introduced in [Imagic](https://imagic-editing.github.io/).

## Dataset Structure
Each entry in this dataset contains a real image (`original_image`), a text describing the desired edit (`caption`), and Imagic's result for comparison purposes (`edited_image`).
Note that Imagic results are of varied quality, and should not be considered as ground-truth.

## Citation (BibTeX)

If you find this dataset useful in your work, please cite:

```
@inproceedings{kawar2023imagic,
      title={Imagic: Text-Based Real Image Editing with Diffusion Models},
      author={Kawar, Bahjat and Zada, Shiran and Lang, Oran and Tov, Omer and Chang, Huiwen and Dekel, Tali and Mosseri, Inbar and Irani, Michal},
      booktitle={Conference on Computer Vision and Pattern Recognition 2023},
      year={2023}
}
```
