Datasets:

Modalities:
Image
Languages:
English
Size:
< 1K
ArXiv:
Libraries:
Datasets
License:
DragBench / README.md
LuJingyi's picture
Update README.md
f53c77f verified
---
license: apache-2.0
task_categories:
- image-to-image
language:
- en
size_categories:
- n<1K
---
arxiv: arxiv.org/abs/2509.04582
# DragBench Dataset
A benchmark dataset for drag-based image editing evaluation, consisting of two subsets with additional annotations for [Inpaint4Drag](https://visual-ai.github.io/inpaint4drag/) method evaluation.
## Dataset Overview
DragBench provides standardized evaluation data for interactive point-based image editing research. The dataset combines:
- **DragBench-DR** (205 samples): Modified version of DragBench-D from [DragDiffusion](https://github.com/Yujun-Shi/DragDiffusion/)
- **DragBench-SR** (100 samples): Modified version of DragBench-S from [SDE-Drag](https://github.com/ML-GSAI/SDE-Drag)
Both subsets include additional annotations for Inpaint4Drag method evaluation.
## Dataset Structure
```
drag_data/
├── dragbench-dr/ # DragBench-DR (205 samples)
│ ├── animals/
│ │ ├── sample_001/
│ │ │ ├── original_image.png
│ │ │ ├── meta_data.pkl
│ │ │ ├── user_drag.png
│ │ │ ├── meta_data_i4p.pkl
│ │ │ └── user_drag_i4p.png
│ │ └── ...
│ └── [other_categories]/
└── dragbench-sr/ # DragBench-SR (100 samples)
├── sample_001/
│ ├── original_image.png
│ ├── meta_data.pkl
│ ├── user_drag.png
│ ├── meta_data_i4p.pkl
│ └── user_drag_i4p.png
└── ...
```
## File Descriptions
Each sample contains the following files:
### Core Files
- **`original_image.png`**: The input image to be edited
- **`meta_data.pkl`**: Annotation data containing editing instructions and metadata
- **`user_drag.png`**: Visualization of the original drag editing annotation
### Inpaint4Drag Annotations
- **`meta_data_i4p.pkl`**: Additional annotation for Inpaint4Drag method evaluation
- **`user_drag_i4p.png`**: Visualization of the Inpaint4Drag (I4P) annotation
## Metadata Format
### `meta_data.pkl`
```python
{
'prompt': str, # Text prompt describing the desired output image
'points': list, # Point coordinates [(x1,y1), (x2,y2), ..., (xn,yn)]
# Format: handle_point1, target_point1, handle_point2, target_point2, ...
'mask': array # Binary mask specifying the editable area
}
```
### `meta_data_i4p.pkl`
```python
{
'points': list, # Point coordinates with same editing intent as original annotation
'mask': array # Binary mask specifying the deformable region for I4P method
}
```