README.md

---
language: [en]
license: cc-by-4.0
task_categories: [image-classification]
tags: [ui-grounding, web, showui, processed]
source_datasets: [showlab/ShowUI-web]
size_categories: [10K<n<100K]
---

# ShowUI-Web Processed

Flattened, normalized, and scenario-split version of [showlab/ShowUI-web](https://huggingface.co/datasets/showlab/ShowUI-web).

Each row is a single (instruction, UI element) pair with normalized bounding-box coordinates.

## Schema

| Column | Type | Description |
|---|---|---|
| `sample_id` | string | Unique row identifier (`{row}_{element}`) |
| `screenshot_id` | string | Groups elements from the same screenshot |
| `image_relpath` | string | Relative path to the screenshot image |
| `scenario` | string | Website/domain inferred from the image path |
| `instruction` | string | Natural-language grounding instruction |
| `bbox_xyxy` | list[float] | Normalized bounding box `[x1, y1, x2, y2]` in `[0, 1]` |
| `point_xy` | list[float] or null | Normalized click point `[x, y]` |
| `element_type` | string or null | UI element type label |

## Splits

| Split | Rows | Strategy |
|---|---|---|
| train | majority | Scenario-based holdout |
| validation | ~10% scenarios | Domain holdout |
| test | ~15% scenarios | Domain holdout |

## Repository Layout

The dataset repo contains both row-level parquet artifacts and image files:

- `flat.parquet` — full flattened table (all rows)
- `splits/train.parquet` — train split
- `splits/val.parquet` — validation split
- `splits/test.parquet` — test split
- `splits/splits.json` — split metadata
- `images/...` — screenshot and UI metadata files

## Images

Screenshot images are hosted in the `images/` directory of this repository.
Use `image_relpath` to construct the path or fetch individual images on demand:

```python
from huggingface_hub import hf_hub_download
from PIL import Image

path = hf_hub_download(
    repo_id="e1879/showui-web-processed",
    repo_type="dataset",
    filename=f"images/{row['image_relpath']}",
)
img = Image.open(path)
```

## Usage

Load train split via `datasets`:

```python
from datasets import load_dataset

ds = load_dataset("e1879/showui-web-processed")
print(ds["train"][0]["instruction"])
```

Or load parquet artifacts directly from the dataset repo:

```python
import pandas as pd
from huggingface_hub import hf_hub_download

train_path = hf_hub_download(
    repo_id="e1879/showui-web-processed",
    repo_type="dataset",
    filename="splits/train.parquet",
)
train_df = pd.read_parquet(train_path)
print(train_df.shape)
```

## Credit

Source dataset: [showlab/ShowUI-web](https://huggingface.co/datasets/showlab/ShowUI-web)