e1879/showui-web-processed
ShowUI-Web Processed Flattened, normalized, and scenario-split version of 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… See the full description on the dataset page: https://huggingface.co/datasets/e1879/showui-web-processed.
ShowUI-Web Processed
Flattened, normalized, and scenario-split version of showlab/ShowUI-web.
Each row is a single (instruction, UI element) pair with normalized bounding-box coordinates.
Schema
Splits
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 splitsplits/val.parquet— validation splitsplits/test.parquet— test splitsplits/splits.json— split metadataimages/...— 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:
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:
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:
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
