AnonymousSubmissionASE/pixels_vs_code

Pattern Over Pixels Screenshot-to-Code

This dataset contains controlled counterfactual screenshot-to-code examples built from 30 real-world webpages from Design2Code. Each example preserves a repeated UI pattern while introducing a single localized deviation, allowing researchers to test whether multimodal models follow the pixels or simply restore the dominant template.

Contents

• 720 perturbed HTML instances
• 360 structural-card examples
• 360 text-style examples
• 2 screenshot conditions per example:
  • standard_image
  • noise_image

Layout

hf_release/
  README.md
  .gitattributes
  data/
    examples.jsonl
  metadata/
    dataset_info.json
    validation_report.json
  html/
    cards/
    texts/
  images/
    cards/
      standard/
      noise/
    texts/
      standard/
      noise/

Row Schema

Each line in data/examples.jsonl is one perturbed HTML instance with both image conditions attached. Important fields include:

• example_id
• source_id
• pattern_family
• pattern_name
• attribute_name
• position
• target_value
• bias_value
• html_path
• standard_image
• noise_image
• code_snippet_line
• code_snippet_context

Loading

Load the local release folder with:

from datasets import load_dataset, Image

ds = load_dataset("json", data_files="data/examples.jsonl", split="train")
ds = ds.cast_column("standard_image", Image())
ds = ds.cast_column("noise_image", Image())

After pushing to the Hub with scripts/push_hf_dataset.py, load it with:

from datasets import load_dataset

ds = load_dataset("AnonymousSubmissionASE/pixels_vs_code", split="train")

Notes

• standard_image and noise_image are relative paths inside the dataset repo.
• The Hub push script materializes html_content and embeds image bytes into the Parquet shards so the hosted dataset is self-contained.
• This release is organized for public hosting and loading, not for regeneration.
• The underlying webpages originate from real-world websites. Check original website licenses and terms before downstream redistribution or commercial use.