README.md

metadata

configs:
  - config_name: default
    data_files:
      - split: test
        path: data_test.parquet
      - split: rest
        path: data_rest.parquet
    features:
      root: Image
      page_url: string
      annotation: string
      metadata: string
      image_refs:
        - path: string
          image: Image
      svg_assets:
        - path: string
          content: string

Figma2Code Dataset

This dataset contains preprocessed Figma design files for the task of generating UI code from Figma designs.

Dataset Structure

The dataset is divided into two splits: test and rest. Each sample in the dataset includes the following features:

• root: The main screenshot of the UI page as a PIL Image object.
• page_url: The original URL of the Figma page.
• annotation: A JSON string containing manual annotations about the UI's content and description.
• metadata: A JSON string containing the complete preprocessed Figma node tree and properties.
• image_refs: A list of dictionaries, where each dictionary contains the relative path and the image data (as a PIL Image) for bitmap assets.
• svg_assets: A list of dictionaries, where each dictionary contains the relative path and the string content for SVG vector assets.

How to Use

You can load the dataset using the datasets library:

from datasets import load_dataset

# Load the dataset
ds = load_dataset("anonymousauthor001/ds001")

# Access the different splits
test_split = ds["test"]
rest_split = ds["rest"]

# Get the first sample from the test split
sample = test_split[0]
print(sample.keys())
# dict_keys(['root', 'page_url', 'annotation', 'metadata', 'image_refs', 'svg_assets'])