README.md

metadata

license: mit
task_categories:
  - object-detection
tags:
  - ui
  - user-interface
  - web-design
  - gui
pretty_name: Web UI Dataset
size_categories:
  - n<1K
language:
  - ru
  - en

Web UI Dataset

Dataset Description

This dataset consists of real-world screenshots of web user interfaces, annotated for object detection. It is designed to be used in pair with the Synthetic UI Dataset for fine-tuning and model validation.

• Total Images: 250
• Task: Object Detection
• Source: Annotation of websites screenshots

Dataset Structure

Classes

The dataset annotates 6 distinct classes of UI elements:

1. button: Buttons of various styles.
2. input: Input fields, text areas, and dropdown lists.
3. checkbox: Selection elements including checkboxes, radio buttons, and switches/toggles.
4. image: Visual content including standard images, user avatars, and banners.
5. header: Visual headers and highlights.
6. text: Text content blocks, paragraphs, labels, and descriptions.

Data Splits

The dataset is split into training and validation sets with a 90/10 ratio:

Split	Percentage	Number of Images
Train	80%	185
Validation	20%	45

Usage

from datasets import load_dataset

dataset = load_dataset("egnch/real-ui")

# Example: View the first training example
print(dataset["train"][0])

Additional Information

Annotation Distribution

Class Label	Description	Count	Distribution (Approx.)
text	Text content blocks, paragraphs, labels	2938	~50%
button	Buttons of various styles	955	~15%
image	Visual content, avatars, banners	508	~10%
header	Visual headers and highlights	446	~10%
input	Input fields, text areas, dropdowns	431	~10%
checkbox	Checkboxes, radio buttons, switches	263	~5%

Licensing

This dataset is licensed under the MIT License.