metadata

language:
  - en
license: mit
datasets:
  - MobileViews
pretty_name: 'MobileViews: A Large-Scale Mobile GUI Dataset'
tags:
  - mobile-ui
  - user-interfaces
  - view-hierarchy
  - android-apps
  - screenshots
task_categories:
  - question-answering
  - image-to-text
task_ids:
  - task-planning
  - visual-question-answering

MobileViews: A Large-Scale Mobile GUI Dataset

Read the paper

MobileViews is a large-scale dataset designed to support research in mobile user interface (UI) analysis and mobile agents. Our first version — MobileViews-600K — contains over 600,000 mobile UI screenshot-view hierarchy (VH) pairs, collected from approximately 20,000 apps on the Google Play Store.

Dataset Overview

The dataset consists of multiple .tar.gz files containing screenshot-VH pairs and corresponding CSV index files that map each screenshot to its VH:

MobileViews_0-291197.tar.gz and MobileViews_index_0-291197.csv: The first set of screenshot-VH pairs, containing IDs from 0 to 291197.
MobileViews_300000-522301.tar.gz and MobileViews_index_300000-522301.csv: The second set of screenshot-VH pairs, containing IDs from 300000 to 522301.
AppMetadata.csv: App metadata for 15,000 apps from the Google Play Store, retrieved in June 2024.

Index CSV Columns

Each index CSV file contains the following columns, mapping each screenshot to its corresponding view hierarchy:

Column	Description
`Image File`	Filename of the screenshot (e.g., 0.jpg)
`JSON File`	Filename of the view hierarchy (e.g., 0.json)

Example:

Image File,JSON File
300000.jpg,300000.json
300001.jpg,300001.json
300002.jpg,300002.json

Each .tar.gz file contains both the screenshots (JPG) and view hierarchy files (JSON).

AppMetadata.csv Columns

The AppMetadata.csv file contains detailed information about each app. The columns are as follows:

Column	Description
`title`	App title
`installs`	Number of installs
`minInstalls`	Minimum number of installs
`realInstalls`	Real number of installs
`score`	App score (rating)
`ratings`	Number of ratings
`reviews`	Number of reviews
`histogram`	Rating distribution
`price`	App price
`free`	Indicates if the app is free (True/False)
`offersIAP`	Offers in-app purchases (True/False)
`inAppProductPrice`	In-app product price
`developer`	Developer name
`developerId`	Developer ID
`genre`	App genre
`genreId`	Genre ID
`categories`	App categories
`contentRating`	Content rating (e.g., Everyone, Teen)
`adSupported`	Indicates if the app is ad-supported (True/False)
`containsAds`	Indicates if the app contains ads (True/False)
`released`	App release date
`lastUpdatedOn`	Date of the latest update
`appId`	Unique app identifier

How to Use

To access and use the MobileViews dataset, follow these steps:

Clone the Repository and Download the Dataset Files:

Use Git and Git LFS to clone the repository and ensure that large files (such as .tar.gz) are correctly pulled from Git LFS:
```
git clone https://huggingface.co/datasets/mllmTeam/MobileViews
cd /path/to/MobileViews
git lfs pull
```
Verify the Downloaded File Sizes:

After running git lfs pull, use the following command to verify that the downloaded file sizes match the expected sizes:
```
du -sh /path/to/downloaded/file
```
The correct file sizes are:
- MobileViews_0-291197.tar.gz: 11.9 GB
- MobileViews_300000-522301.tar.gz: 11 GB
If the sizes do not match, please rerun git lfs pull to ensure the files are fully downloaded.

Extract the Dataset Files:

The .tar.gz files contain the screenshot-view hierarchy (VH) pairs. Use the following commands to extract the files:

# Extract the first set of data
tar -xzvf MobileViews_0-291197.tar.gz

# Extract the second set of data
tar -xzvf MobileViews_300000-522301.tar.gz

Use the CSV Index Files: Each .tar.gz file has an associated CSV index file that maps the screenshots to their corresponding view hierarchy files (JSON). You can use the index CSV file to match each pair based on their IDs.

Citation

@misc{gao2024mobileviewslargescalemobilegui,
      title={MobileViews: A Large-Scale Mobile GUI Dataset}, 
      author={Longxi Gao and Li Zhang and Shihe Wang and Shangguang Wang and Yuanchun Li and Mengwei Xu},
      year={2024},
      eprint={2409.14337},
      archivePrefix={arXiv},
      primaryClass={cs.HC},
      url={https://arxiv.org/abs/2409.14337}, 
}