MobileViews / README.md
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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 on mobile user interface (UI) analysis and mobile agents. The 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 zip and parquet files with the same index contain the same screenshots and VH files, so you can choose whichever format you prefer to download and use.

  • MobileViews_0-150000.zip, MobileViews_0-150000.parquet and MobileViews_index_0-150000.csv: The first set of screenshot-VH pairs, containing IDs from 0 to 150,000.

  • MobileViews_150001-291197.zip, MobileViews_150001-291197.parquet and MobileViews_index_150001-291197.csv: The second set of screenshot-VH pairs, containing IDs from 150,001 to 291,197.

  • MobileViews_300000-400000.zip, MobileViews_300000-400000.parquet and MobileViews_index_300000-400000.csv: The third set of screenshot-VH pairs, containing IDs from 300,000 to 400,000.

  • MobileViews_400001-522301.zip, MobileViews_400001-522301.parquet and MobileViews_index_400001-522301.csv: The fourth set of screenshot-VH pairs, containing IDs from 400,001 to 522,301.

  • AppMetadata.csv: Metadata for 15,000 apps from the Google Play Store, retrieved in June 2024.

CSV and Parquet Column Descriptions

Both the CSV and Parquet files provide mappings between images and JSON view hierarchy files.

  1. CSV Columns

    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
    

Here’s the updated section of the README for the MobileViews open-sourced dataset, modified to reflect that the Parquet columns are image_content and json_content instead of image_path:


  1. Parquet Columns

    Column Description
    image_content Binary data representing the image file (e.g., screenshot in .jpg format)
    json_content JSON content representing the view hierarchy for the corresponding image

    Example Data in Parquet:

    image_content json_content
    Binary image data {"viewHierarchy": {"bounds": [0, 0, 1080, 1920], "viewClass": ...}
    Binary image data {"viewHierarchy": {"bounds": [0, 0, 1080, 1920], "viewClass": ...}
    Binary image data {"viewHierarchy": {"bounds": [0, 0, 1080, 1920], "viewClass": ...}

    The image_content column contains the binary image data for each screenshot, which can be converted back into a .jpg image. The json_content column stores the JSON string with the view hierarchy details for each corresponding image.

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 Whether 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

Download via Hugging Face Python Library

Install the library:

pip install huggingface_hub

Download specific files:

from huggingface_hub import hf_hub_download

# Download specific files
hf_hub_download(repo_id="mllmTeam/MobileViews", filename="MobileViews_0-150000.parquet")
hf_hub_download(repo_id="mllmTeam/MobileViews", filename="MobileViews_0-150000.zip")
hf_hub_download(repo_id="mllmTeam/MobileViews", filename="AppMetadata.csv")

Download the entire repository:

from huggingface_hub import snapshot_download

# Download the entire repository
snapshot_download(repo_id="mllmTeam/MobileViews")

The usage of zip files

We recommend verifying the completeness and integrity of the files before unzipping them by following these steps.

Example for MobileViews_0-150000.zip:

# Integrity check
zip -T MobileViews_0-150000.zip   # Expected output: test of MobileViews_0-150000.zip OK

# Verify file counts (JSON and JPG)
unzip -l MobileViews_0-150000.zip | grep ".json" | wc -l  # Expected output: 150001
unzip -l MobileViews_0-150000.zip | grep ".jpg" | wc -l   # Expected output: 150001

# Verify file size
du -sh MobileViews_0-150000.zip  # Expected output: 23G

# Verify SHA256 checksum
sha256sum -c MobileViews_0-150000.zip.sha256  # Expected output: MobileViews_0-150000.zip: OK

# Unzip
unzip MobileViews_0-150000.zip

Expected Outputs for Other ZIP Files:

  • MobileViews_150001-291197.zip:

    • Integrity: test of MobileViews_150001-291197.zip OK
    • JSON count: 141197
    • JPG count: 141197
    • Size: 36G
    • SHA256: MobileViews_150001-291197.zip: OK
  • MobileViews_300000-400000.zip:

    • Integrity: test of MobileViews_300000-400000.zip OK
    • JSON count: 100001
    • JPG count: 100001
    • Size: 24G
    • SHA256: MobileViews_300000-400000.zip: OK
  • MobileViews_400001-522301.zip:

    • Integrity: test of MobileViews_400001-522301.zip OK
    • JSON count: 122301
    • JPG count: 122301
    • Size: 13G
    • SHA256: MobileViews_400001-522301.zip: OK

The usage of parquet files

Parquet is an efficient, compressed columnar storage format optimized for large datasets. You can learn more about Parquet.

We provide useparquet.py, which includes functions such as check_row_count, save_n_images_and_jsons, and save_all_images_and_jsons to help you quickly access the dataset.

If you need additional functionality, you can refer to the pyarrow documentation to explore more APIs.

pip install pyarrow

# check the path and the function you need
python path/to/useparquet.py

Citation

If you use this dataset in your research, please cite our work as follows:

@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}, 
}