---
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**](https://arxiv.org/abs/2409.14337)
**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:**
```csv
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`:
---
2. **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:**
```bash
pip install huggingface_hub
```
**Download specific files:**
```python
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:**
```python
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`:**
```bash
# 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](https://parquet.apache.org/docs).
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`](https://arrow.apache.org/docs/python/generated/pyarrow.parquet.ParquetFile.html) documentation to explore more APIs.
```bash
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},
}
```