--- 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}, } ```