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--- |
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language: [en] |
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license: mit |
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datasets: [MobileViews] |
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pretty_name: "MobileViews: A Large-Scale Mobile GUI Dataset" |
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tags: |
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- mobile-ui |
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- user-interfaces |
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- view-hierarchy |
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- android-apps |
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- screenshots |
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task_categories: |
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- question-answering |
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- image-to-text |
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task_ids: |
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- task-planning |
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- visual-question-answering |
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--- |
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# MobileViews: A Large-Scale Mobile GUI Dataset |
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[**Read the paper**](https://arxiv.org/abs/2409.14337) |
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**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. |
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## Dataset Overview |
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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. |
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- **`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. |
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- **`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. |
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- **`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. |
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- **`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. |
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- **`AppMetadata.csv`**: Metadata for **15,000 apps** from the Google Play Store, retrieved in **June 2024**. |
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### CSV and Parquet Column Descriptions |
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Both the CSV and Parquet files provide mappings between images and JSON view hierarchy files. |
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1. **CSV Columns** |
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| Column | Description | |
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|--------------|-------------------------------------------| |
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| `Image File` | Filename of the screenshot (e.g., 0.jpg) | |
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| `JSON File` | Filename of the view hierarchy (e.g., 0.json) | |
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**Example:** |
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```csv |
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Image File,JSON File |
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300000.jpg,300000.json |
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300001.jpg,300001.json |
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300002.jpg,300002.json |
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``` |
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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`: |
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--- |
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2. **Parquet Columns** |
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| Column | Description | |
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|-----------------|--------------------------------------------------------------------------| |
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| `image_content` | Binary data representing the image file (e.g., screenshot in `.jpg` format) | |
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| `json_content` | JSON content representing the view hierarchy for the corresponding image | |
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**Example Data in Parquet:** |
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| image_content | json_content | |
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|------------------------|----------------------------------------------------------------------| |
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| Binary image data | `{"viewHierarchy": {"bounds": [0, 0, 1080, 1920], "viewClass": ...}` | |
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| Binary image data | `{"viewHierarchy": {"bounds": [0, 0, 1080, 1920], "viewClass": ...}` | |
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| Binary image data | `{"viewHierarchy": {"bounds": [0, 0, 1080, 1920], "viewClass": ...}` | |
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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. |
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### AppMetadata.csv Columns |
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The `AppMetadata.csv` file contains detailed information about each app. The columns are as follows: |
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| Column | Description | |
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|---------------------|------------------------------------------------------------------| |
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| `title` | App title | |
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| `installs` | Number of installs | |
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| `minInstalls` | Minimum number of installs | |
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| `realInstalls` | Real number of installs | |
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| `score` | App score (rating) | |
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| `ratings` | Number of ratings | |
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| `reviews` | Number of reviews | |
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| `histogram` | Rating distribution | |
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| `price` | App price | |
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| `free` | Whether the app is free (True/False) | |
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| `offersIAP` | Offers in-app purchases (True/False) | |
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| `inAppProductPrice` | In-app product price | |
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| `developer` | Developer name | |
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| `developerId` | Developer ID | |
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| `genre` | App genre | |
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| `genreId` | Genre ID | |
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| `categories` | App categories | |
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| `contentRating` | Content rating (e.g., Everyone, Teen) | |
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| `adSupported` | Indicates if the app is ad-supported (True/False) | |
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| `containsAds` | Indicates if the app contains ads (True/False) | |
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| `released` | App release date | |
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| `lastUpdatedOn` | Date of the latest update | |
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| `appId` | Unique app identifier | |
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## How to Use |
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### Download via Hugging Face Python Library |
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**Install the library:** |
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```bash |
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pip install huggingface_hub |
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``` |
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**Download specific files:** |
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```python |
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from huggingface_hub import hf_hub_download |
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# Download specific files |
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hf_hub_download(repo_id="mllmTeam/MobileViews", filename="MobileViews_0-150000.parquet") |
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hf_hub_download(repo_id="mllmTeam/MobileViews", filename="MobileViews_0-150000.zip") |
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hf_hub_download(repo_id="mllmTeam/MobileViews", filename="AppMetadata.csv") |
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``` |
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**Download the entire repository:** |
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```python |
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from huggingface_hub import snapshot_download |
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# Download the entire repository |
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snapshot_download(repo_id="mllmTeam/MobileViews") |
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``` |
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### The usage of `zip` files |
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We recommend verifying the completeness and integrity of the files before unzipping them by following these steps. |
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**Example for `MobileViews_0-150000.zip`:** |
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```bash |
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# Integrity check |
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zip -T MobileViews_0-150000.zip # Expected output: test of MobileViews_0-150000.zip OK |
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# Verify file counts (JSON and JPG) |
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unzip -l MobileViews_0-150000.zip | grep ".json" | wc -l # Expected output: 150001 |
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unzip -l MobileViews_0-150000.zip | grep ".jpg" | wc -l # Expected output: 150001 |
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# Verify file size |
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du -sh MobileViews_0-150000.zip # Expected output: 23G |
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# Verify SHA256 checksum |
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sha256sum -c MobileViews_0-150000.zip.sha256 # Expected output: MobileViews_0-150000.zip: OK |
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# Unzip |
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unzip MobileViews_0-150000.zip |
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``` |
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**Expected Outputs for Other ZIP Files:** |
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- **MobileViews_150001-291197.zip**: |
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- Integrity: `test of MobileViews_150001-291197.zip OK` |
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- JSON count: `141197` |
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- JPG count: `141197` |
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- Size: `36G` |
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- SHA256: `MobileViews_150001-291197.zip: OK` |
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- **MobileViews_300000-400000.zip**: |
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- Integrity: `test of MobileViews_300000-400000.zip OK` |
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- JSON count: `100001` |
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- JPG count: `100001` |
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- Size: `24G` |
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- SHA256: `MobileViews_300000-400000.zip: OK` |
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- **MobileViews_400001-522301.zip**: |
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- Integrity: `test of MobileViews_400001-522301.zip OK` |
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- JSON count: `122301` |
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- JPG count: `122301` |
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- Size: `13G` |
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- SHA256: `MobileViews_400001-522301.zip: OK` |
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## The usage of `parquet` files |
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`Parquet` is an efficient, compressed columnar storage format optimized for large datasets. You can learn more about [Parquet](https://parquet.apache.org/docs). |
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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. |
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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. |
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```bash |
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pip install pyarrow |
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# check the path and the function you need |
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python path/to/useparquet.py |
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``` |
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## Citation |
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If you use this dataset in your research, please cite our work as follows: |
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``` |
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@misc{gao2024mobileviewslargescalemobilegui, |
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title={MobileViews: A Large-Scale Mobile GUI Dataset}, |
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author={Longxi Gao and Li Zhang and Shihe Wang and Shangguang Wang and Yuanchun Li and Mengwei Xu}, |
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year={2024}, |
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eprint={2409.14337}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.HC}, |
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url={https://arxiv.org/abs/2409.14337}, |
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} |
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``` |
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