readme

README.md

@@ -1,3 +1,4 @@
+
 ---
 language: [en]
 license: mit
@@ -19,37 +20,60 @@ task_ids:
 # 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 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.
-
+**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 dataset includes several `.zip` files, each containing screenshot-VH pairs and corresponding CSV index files, which map each screenshot to its respective view hierarchy (VH).
+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_0-150000.zip` (23 GB) and `MobileViews_index_0-150000.csv`: The first set of screenshot-VH pairs, containing IDs from 0 to 150000.
-- `MobileViews_150001-291197.zip` (36 GB) and `MobileViews_index_150001-291197.csv`: The second set of screenshot-VH pairs, containing IDs from 150001 to 291197.
-- `MobileViews_300000-522301.zip` (37 GB) and `MobileViews_index_300000-522301.csv`: The third 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**.
+- **`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.
 
-### Index CSV Columns
+- **`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.
 
-Each index CSV file contains the following columns, mapping each screenshot to its corresponding view hierarchy:
+- **`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.
 
-| Column       | Description                               |
-|--------------|-------------------------------------------|
-| `Image File` | Filename of the screenshot (e.g., 0.jpg)  |
-| `JSON File`  | Filename of the view hierarchy (e.g., 0.json) |
+- **`AppMetadata.csv`**: Metadata for **15,000 apps** from the Google Play Store, retrieved in **June 2024**.
 
-**Example:**
-```csv
-Image File,JSON File
-300000.jpg,300000.json
-300001.jpg,300001.json
-300002.jpg,300002.json
-```
+### CSV and Parquet Column Descriptions
+
+Both the CSV and Parquet files provide mappings between images and JSON view hierarchy files.
+
+1. **CSV Columns**
 
-Each `.zip` file contains both the screenshots (JPG) and view hierarchy files (JSON).
+    | 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
 
@@ -66,7 +90,7 @@ The `AppMetadata.csv` file contains detailed information about each app. The col
 | `reviews`           | Number of reviews                                                |
 | `histogram`         | Rating distribution                                              |
 | `price`             | App price                                                        |
-| `free`              | Indicates if the app is free (True/False)                        |
+| `free`              | Whether the app is free (True/False)                        |
 | `offersIAP`         | Offers in-app purchases (True/False)                             |
 | `inAppProductPrice` | In-app product price                                             |
 | `developer`         | Developer name                                                   |
@@ -81,101 +105,101 @@ The `AppMetadata.csv` file contains detailed information about each app. The col
 | `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
+```
 
-## How to Download
+**Download specific files:**
 
-You can download the dataset using the following methods:
+```python
+from huggingface_hub import hf_hub_download
 
-1. **Download via Web UI**:
-    
-    Hugging Face provides a direct download button for each file on the dataset page. Simply click the download button next to the desired `.zip` or `.csv` file.
-   
+# 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")
+```
 
-2. **Download via `wget`**:
+**Download the entire repository:**
 
-    You can also use `wget` to download the files, which allows you to resume the download if interrupted:
+```python
+from huggingface_hub import snapshot_download
 
-    ```bash
-    wget -c https://huggingface.co/datasets/mllmTeam/MobileViews/resolve/main/MobileViews_0-150000.zip
-    wget -c https://huggingface.co/datasets/mllmTeam/MobileViews/resolve/main/MobileViews_150001-291197.zip
-    wget -c https://huggingface.co/datasets/mllmTeam/MobileViews/resolve/main/MobileViews_300000-522301.zip
-    ```
+# Download the entire repository
+snapshot_download(repo_id="mllmTeam/MobileViews")
+```
 
-3. **Download via Git LFS**:
+### The usage of `zip` files
 
-    Alternatively, you can clone the repository and pull the large files via Git LFS:
+We recommend verifying the completeness and integrity of the files before unzipping them by following these steps.
 
-    ```bash
-    git clone https://huggingface.co/datasets/mllmTeam/MobileViews
-    cd MobileViews
-    git lfs pull
-    ```
+**Example for `MobileViews_0-150000.zip`:**
 
-## File Verification
+```bash
+# Integrity check
+zip -T MobileViews_0-150000.zip   # Expected output: test of MobileViews_0-150000.zip OK
 
-To ensure the downloaded files are complete and correct, you can verify them in multiple ways.
+# 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
 
-1. **Verify Integrity Using `zip -T`**:
-   
-    ```bash
-    zip -T MobileViews_0-150000.zip   # expected output: test of MobileViews_0-150000.zip OK
-    zip -T MobileViews_150001-291197.zip   # expected output: test of MobileViews_150001-291197.zip OK
-    zip -T MobileViews_300000-522301.zip # expected output: test of MobileViews_300000-522301.zip OK
-    ```
+# Verify file size
+du -sh MobileViews_0-150000.zip  # Expected output: 23G
 
-2. **Verify the Number of Files**:
-   
-    You can verify the number of `.jpg` and `.json` files inside the `.zip`:
-    
-    ```bash
-    # Check the number of JSON files
-    unzip -l MobileViews_0-150000.zip | grep ".json" | wc -l  # expected output: 150001
-    unzip -l MobileViews_150001-291197.zip | grep ".json" | wc -l  # expected output: 141197
-    unzip -l MobileViews_300000-522301.zip | grep ".json" | wc -l  # expected output: 222302
-
-    # Check the number of JPG files
-    unzip -l MobileViews_0-150000.zip | grep ".jpg" | wc -l  # expected output: 150001
-    unzip -l MobileViews_150001-291197.zip | grep ".jpg" | wc -l  # expected output: 141197
-    unzip -l MobileViews_300000-522301.zip | grep ".jpg" | wc -l  # expected output: 222302
-    ```
+# Verify SHA256 checksum
+sha256sum -c MobileViews_0-150000.zip.sha256  # Expected output: MobileViews_0-150000.zip: OK
 
-3. **Verify the File Size**:
+# Unzip
+unzip MobileViews_0-150000.zip
+```
 
-    You can verify that the file sizes match the expected sizes:
+**Expected Outputs for Other ZIP Files:**
 
-    ```bash
-    du -sh MobileViews_0-150000.zip  # expected output: 23G
-    du -sh MobileViews_150001-291197.zip  # expected output: 36G
-    du -sh MobileViews_300000-522301.zip  # expected output: 37G
-    ```
+- **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`
 
-4. **Verify Using SHA256**:
+- **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`
 
-    We provide SHA256 checksum files to verify the integrity of the downloaded .zip files:
+- **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`
 
-    ```bash 
-    sha256sum -c MobileViews_0-150000.zip.sha256  # expected output: MobileViews_0-150000.zip: OK
-    sha256sum -c MobileViews_150001-291197.zip.sha256  # expected output: MobileViews_150001-291197.zip: OK
-    sha256sum -c MobileViews_300000-522301.zip.sha256  # expected output: MobileViews_300000-522301.zip: OK
-    ```
+## The usage of `parquet` files
 
-    If the output shows `OK`, the file has been downloaded correctly.
+`Parquet` is an efficient, compressed columnar storage format optimized for large datasets. You can learn more about [Parquet](https://parquet.apache.org/docs).
 
-    If the verification result is not as expected, the download may be corrupted. Please try downloading the file again. If the issue persists, feel free to contact us at any time.
+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. 
 
-## How to Use
+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.
 
-  You can unpack the `.zip` files using the `unzip` command in the terminal or any other unzipping tool.
+```bash
+pip install pyarrow
 
-  ```bash
-  unzip MobileViews_0-150000.zip -d /path/to/extract/directory
-  unzip MobileViews_150001-291197.zip -d /path/to/extract/directory
-  unzip MobileViews_300000-522301.zip -d /path/to/extract/directory
-  ```
-  This will extract the contents to the specified directory.
+# 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,
@@ -187,4 +211,4 @@ To ensure the downloaded files are complete and correct, you can verify them in
       primaryClass={cs.HC},
       url={https://arxiv.org/abs/2409.14337}, 
 }
-```
+```