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| license: apache-2.0 | |
| task_categories: | |
| - visual-question-answering | |
| - image-to-text | |
| language: | |
| - en | |
| tags: | |
| - mobile-ui | |
| - gui-grounding | |
| - android | |
| - ui-automation | |
| - multimodal | |
| size_categories: | |
| - 10K<n<100K | |
| pretty_name: Android Control Dataset for LLaMA-Factory | |
| # Android Control Dataset | |
| ## Overview | |
| This directory contains two dataset files (`and_ctrl_train.json` and `and_ctrl_test.json`) derived from the [Android Control](https://github.com/google-research/google-research/tree/master/android_control) project by Google Research. These datasets have been formatted specifically for GUI grounding training in LLaMA-Factory. | |
| ## Dataset Description | |
| The Android Control dataset consists of episodes where each episode contains multiple steps. Each step includes: | |
| - **Step instructions**: Natural language instructions for UI interactions | |
| - **Actions**: The type of action to perform (click, scroll, input text, etc.) | |
| - **Coordinates**: Precise x, y coordinates for the action | |
| The data has been extracted and formatted to train models for mobile UI understanding and interaction tasks. | |
| ## Files | |
| - `and_ctrl_train.json`: Training dataset | |
| - `and_ctrl_test.json`: Test/evaluation dataset | |
| - `download_android_control.ipynb`: Jupyter notebook for downloading images and processing the original data | |
| ## Data Format | |
| Each entry in the JSON files follows the LLaMA-Factory conversation format: | |
| ```json | |
| { | |
| "messages": [ | |
| { | |
| "role": "system", | |
| "content": "You are a helpful assistant that can identify what action to perform on mobile UI Screenshot given the user instruction." | |
| }, | |
| { | |
| "role": "user", | |
| "content": "<image>Click on the Recording 2" | |
| }, | |
| { | |
| "role": "assistant", | |
| "content": "{\"action_type\": \"click\", \"x\": 561, \"y\": 535}" | |
| } | |
| ], | |
| "images": ["and_ctrl/out_episode_18557_step_001.png"] | |
| } | |
| ``` | |
| ## Setup Instructions | |
| To use these datasets in LLaMA-Factory: | |
| 1. **Create the image directory**: | |
| ```bash | |
| mkdir -p data/and_ctrl | |
| ``` | |
| 2. **Download images**: | |
| Run the provided `download_android_control.ipynb` notebook to download and process the original images. The notebook will: | |
| - Download TFRecord files from Google Storage (`gs://gresearch/android_control/`) | |
| - Extract images and save them directly to `and_ctrl/` directory | |
| - Automatically organize images with the naming convention: `out_episode_{episode_id}_step_{step_number}.png` | |
| - Generate an `and_ctrl.json` file with the processed data | |
| 3. **Dataset files**: | |
| - Images: Stored in `data/and_ctrl/` folder | |
| - Training dataset: `and_ctrl_train.json` in `data/datasets/` | |
| - Test dataset: `and_ctrl_test.json` in `data/datasets/` | |
| ## Dataset Statistics | |
| **Total samples**: Train: 82,944 | Test: 904 | |
| | Action Type | Train | Test | | |
| |-------------|-------|------| | |
| | click | 51,793 (62.44%) | 125 (13.83%) | | |
| | scroll | 11,005 (13.27%) | 125 (13.83%) | | |
| | input_text | 5,966 (7.19%) | 125 (13.83%) | | |
| | wait | 5,657 (6.82%) | 125 (13.83%) | | |
| | open_app | 5,572 (6.72%) | 125 (13.83%) | | |
| | navigate_back | 2,909 (3.51%) | 125 (13.83%) | | |
| | long_press | 42 (0.05%) | 125 (13.83%) | | |
| | navigate_home | 0 (0.00%) | 29 (3.21%) | | |
| **Note**: The training dataset shows a natural distribution with click actions being dominant (62.44%), while the test dataset is intentionally balanced with most action types having equal representation (~13.83% each). The `navigate_home` action appears only in the test set. | |
| ## Training Usage | |
| These datasets are specifically formatted for training multimodal language models to: | |
| - Understand mobile UI screenshots | |
| - Ground natural language instructions to specific UI elements | |
| - Generate precise action coordinates for UI automation | |
| - Learn mobile app interaction patterns | |
| ## Source and Attribution | |
| Original dataset: [Google Research Android Control](https://github.com/google-research/google-research/tree/master/android_control) | |
| The Android Control dataset was created by Google Research for advancing mobile UI understanding and automation research. | |
| ### License | |
| This dataset is derived from Google Research's Android Control dataset, which is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). The reformatted version for LLaMA-Factory maintains the same Apache 2.0 license terms. | |
| Copyright for the original dataset belongs to Google LLC. Any modifications or reformatting for LLaMA-Factory compatibility are also provided under Apache License 2.0. | |
| ## Notes | |
| - The images are referenced with relative paths starting with `and_ctrl/` | |
| - Each action includes the action type and necessary parameters (coordinates, text, direction, etc.) | |
| - The test set can be used for evaluating model performance on unseen mobile UI interactions |