Datasets:
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 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 datasetand_ctrl_test.json: Test/evaluation datasetdownload_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:
{
"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:
Create the image directory:
mkdir -p data/and_ctrlDownload images: Run the provided
download_android_control.ipynbnotebook 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.jsonfile with the processed data
- Download TFRecord files from Google Storage (
Dataset files:
- Images: Stored in
data/and_ctrl/folder - Training dataset:
and_ctrl_train.jsonindata/datasets/ - Test dataset:
and_ctrl_test.jsonindata/datasets/
- Images: Stored in
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
The Android Control dataset was created by Google Research for advancing mobile UI understanding and automation research.
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