Android-Control-84k / README.md
OfficerChul's picture
Upload folder using huggingface_hub
8d778a0 verified
|
raw
history blame
4.3 kB
metadata
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 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:

{
  "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:

    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

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