leosltl/Android-in-the-Wild
Android in the Wild (AITW) This is a mirror of Google's Android in the Wild (AITW) dataset, re-hosted on Hugging Face for easier community access. Original Source Paper: Android in the Wild: A Large-Scale Dataset for Android Device Control Original Repository: google-research/google-research/tree/master/android_in_the_wild Dataset Description Android in the Wild (AITW) is a large-scale dataset for Android device control. It contains human… See the full description on the dataset page: https://huggingface.co/datasets/leosltl/Android-in-the-Wild.
Android in the Wild (AITW)
This is a mirror of Google's Android in the Wild (AITW) dataset, re-hosted on Hugging Face for easier community access.
Original Source
- Paper: Android in the Wild: A Large-Scale Dataset for Android Device Control
- Original Repository: google-research/google-research/tree/master/android_in_the_wild
Dataset Description
Android in the Wild (AITW) is a large-scale dataset for Android device control. It contains human demonstrations of natural language instructions being carried out on Android devices. Each demonstration consists of a sequence of screenshots paired with corresponding actions (taps, swipes, types, etc.) and UI annotations.
Dataset Structure
The dataset is organized into 5 subsets, stored as gzip-compressed TFRecord files:
Additionally, the splits/ directory contains JSON files defining train/test splits:
standard.jsonunseen_android_version.jsonunseen_domain.jsonunseen_subject.jsonunseen_verb.json
Data Format
Each TFRecord contains examples with the following fields:
image/encoded— screenshot image (encoded)image/ui_annotations_ui_types— UI element type annotations (e.g.,ICON_STOP,ICON_V_BACKWARD)- Additional action and metadata fields
Usage
import tensorflow as tf
import gzip
def read_tfrecord(file_path):
with gzip.open(file_path, 'rb') as f:
raw = f.read()
dataset = tf.data.TFRecordDataset([file_path], compression_type='GZIP')
return datasetFor detailed usage instructions, refer to the original repository.
License
This dataset is licensed under CC BY 4.0, following the original release.
Citation
@article{rawles2023android,
title={Android in the Wild: A Large-Scale Dataset for Android Device Control},
author={Rawles, Christopher and Li, Alice and Rodriguez, Daniel and Ber, Oriana and Zitkovich, Brianna},
journal={arXiv preprint arXiv:2307.10088},
year={2023}
}Disclaimer
This is an unofficial mirror. All credit goes to the original authors at Google Research. This copy is provided solely to facilitate easier access for the research community.
