metadata
license: mit
task_categories:
- text-generation
language:
- en
tags:
- code
pretty_name: OmniACT
Dataset for OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web
Splits:
| split_name | count |
|---|---|
| train | 6788 |
| test | 2020 |
| val | 991 |
Example datapoint:
"2849": {
"task": "data/tasks/desktop/ibooks/task_1.30.txt",
"image": "data/data/desktop/ibooks/screen_1.png",
"ocr": "ocr/desktop/ibooks/screen_1.json",
"color": "detact_color/desktop/ibooks/screen_1.json",
"icon": "detact_icon/desktop/ibooks/screen_1.json",
"box": "data/metadata/desktop/boxes/ibooks/screen_1.json"
},
where:
task- contains natural language description ("Task") along with the corresponding PyAutoGUI code ("Output Script"):
Task: Navigate to see the upcoming titles
Output Script:
pyautogui.moveTo(1881.5,1116.0)
image- screen image where the action is performed
To cite OmniACT, please use:
@misc{kapoor2024omniact,
title={OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web},
author={Raghav Kapoor and Yash Parag Butala and Melisa Russak and Jing Yu Koh and Kiran Kamble and Waseem Alshikh and Ruslan Salakhutdinov},
year={2024},
eprint={2402.17553},
archivePrefix={arXiv},
primaryClass={cs.AI}
}