alucent/mirror-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",
      "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

• box - This is the metadata used during evaluation. The json format file contains labels for the interactable elements on the screen and their corresponding bounding boxes. They shouldn't be used while inferencing on the test set.

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}
}