📢 [Project Page] [Blog Post] [Models] [Huggingface demo]
OmniParser is a comprehensive method for parsing user interface screenshots into structured and easy-to-understand elements, which significantly enhances the ability of GPT-4V to generate actions that can be accurately grounded in the corresponding regions of the interface.
Install environment:
conda create -n "omni" python==3.12
conda activate omni
pip install -r requirements.txt
Then download the model ckpts files in: https://huggingface.co/microsoft/OmniParser, and put them under weights/, default folder structure is: weights/icon_detect, weights/icon_caption_florence, weights/icon_caption_blip2.
Finally, convert the safetensor to .pt file.
python weights/convert_safetensor_to_pt.py
We put together a few simple examples in the demo.ipynb.
To run gradio demo, simply run:
python gradio_demo.py
For the model checkpoints on huggingface model hub, please note that icon_detect model is under AGPL license since it is a license inherited from the original yolo model. And icon_caption_blip2 & icon_caption_florence is under MIT license. Please refer to the LICENSE file in the folder of each model: https://huggingface.co/microsoft/OmniParser.
Our technical report can be found here. If you find our work useful, please consider citing our work:
@misc{lu2024omniparserpurevisionbased,
title={OmniParser for Pure Vision Based GUI Agent},
author={Yadong Lu and Jianwei Yang and Yelong Shen and Ahmed Awadallah},
year={2024},
eprint={2408.00203},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2408.00203},
}