📢 [Project Page] [V2 Blog Post] [Models V2] [Models V1.5] [huggingface space (to be updated)]
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.
- [2025/2] We release OmniParser V2 checkpoints. Watch Video
- [2025/2] We introduce OmniTool: Control a Windows 11 VM with OmniParser + your vision model of choice. OmniTool supports out of the box the following large language models - OpenAI (4o/o1/o3-mini), DeepSeek (R1), Qwen (2.5VL) or Anthropic Computer Use. Watch Video
- [2025/1] V2 is coming. We achieve new state of the art results 39.5% on the new grounding benchmark Screen Spot Pro with OmniParser v2 (will be released soon)! Read more details here.
- [2024/11] We release an updated version, OmniParser V1.5 which features 1) more fine grained/small icon detection, 2) prediction of whether each screen element is interactable or not. Examples in the demo.ipynb.
- [2024/10] OmniParser was the #1 trending model on huggingface model hub (starting 10/29/2024).
- [2024/10] Feel free to checkout our demo on huggingface space! (stay tuned for OmniParser + Claude Computer Use)
- [2024/10] Both Interactive Region Detection Model and Icon functional description model are released! Hugginface models
- [2024/09] OmniParser achieves the best performance on Windows Agent Arena!
Install environment:
conda create -n "omni" python==3.12
conda activate omni
pip install -r requirements.txtEnsure you have the V2 weights downloaded in weights folder (ensure caption weights folder is called icon_caption_florence). If not download them with:
rm -rf weights/icon_detect weights/icon_caption weights/icon_caption_florence
for f in icon_detect/{train_args.yaml,model.pt,model.yaml} icon_caption/{config.json,generation_config.json,model.safetensors}; do huggingface-cli download microsoft/OmniParser-v2.0 "$f" --local-dir weights; done
mv weights/icon_caption weights/icon_caption_florence
We put together a few simple examples in the demo.ipynb.
To run gradio demo, simply run:
python gradio_demo.pyFor 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},
}