# OmniParser: Screen Parsing tool for Pure Vision Based GUI Agent
[](https://arxiv.org/abs/2408.00203)
[](https://opensource.org/licenses/MIT)
[[Project Page](https://microsoft.github.io/OmniParser/)] [[V2 Blog Post](https://www.microsoft.com/en-us/research/articles/omniparser-v2-turning-any-llm-into-a-computer-use-agent/)] [[Models V2](https://huggingface.co/microsoft/OmniParser-v2.0)] [[Models V1.5](https://huggingface.co/microsoft/OmniParser)] [[HuggingFace Space Demo](https://huggingface.co/spaces/microsoft/OmniParser-v2)]
**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.
## News
- [2025/3] We support local logging of trajecotry so that you can use OmniParser+OmniTool to build training data pipeline for your favorate agent in your domain. [Documentation WIP]
- [2025/3] We are gradually adding multi agents orchstration and improving user interface in OmniTool for better experience.
- [2025/2] We release OmniParser V2 [checkpoints](https://huggingface.co/microsoft/OmniParser-v2.0). [Watch Video](https://1drv.ms/v/c/650b027c18d5a573/EWXbVESKWo9Buu6OYCwg06wBeoM97C6EOTG6RjvWLEN1Qg?e=alnHGC)
- [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](https://1drv.ms/v/c/650b027c18d5a573/EehZ7RzY69ZHn-MeQHrnnR4BCj3by-cLLpUVlxMjF4O65Q?e=8LxMgX)
- [2025/1] V2 is coming. We achieve new state of the art results 39.5% on the new grounding benchmark [Screen Spot Pro](https://github.com/likaixin2000/ScreenSpot-Pro-GUI-Grounding/tree/main) with OmniParser v2 (will be released soon)! Read more details [here](https://github.com/microsoft/OmniParser/tree/master/docs/Evaluation.md).
- [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](https://huggingface.co/spaces/microsoft/OmniParser)! (stay tuned for OmniParser + Claude Computer Use)
- [2024/10] Both Interactive Region Detection Model and Icon functional description model are released! [Hugginface models](https://huggingface.co/microsoft/OmniParser)
- [2024/09] OmniParser achieves the best performance on [Windows Agent Arena](https://microsoft.github.io/WindowsAgentArena/)!
## Install
First clone the repo, and then install environment:
\`\`\`python
cd OmniParser
conda create -n "omni" python==3.12
conda activate omni
pip install -r requirements.txt
\`\`\`
Ensure you have the V2 weights downloaded in weights folder (ensure caption weights folder is called icon_caption_florence). If not download them with:
\`\`\`
# download the model checkpoints to local directory OmniParser/weights/
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
\`\`\`
## Examples:
We put together a few simple examples in the demo.ipynb.
## Gradio Demo
To run gradio demo, simply run:
\`\`\`python
python gradio_demo.py
\`\`\`
## Model Weights License
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.
## Citation
Our technical report can be found [here](https://arxiv.org/abs/2408.00203).
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\},
\}
\`\`\`
