microsoft-omniparser-v2-0
Hugging FaceVersion: 3
OmniParser is a general screen parsing tool, which interprets/converts UI screenshot to structured format, to improve existing LLM based UI agent.
Training Datasets include: 1) an interactable icon detection dataset, which was curated from popular web pages and automatically annotated to highlight clickable and actionable regions, and 2) an icon description dataset, designed to associate each UI element with its corresponding function. This model hub includes a finetuned version of YOLOv8 and a finetuned Florence-2 base model on the above dataset respectively. For more details of the models used and finetuning, please refer to the paper .
Training Datasets include: 1) an interactable icon detection dataset, which was curated from popular web pages and automatically annotated to highlight clickable and actionable regions, and 2) an icon description dataset, designed to associate each UI element with its corresponding function. This model hub includes a finetuned version of YOLOv8 and a finetuned Florence-2 base model on the above dataset respectively. For more details of the models used and finetuning, please refer to the paper .
- Larger and cleaner set of icon caption + grounding dataset
- 60% improvement in latency compared to V1. Avg latency: 0.6s/frame on A100, 0.8s on single 4090.
- Strong performance: 39.6 average accuracy on ScreenSpot Pro
- Your agent only need one tool: 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. Check out our github repo for details.