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Omniparser V2.0
Overview :
OmniParser, developed by Microsoft, is an advanced image parsing technology designed to transform irregular screenshots into structured lists of elements, including the location of interactive areas and functional descriptions of icons. It achieves efficient parsing of UI interfaces through deep learning models like YOLOv8 and Florence-2. Its main advantages lie in its efficiency, accuracy, and broad applicability. OmniParser significantly enhances the performance of user interface agents based on large language models (LLMs), enabling them to better understand and interact with various user interfaces. It performs exceptionally well in various application scenarios, such as automated testing and intelligent assistant development. OmniParser's open-source nature and flexible licensing make it a powerful tool for developers and researchers alike.
Target Users :
OmniParser is ideal for developers, researchers, and enterprises needing to automate the parsing and manipulation of user interfaces. It helps accelerate the development of intelligent UI agents, increase work efficiency, and reduce development costs. For instance, in automated testing, OmniParser swiftly identifies and interacts with UI elements, boosting testing efficiency. In intelligent assistant development, it provides more accurate interface information to the assistant, enhancing user experience.
Use Cases
In automated testing, OmniParser can quickly identify UI elements and perform actions, improving testing efficiency.
In intelligent assistant development, OmniParser can provide assistants with more accurate interface information, enhancing the user experience.
In a Windows 11 virtual machine, use OmniParser and a selected vision model to control the interface and achieve automated operations.
Features
Converts UI screenshots into a structured format, extracting interactive areas and icon function descriptions.
Supports various large language models, such as OpenAI, DeepSeek, Qwen, etc., for seamless integration.
Offers efficient parsing performance with an average latency as low as 0.6 seconds/frame (A100).
Utilizes cleaner and larger datasets of icon descriptions and locations to enhance model performance.
Supports screenshot parsing from various devices and applications, including PCs and mobile phones.
Provides open-source code and detailed documentation for developers to conduct secondary development and customization.
How to Use
Visit the Hugging Face page to download the OmniParser-v2.0 model and related files.
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Choose a suitable large language model (LLM) for integration, such as OpenAI, DeepSeek, etc.
Fine-tune the model using the provided training dataset to adapt to specific application scenarios.
Input screenshots into the OmniParser model to obtain structured UI element information.
Develop corresponding automation scripts or intelligent assistant functions based on the parsing results.
In real-world applications, leverage the interface information provided by OmniParser to automate operations or interactions with the user interface.
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