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Showui
Overview :
ShowUI is a lightweight vision-language-action model specifically designed for GUI agents. By integrating visual input, language understanding, and action prediction, it allows computer interfaces to respond to user commands in a more natural way. The importance of ShowUI lies in its ability to enhance the efficiency and naturalness of human-computer interaction, particularly in the fields of graphical user interface automation and natural language processing. Developed by the showlab laboratory, this model is currently available on the Hugging Face platform for research and application.
Target Users :
The target audience includes developers, researchers, and tech enthusiasts interested in natural language processing and human-computer interaction. ShowUI is suitable for them because it offers a powerful tool for developing and researching visual and language-based interaction systems, applicable in various fields such as automated testing and intelligent assistants.
Use Cases
- Automate web operations such as filling out forms and clicking buttons using the ShowUI model.
- Utilize ShowUI for image recognition and command-based interface navigation.
- Integrate ShowUI into custom applications to provide a more natural user experience.
Features
- Vision-language-action model: Combines visual input, language understanding, and action prediction.
- GUI automation: Facilitates automated operations for graphical user interfaces.
- Model training and deployment: Supports model training and deployment on the Hugging Face platform.
- Multimodal input: Supports multimodal inputs of images and text.
- Action prediction: Capable of predicting interface operations corresponding to user commands.
- Interface operations: Supports various operations such as clicking, inputting, and selecting.
- Model fine-tuning: Provides fine-tuning code and instructions to meet specific application scenarios.
How to Use
1. Install dependencies: Use pip to install the dependencies listed in requirements.txt.
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2. Clone the repository: Use the git clone command to clone the ShowUI code repository.
3. Launch the interface: Run app.py to start the graphical interface of ShowUI.
4. Load the model: Use the Qwen2VLForConditionalGeneration class to load the pre-trained ShowUI model.
5. Interface operation: Execute interface operations by sending a list of messages containing system prompts, images, and queries.
6. Display results: Use the draw_point function to mark operational results on images, such as clicked locations.
7. Fine-tune the model: Fine-tune the model as needed to accommodate specific application scenarios.
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