Search Results for "vision"

The Self-Operating Computer Framework is an innovative system that enables multimodal models to autonomously operate a computer by interpreting the screen and executing mouse and keyboard actions to achieve specified objectives. This framework is compatible with various multimodal models and currently integrates with GPT-4o, o1, Gemini Pro Vision, Claude 3, and LLaVa. Notably, it was the first known project to implement a multimodal model capable of viewing and controlling a computer screen. The framework supports features like Optical Character Recognition (OCR) and Set-of-Mark (SoM) prompting to enhance visual grounding capabilities. It is designed to be compatible with macOS, Windows, and Linux (with X server installed), and is released under the MIT license.

...Unlike traditional automation scripts that depend on brittle heuristics, Open-AutoGLM uses pretrained large language and vision-language models to interpret visual context and natural language instructions, giving the agent robust adaptability across apps and interfaces.

...It opens up as much learning power as possible for your own robots and precisely control every step of the AI processing pipeline. BotSharp is an open source machine learning framework for AI Bot platform builder. This project involves natural language understanding, computer vision and audio processing technologies, and aims to promote the development and application of intelligent robot assistants in information systems. Out-of-the-box machine learning algorithms allow ordinary programmers to develop artificial intelligence applications faster and easier. It's written in C# running on .Net Core that is full cross-platform framework. ...

UI-TARS Desktop is a graphical user interface (GUI) agent application that leverages the UI-TARS vision-language model to enable natural language control of computers. This cross-platform tool supports both Windows and macOS, allowing users to perform tasks through intuitive commands. Key features include screenshot-based visual recognition, precise mouse and keyboard control, and real-time feedback on actions. Provides immediate responses and visual feedback on actions performed. ...

OmniParser is a comprehensive method for parsing user interface screenshots into structured elements, significantly enhancing the ability of multimodal models like GPT-4 to generate actions accurately grounded in corresponding regions of the interface. It reliably identifies interactable icons within user interfaces and understands the semantics of various elements in a screenshot, associating intended actions with the correct screen regions. To achieve this, OmniParser curates an...