SegAgent is a Python framework that orchestrates AI agents to perform semantic image segmentation through natural language interaction. By combining GPT-based language understanding with the Segment Anything Model (SAM), it converts user prompts—such as “segment the tumor region” or “refine around the edges”—into accurate masks. The agent retains conversational context, supports iterative refinement of segmentation results, and can integrate custom models or post-processing steps. It provides an extensible API, command-line tools, and Jupyter notebook examples. SegAgent accelerates annotation workflows, reduces manual tracing effort, and allows developers to embed conversational segmentation capabilities into broader pipelines or applications.

Magic Copy transforms the way users interact with images by offering a 'Magic Copy' option in the context menu. This functionality enables users to select specific parts of an image, effectively removing background noise and allowing for precise copying. Powered by Meta's advanced Segment Anything Model (SAM), it offers high accuracy in object detection and segmentation, thus enhancing user productivity. With Magic Copy, anyone can copy images exactly as they see fit, making it an invaluable tool for students, creators, and professionals alike.