Image In Words utilizes advanced generative models to analyze images, producing ultra-detailed textual descriptions. This innovative solution is perfect for various applications, such as content creation, accessibility, and improved understanding of visual data. By harnessing the power of artificial intelligence, Image In Words ensures accuracy and depth in its text output, making it a valuable tool for professionals, educators, and anyone needing text extracted or generated from visuals.

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.