The utilization of Large Language Models (LLMs) for the construction of AI systems has garnered significant attention across diverse fields. The extension of LLMs to the domain of fashion holds substantial commercial potential but also inherent challenges due to the intricate semantic interactions in fashion-related generation. To address this issue, we developed a hierarchical AI system called Fashion Matrix dedicated to editing photos by just talking. This system facilitates diverse prompt-driven tasks, encompassing garment or accessory replacement, recoloring, addition, and removal. Specifically, Fashion Matrix employs LLM as its foundational support and engages in iterative interactions with users. It employs a range of Semantic Segmentation Models (e.g., Grounded-SAM, MattingAnything, etc.) to delineate the specific editing masks based on user instructions. Subsequently, Visual Foundation Models (e.g., Stable Diffusion, ControlNet, etc.) are leveraged to generate edited images from text prompts and masks, thereby facilitating the automation of fashion editing processes. Experiments demonstrate the outstanding ability of Fashion Matrix to explores the collaborative potential of functionally diverse pre-trained models in the domain of fashion editing.

将大型语言模型（LLMs）用于构建人工智能系统在各个领域引起了广泛关注。我们开发了一种名为Fashion Matrix的分层人工智能系统，旨在通过语音进行照片编辑，以解决时尚相关生成中的复杂语义交互问题。Fashion Matrix利用LLM作为基础支持，并与用户进行迭代交互，利用语义分割模型和视觉基础模型实现基于用户指令的照片编辑。实验证明，Fashion Matrix在时尚编辑领域发挥了卓越的潜力。

时尚矩阵：通过对话进行照片编辑