AI Clothing Graffiti Project: Implementation and Optimization of AIGC Technology in Taobao Life 2

This article introduces the AI clothing graffiti project in Taobao Life 2, an application that uses AI to provide users with rich and interesting interactive content. The project aims to enhance user participation and sense of achievement by allowing users to create and generate clothing through AI technology.

The article covers the technical background, including Stable Diffusion (SD), ControlNet, and LoRA technologies. It explains how SD works as a text-to-image generation model based on Latent Diffusion Models, and how ControlNet enables more controllable image generation by adding additional input conditions. LoRA is introduced as a low-rank adaptation method that significantly reduces computational costs for fine-tuning large models.

The implementation details of the clothing graffiti project are discussed, including the use of SD with ControlNet for text+image+control conditions to stylize user graffiti. The article also covers the deployment of the image generation service, model management strategies, and various optimizations such as parallel processing for generating multiple images, face repair, and sensitive content filtering.

The project has been successfully launched and received positive user feedback, with users creating impressive graffiti-generated clothing designs. The article concludes with a call for algorithm engineers interested in search recommendation and AIGC technologies to join the team.