From feature recognition to image generation:Miao ethnic costume design based on the AIGC paradigm
Miao ethnic costumes constitute a vital component of China's ethnic costume system,carving out a significant market presence in the realm of commercial development.These costumes play a crucial role in cultural and tourism activities,with their distinctive characteristics not only fulfilling the yearnings of tourists for exotic experiences but also elevating the influence of Miao culture.However,the market is inundated with a plethora of homogeneous products.Ordinary designers may struggle to comprehend the profoundness of Miao culture,and inheritors of intangible cultural heritage find it challenging to balance the cultural preservation aspect with the commercial viability of garment design.The phenomenon of product homogenization poses a hindrance to the continued development of ethnic culture.The question of how to enrich Miao costume design and consistently offer diverse Miao costume products becomes a topic that warrants careful consideration.The emergence of the Latent Diffusion Model(LDM)has opened up new possibilities for traditional costume design.Based on the modernization needs of Miao ethnic costumes,the Latent Diffusion Model SD1.5 served as the foundational model.Analyzing identifiable features in Miao ethnic costumes from the perspectives of style,accessories,patterns,and color,and with them as criteria for selecting training set images,the study applied the Low-Rank Adaptation of Large Language Model(Lora)method to construct a few-sample style transfer model.The ultimate control of generated content was achieved through the use of Control Net.By establishing a multi-model combination process,inspirational samples were provided for the ready-to-wear design of Miao ethnic costumes.Experimental results indicate that,based on costume recognizability and using the Lora training method,only a small number of samples are needed to achieve the transfer of Miao ethnic costume features in the content generated by Stable Diffusion.The few-sample Miao style transfer model based on the recognizability of Miao ethnic costumes possesses certain advantages in reducing the amount of training materials,minimizing training steps,and shortening training time.It plays a positive role in enriching the ready-to-wear design of Miao intangible cultural heritage costumes.By introducing deep learning into the modernization of intangible cultural heritage costumes,the study aims to revitalize ethnic costumes through digital means.The application of Artificial Intelligence Generated Content(AIGC)is intended to provide more design inspiration for traditional intangible cultural heritage costume design,supporting its development towards ready-to-wear,diversification,and popularization.Intangible cultural heritage costumes can not only better integrate into modern fashion trends but also achieve diversity through innovative design to meet the needs of different groups.The digital approach not only improves the efficiency of costume design,but also injects new inspiration and elements into traditional craftsmanship,promoting the transformation and upgrading of ethnic costumes through digital means.
AIGCMiao ethnic groupintangible cultural heritage costumesfew-sample style transferStable DiffusionLoraassisted design
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