Children bed design effect diagram based on ControlNet
Product design renderings have an important impact on designers'plans and final product presentation.There-fore,the rapid generation of high-quality renderings for improving design efficiency and promoting the development of the design industry is of great significance.The traditional rendering method of product design renderings needs to con-figure the elements of 3D model,such as material,lighting and background,and use complex algorithms to obtain re-alistic renderings,the resulting renderings have some problems in terms of light and shadow,and often cannot express the lighting,material,and texture details of the real world perfectly.Therefore,in order to solve the problems of tra-ditional rendering methods of product design renderings,such as time-consuming,high cost and low quality,deep learning-based image generation technology has become one of the development directions of the furniture industry.The development of deep learning technology provides a new idea for high-quality image generation,and the rapid generation of product design renderings through computer generation technology can further improve the efficiency of product design,reduce the intensity of manual labor.In this study,a method of generating children bed design effect graph using ControlNet,which is a neural network computing platform,is proposed.Firstly,Canny edge detection al-gorithm is used to process the original images and obtain the corresponding edge images.Then,the feature is extracted from the edge image using the control branch network.Finally,the extracted edge features are fused into the feature layer of the original diffusion model and used as a condition to control the generating process of ControlNet.By setting different seeds of random number,the target image with the same structure but different color matching can be genera-ted.Based on Fréchet Inception Distance(FID)and Inception Score,the results show that the images generated by ControlNet not only have better diversity than those generated by CycleGan,ChipGan and Style2Paints,the image de-tail quality is also improved,which proves the validity and rationality of the applied model.At the same time,the effect diagram method of children bed design based on ControlNet is evaluated by experts,and the result proves the reliability and applicability of the method.It is feasible to apply ControlNet to children bed design,which could not only provide inspiration for designers,but also save human and material cost and improve design efficiency.
children bed design diagramControlNet algorithmgenerate antagonism networkproduct designimage generation
万方数据
维普
