An artificial intelligence stylized painting system based on the aesthetic gradient method
At present it is difficult for artificial intelligence painting models such as Stable diffusion to directly control image style in painting.At the same time,current style model training is focused on a single style.To address this issue,an artificial intelligence stylized painting system based on the aesthetic gradient method was proposed.It aimed to achieve control and integration of multiple image styles,and to provide a more convenient image creation experience.It collected and analyzed network user data and employed a questionnaire-based approach to obtain the user's perceptual needs for image style.Furthermore,it collected the data of each style image according to the perceptual requirements to obtain the corresponding style image training set.It also used the gradient descent algorithm to calculate the weights of the stylized text encoder to achieve the effect of generating image stylization.A usability test was conducted to compare user satisfaction with the image styles produced by the traditional artificial intelligence painting system and the artificial intelligence stylized painting system.The results show that the average satisfaction of the latter is 23％higher than that of the former,indicating that artificial intelligence stylized painting system has better effects in image style generation and can effectively meet users'needs for image styles.This artificial intelligence stylized painting system can realize image style adjustment more easily,allow users to intuitively choose the weight of different styles and easily use one or more styles,and can effectively meet users'needs for image style design.
NETL
NSTL
万方数据
