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This application discloses an automated rendering optimization method based on visual UI. The method provides optimization for rendering images containing text content. To obtain a rendered image that achieves the desired effect in terms of graphic content, text content, and the fusion between the two, the fusion degree between the two is quantified during sample construction. This helps to convey information while expressing the aesthetic appeal of the image and restoring the designer's intention. Furthermore, the sample labels also indicate the position of the text content in the sample graph, allowing the image processing model to understand the relationship between the boundary and fusion degree between graphic and text content, thus better locating the text content. After the image processing model converges, it possesses the ability to locate the text content and distinguish it from the graphic content. This application provides the means to identify whether the rendering effect of an image needs further optimization.

Embodiments of the present disclosure disclose an image processing method and device, electronic equipment and storage medium, wherein the method comprises: performing the following steps by a Transformer model: combining each window image of a to-be-processed image and window feature data to be learned corresponding to each window image to obtain each combination data; performing self-attention transformation of pixel dimensions on each combination data to obtain intra-window information exchange images and learned window feature data; determining influence weights between the intra-window information exchange images according to the learned window feature data; and performing self-attention transformation of window dimensions on the intra-window information exchange images according to the influence weights to obtain inter-window information fusion images. The image processing can be performed based on a lightweight Transformer model, the calculation amount can be reduced on the basis of ensuring the processing effect, efficient and rapid visual image processing is realized, and the deployment of different platforms is facilitated.