Implementation of Neural Style Transformation Technique for Artistic Image Processing Using VGG19

Image transformation is performed for basic image generation and color correction. In many applications, images are used for visual analysis or mainly for creating content. Similarly, stylized transformation is a process of transforming images into art-based content. To perform this artistic rendition through the process of image-stylized transformation, this article used the VGG19 classifier. The procedure begins by preprocessing both the content image and style image for reference, which includes resizing them to a maximum dimension while keeping their initial aspect ratio and transforming them into an array. The utility function reprocesses the image by clipping and normalizing pixel values. Content loss is calculated by comparing the feature maps of the derived content with the processed or stylized image generated by the model. Gradients of the loss concerning the generated image are computed and used to iteratively update the generated image. The process involves sequential display and processing of intermediate images until the process reaches 1000 iterations. In the end, the process produced a stylized image that depicts the artwork as its original counterpart.

Abstract licence: CC BY

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.