Neural style transfer is an optimization technique used to take two images—a content image and a style reference image (such as an artwork by a famous painter)—and blend them together so the output image looks like the content image, but “painted” in the style of the style reference image.
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Feature extraction using a pre-trained VGG19 model.
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Calculation of content loss and style loss.
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Optimization of a target image to blend content and style.
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Visualization of the final stylized image.