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Neural style transfer optimization technique using Generative adversarial neural networks(GANs) to create an NFT.

Wilberforce Wairagu

Wilberforce Wairagu

Nairobi, Nairobi County

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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. ...learn more

Project status: Concept

oneAPI, Artificial Intelligence

Intel Technologies
Intel Python

Code Samples [1]Links [1]

Overview / Usage

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.

This is implemented by optimizing the output image to match the content statistics of the content image and the style statistics of the style reference image. These statistics are extracted from the images using a convolutional network.

For my case i blended a picture of elephants taken from masaai mara in Kenya and a hand drawn art of the rich savanna landscape.

Repository

https://github.com/willywairagu/AICE/tree/master/ASTIS_Week5_GANs-NFTs-main

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