This post is a practical example of Neural Style Transfer based on the paper A Neural Algorithm of Artistic Style (Gatys et al.). For this example, we will use the pretrained Arbitrary Image Stylization module which is available in TensorFlow Hub. We will work with Python and tensorflow 2.x.

Neural Style Transfer

Neural style transfer is an optimization technique used to take two images- an 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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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 example, let’s take an image of the Gold Gate Bridge and the Starry Night by Van Gogh.

Now how would it look like if Van Gogh decided to paint the picture of Golden Gate with this style?

#machine-learning #neural-style-transfer #python #tensorflow #ai