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A web app that uses the Neural Style Transfer algorithm to stylise images

Jupyter Notebook 28.21% Python 28.30% CSS 5.84% JavaScript 2.31% HTML 35.35%
neural-network python html css flask

neuralart's Introduction

NeuralArt

Group 38

Avishi Gupta, Vaseem Naazleen, Shivangi Tomar.

Neural Style Transfer

Neural style transfer is an optimization technique takes two images

  • A content image .
  • 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.
  • Gatys et al(A Neural Algorithm of Artistic Style) introduced a way to use Convolutional Neural Network (CNN) to separate and recombine the image content and style of natural images by extracting image representations from response layers in VGG networks.

The below shows how style transfer looks :

nst

Examples of Neural Style transfer

  • A - Content Image
  • B, C, D, E, F - Stylized Images (Style Image at Right corner)

examples

How Neural Style Transfer works?

how_st_works

REFERENCES :

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