Deep Learning & Art: Neural Style Transfer – An Implementation with Tensorflow (using Transfer Learning with a Pre-trained VGG-19 Network) in Python

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This problem appeared as an assignment in the online coursera course Convolution Neural Networks by Prof Andrew Ng, (deeplearing.ai).  The description of the problem is taken straightway from the assignment.

Neural Style Transfer algorithm was created by Gatys et al. (2015) , the paper can be found here .

In this assignment, we shall:

  • Implement the neural style transfer algorithm
  • Generate novel artistic images using our algorithm

Most of the algorithms we’ve studied optimize a cost function to get a set of parameter values. In Neural Style Transfer, we  shall optimize a cost function to get pixel values!

Problem Statement

Neural Style Transfer (NST) is one of the most fun techniques in deep learning. As seen below, it merges two images, namely,

  1. a “content” image (C) and
  2. a “style” image (S),

to create a “generated” image (

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