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Neural Style Transfer


Python NumPy TensorFlow Jupyter


Neural style transfer consists in generating an image with the same "content" as a base image, but with the "style" of a different picture. This is achieved through the optimization of a loss function that has 3 components: "style loss", "content loss", and "total variation loss".

Implementation Details

This implementation uses TensorFlow2.x to train a fast style transfer network and Flask as an backend API.

How to Run?

Requirements:

  1. Flask
  2. Tensorflow 2.x
python3 app.py

Example

Base Image

Base

Style Image

Style

Genrated Image

Genrated

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Neural style transfer web app with flask.

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