https://github.com/shyamsn97/neuralstyletensorflow

Neural Style algorthim, as introduced in "A Neural Algorithm of Artistic Style", implemented in tensorflow
https://github.com/shyamsn97/neuralstyletensorflow

convolutional-neural-networks deep-learning hacktoberfest2018 help-wanted neural-algorithm style-transfer tensorflow

Last synced: 7 months ago
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Neural Style algorthim, as introduced in "A Neural Algorithm of Artistic Style", implemented in tensorflow

• Host: GitHub
• URL: https://github.com/shyamsn97/neuralstyletensorflow
• Owner: shyamsn97
• Created: 2018-07-26T16:17:38.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2018-07-30T01:35:19.000Z (about 7 years ago)
• Last Synced: 2025-01-28T05:41:36.190Z (8 months ago)
• Topics: convolutional-neural-networks, deep-learning, hacktoberfest2018, help-wanted, neural-algorithm, style-transfer, tensorflow
• Language: Python
• Homepage:
• Size: 1.2 MB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

          
# NeuralStyleTensorflow

## Neural Style algorthim, as introduced in ["A Neural Algorithm of Artistic Style"](https://arxiv.org/abs/1508.06576), implemented in tensorflow

## Examples:

| Input/Content Image | Style Image | Mixed Image|

| :---:         |     :---:      |          :---: |

| ![](images/turtle.jpg)  | ![](images/picasso-guitar.jpg)    | ![](images/picasso-guitar-turtle.jpg)    |

| ![](images/dancing.jpg)      | ![](images/picasso.jpg)        | ![](images/picasso-dancing.jpg)       |

| ![](images/doggo.jpg)      | ![](images/wave.jpg)        | ![](images/doggo-wave.jpg)       |

| ![](images/wave.jpg)      | ![](images/picasso-guitar.jpg)        | ![](images/picasso-guitar-wave.jpg)       |

## How to use:

#### Installation:

		pip install -r requirements.txt

#### Stylize an input image:

		python neural_style.py [input image path] [content image path] [style image path] [size of images] [epochs] [output filename]

#### Stylize a white noise image:

		python neural_style.py "white" [content image path] [style image path] [size of images] [epochs] [output filename]