https://github.com/natsud99/neural-style-transfer

Style transfer is the task of changing the style of an image in one domain to the style of an image in another domain. This technique is outlined in "A Neural Algorithm of Artistic Style (Gatys et al.)."
https://github.com/natsud99/neural-style-transfer

cnn-keras neural-algorithm transfer transfer-learning

Last synced: 3 months ago
JSON representation

Style transfer is the task of changing the style of an image in one domain to the style of an image in another domain. This technique is outlined in "A Neural Algorithm of Artistic Style (Gatys et al.)."

• Host: GitHub
• URL: https://github.com/natsud99/neural-style-transfer
• Owner: NatsuD99
• License: mit
• Created: 2020-08-04T06:19:09.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-10-31T09:24:36.000Z (about 5 years ago)
• Last Synced: 2025-04-08T02:46:31.610Z (7 months ago)
• Topics: cnn-keras, neural-algorithm, transfer, transfer-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 8.88 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Neural Style Transfer using Keras

Neural style transfer is an optimization technique used to take three images:



    
 A content image 

    
 A style reference image (such as an artwork by a famous painter)e 

    
 The input image you want to style 

and blend them together such that the input image is transformed to look like the content image, but “painted” in the style of the style image. An overview of the technical process is that we take the base input image, a content image that we want to match, and the style image that we want to match. We’ll transform the base input image by minimizing the content and style distances (losses) with backpropagation, creating an image that matches the content of the content image and the style of the style image.


## Results