Neural style transfer

This is a TensorFlow implementation for performing style transfer using neural networks. The code uses key ideas from the Perceptual Losses for Real-Time Style Transfer and Super-Resolution and A Neural Algorithm of Artistic Style papers.

Requirements

The code is written in Python 3.5+ and uses TensorFlow. The requirements can be found in top-requirements.txt and installed using pip install -r top-requirements.txt.

Training

For training a model from scratch, we need to specify a folder containing the content images and the path to the style image. For example, assuming we've downloaded the MS COCO 2014 dataset and put the training images to data/train. We can train a model to apply the style of images/style/wave.jpg with the command

python3 train.py --style=images/style/wave.jpg --train_path=data/train --weights_path=weights/wave.hdf5

This will produce a weights file that we can use to generate new images from unseen content images 🎉.

Arguments

• --style Path to style image. Required.
• --train Path to training (content) images. Required.
• --weights Path where to save the model's weights. Required.

Styling

We can style new content images from a path or from a webcam 📷.

For example, for styling images/content/viaducto.jpg with weights located in weights/wave.hdf5 run

python3 style.py  --content=images/content/viaducto.jpg --weights=weights/wave.hdf5

For styling from a webcam feed, run

python3 style.py --weights=weights/wave.hdf5 --webcam

Arguments

• --content Path to content image. Required if --webcam isn't used.
• --gen Path where to save the generated image. If it isn't provided the image will be shown on screen.
• --weights Path to model's weights. Required.
• --webcam Generate images from the webcam. Can't be used if a content image is specified.

Example

Weights

Weights for models trained on the style images found in images/style/ can be found under releases.

Loss weights

These are the loss weights used during training for some style images (which can be found in images/style/)

• wave:
  • Content weight: 1
  • Style weight: 100
  • Total variation weight: 1e-5
• mosaic:
  • Content weight: 3
  • Style weight: 100
  • Total variation weight: 1e-5