Multimodal Style Transfer via Graph Cuts Implementation in TF 2.0.0a

Paper implementation of Multimodal Style Transfer via Graph Cuts

Results

Open Test.ipynb to run your own tests.

alpha=1

Training

To start local training (after building the image datapath structure), simply run:

cd trainer
python train.py

or see below

Data Structure

To load the data we assume the following structure, both locally and remotely:

trainer
-- data
  -- content
    -- images_*.png
  -- style
    -- images_*.png

Local

First, create the following project structure locally.

git clone repo
cd repo/trainer/
mkdir data
cd data/
mkdir content
mkdir style

Then simply run the shell script to start training

sh train.sh local

Remote - GCP

Edit train.sh to specify your datapath=gs://path_to_data_dir/ variable.

sh train.sh remote

Transfer Learning

If you wish to use pretrained decoder weights, specify the path to them using weights parameter in the train.sh file.