PhotoWCT with closed form matting

NOTE: TO BE UPDATED

Torch implementation of the papers Universal Style Transfer and A Closed-form Solution to Photorealistic Image Stylization

This is an unofficial implementation. The original implementation of Universal Style Transfer and A Closed-form Solution to Photorealistic Image Stylization are there <-

How to run it

1. Download the decoders from the directories
2. python3 run_wct.py --x 4 --style <path to style> --content <path to content> --output <output file name> --decoder decoder_1/dec_1849.pkl,decoder_2/dec_1849.pkl,decoder_3/dec_1849.pkl,decoder_4/dec_1849.pkl --smooth True

How to train it

1. Get the 2017 MS COCO train and validation datasets and unzip them
2. Download PyTorch VGG16 model wget https://download.pytorch.org/models/vgg16-397923af.pth
3. For every layer(x = 1 to 4) train the decoder. It is recommended to run training twice with starting lr 0.001 and then 0.0001 python3 --x <layer number> --batch_size <64> --decoder <saved checkpoint if any> --optimizer <optimized checkpoint if any> Note: all decoders & optimizers are saved in the dir decoder_<x>

Results

Clockwise from top left: image, style, whitening+coloring, whitening+coloring+smoothing

TODO

1. Make training easier
2. Make running easier