fast photo style transform

This is an implementation based on mxnet-python of the paper Perceptual Losses for Real-Time Style Transfer and Super-Resolution by Justin Johnson, Alexandre Alahi, Li Fei-Fei.

How to use

Then run python fast_style.py, use -h to see more options

create output and training set directory

• mkdir output
• mkdir datas/training_images

acquire training image set

download the Coco dataset：http://msvocds.blob.core.windows.net/coco2015/test2015.zip or download image dataset from challenger.ai

train

python fast_style.py --train 1 --train_path datas/training_images/

transform

python fast_style.py --input_image input/xxx.jpg

Sample results

output/

Note

• use the mxnet-0.11.0
• The current implementation is based on: https://github.com/Ldpe2G/DeepLearningForFun/tree/master/Mxnet-Scala/FastNeuralStyle and https://github.com/apache/incubator-mxnet/tree/master/example/neural-style