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style_transfer-perceptual_loss

This a funny demo of style transfer of paper ๏ผšPerceptual Losses for Real-Time Style Transfer and Super-Resolution

the detail information about this code is in my CSDN blog

usage:

train:

python train.py -is_training=True -vgg_model='your vgg model path' -train_data_path='your train dataset' -style_data_path='your style img path' -style_w=100 

forexample:

python train.py -is_training=True  -vgg_model='vgg16.ckpt' -train_data_path='/train2014' -style_data_path='img/wave.jpg' -style_w=100

you can download the vgg16.ckpt model from the url

note : you can change the degree of style transfer by changing style_w value, and you can also modify the code to set the args papameter as default

test

python train -is_training=False -test_data_path='your test img' -new_img_name='transfer.jpg' -transfer_model='your saved model after train'

forexample:

python train.py -is_training=False  -test_data_path='dog.jpg'  -new_img_name='transfer.jpg' -transfer_model='model_saved/wave.ckpt'

results

note

if you find it is useful for you, please leave your star, thanks. =_=

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