We have implememted the AdaIN model described in Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization using Tensorflow 2.0 version.

Required environments

• python 3.7.9
• tensorflow-gpu 2.4
• scikit-image 0.18.1
• kaggle-api: to download dataset from kaggle

The requirements.txt contains all packages in our virtual environment when implementing this model.

Below we presented several examples created by the AdaIN model implemented. The orginal content image is a picture taken in Brown University Main Green. For more examples, please check ./examples/results folder. For pretrained models, click here

Styles	Results

The training content images are MS-COCO and style images are WikiArt. We also provide the preprocessed dataset used in our training. The preprocess includes removing all images that don't have the third dimension, images whose third dimension number is not 3 and images that are too large to raise a warning. All images have been resized to the size of which the shortest dimension is 512. The image ratio is kept during the resizing. Check the clean_images() function in preprocess.py for details.

We provide the cleaned MS-COCO and cleaned WikiArt dataset on google drive. [Click here] We also provide download instruction in the setup.sh. In total, there are 82606 images in cleaned content folder and 78572 images in cleaned style folder.

Use python run.py --help to check all available arguments. All hyperparameters are included in hyperparameters.py.

python run.py --content-dir ./images/content_cleaned \ 
              --style-dir ./images/style_kaggle_cleaned \ 
              --pretrained-vgg19 ./images/vgg19_normalised.npz

python run.py --load-checkpoint ./output/checkpoints/041921-213116/epoch_1_batch_5000 \
              --evaluate \
              --content-evaluate ./examples/content/brownspring.jpg \
              --style-evaluate ./examples/style/starry_night.jpg

1. Repository from Xun Huang, AdaIN-style implemented in Torch, who is the first author of AdaIN model paper
2. AdaIN-style-transfer---Tensorflow-2.0, implemented in Tensorflow 2.0. (Note: The repo resize all images to (256, 256) without preserving the ratio, which is different from the data preparation described in the paper. It would cause checkboard artifacts in the result.)
3. Tensorflow-Style-Transfer-with-Adain, implemented in Tensorflow 1.0 version.