Within this repo, I try to implement a cartoon GAN [Chen et al., CVPR18].

I created a github page for detailed documentation, please see https://tobiassunderdiek.github.io/cartoon-gan/ for details.

All scripts to create the images are resumeable. It is possible to run make cartoons and make photos in parallel by calling them manually in separate terminals.

• download all_data.csv from safebooru dataset [2]
• point to all_data.csv in PATH_TO_SAFEBOORU_ALL_DATA_CSV of cartoon_image_downloader.py
• run make install to install necessary libraries
• run make cartoons to download configurable amount of medium size images

• run make cartoons-smooth to create the images

• download and unzip coco annotations from [3]
• configure annotations dir location in PATH_TO_COCO_ANNOTATIONS_ROOT_FOLDER of photo_downloader.py
• run make photos to download configurable amount of photos of persons

All the steps are described in a jupyter notebook on colab, please see here for details.

• run make install-transform
• download pre-trained weights, they are available for download as part of the release here..
• run make transform IMAGE=some_example_image_path

Additional information about how to load the pre-trained weights and transform images can be found in the project documentation here: https://tobiassunderdiek.github.io/cartoon-gan/ .

Thanks to the authors [Chen et al., CVPR18] of the paper for their great work.

[Chen et al., CVPR18] http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_CartoonGAN_Generative_Adversarial_CVPR_2018_paper.pdf

[2] https://www.kaggle.com/alamson/safebooru/download

[3] http://images.cocodataset.org/annotations/annotations_trainval2017.zip