unofficial implementation of DCT-Net: Domain-Calibrated Translation for Portrait Stylization.
you can find official version here

you can build your environment follow this
pip install tensorboardX for show

download pretrain weights

cd utils
bash download_weight.sh

follow rosinality/stylegan2-pytorch and put 550000.pt in pretrain_models

1. prepare the style pictures and align them
   the image path is like this
   style-photos/
   |-- 000000.png
   |-- 000006.png
   |-- 000010.png
   |-- 000011.png
   |-- 000015.png
   |-- 000028.png
   |-- 000039.png
   

2. change your own path in ccn_config

3. train ccn
   

   # single gpu
   python  train.py \
   --model ccn \
   --batch_size 16 \
   --checkpoint_path checkpoint \
   --lr 0.002 \
   --print_interval 100 \
   --save_interval 100 --dist 

    # multi gpu
   python -m torch.distributed.launch train.py \
   --model ccn \
   --batch_size 16 \
   --checkpoint_path checkpoint \
   --lr 0.002 \
   --print_interval 100 \
   --save_interval 100 

almost 1000 steps, you can stop

1. prepare expression information
   you can follow LVT to estimate facial landmark
   

   cd utils
   python get_face_expression.py \
   --img_base '' # your real image path base,like ffhq \
   --pool_num 2 # multiprocess number \
   --LVT '' # the LVT path you put \
   --train  # train data or val data

2. prepare your generator image
   

   cd utils
   python get_tcc_input.py \
   --model_path '' # ccn model path \
   --output_path '' # save path

   select almost 5k~1w good image manually
3. change your own path in ttn_config

   # like
   self.train_src_root = '/StyleTransform/DATA/ffhq-2w/img'
   self.train_tgt_root = '/StyleTransform/DATA/select-style-gan'
   self.val_src_root = '/StyleTransform/DATA/dmloghq-1k/img'
   self.val_tgt_root = '/StyleTransform/DATA/select-style-gan'

4. train tnn

   # like ccn single and multi gpus
   python  train.py \
   --model ttn \
   --batch_size 64 \
   --checkpoint_path checkpoint \
   --lr 2e-4 \
   --print_interval 100 \
   --save_interval 100 \
   --dist

you can follow inference.py to put your own ttn model path and image path
python inference.py

SEAN model and implementation:
https://github.com/ZPdesu/SEAN Copyright © 2020, ZPdesu.
License https://github.com/ZPdesu/SEAN/blob/master/LICENSE.md

stylegan2-pytorch model and implementation:
https://github.com/rosinality/stylegan2-pytorch Copyright © 2019, rosinality.
License https://github.com/rosinality/stylegan2-pytorch/blob/master/LICENSE

White-box-Cartoonization model and implementation:
https://github.com/SystemErrorWang/White-box-Cartoonization Copyright © 2020, SystemErrorWang.

White-box-Cartoonization model pytorch model and implementation:
https://github.com/vinesmsuic/White-box-Cartoonization-PyTorch Copyright © 2022, vinesmsuic.
License https://github.com/vinesmsuic/White-box-Cartoonization-PyTorch/blob/main/LICENSE

arcface pytorch model pytorch model and implementation:
https://github.com/ronghuaiyang/arcface-pytorch Copyright © 2018, ronghuaiyang.