StyleGAN V2

cd applications/
python -u tools/styleganv2.py \
       --output_path <替换为生成图片存放的文件夹> \
       --weight_path <替换为你的预训练模型路径> \
       --model_type ffhq-config-f \
       --seed 233 \
       --size 1024 \
       --style_dim 512 \
       --n_mlp 8 \
       --channel_multiplier 2 \
       --n_row 3 \
       --n_col 5 \
       --cpu

  PaddleGAN
    ├── data
        ├── ffhq
              ├──images1024x1024
                    ├── 00000.png
                    ├── 00001.png
                    ├── 00002.png
                    ├── 00003.png
                    ├── 00004.png
               ├──images256x256
                    ├── 00000.png
                    ├── 00001.png
                    ├── 00002.png
                    ├── 00003.png
                    ├── 00004.png
       ├──custom_data
            ├── img0.png
            ├── img1.png
            ├── img2.png
            ├── img3.png
            ├── img4.png
            ...

python tools/main.py -c configs/stylegan_v2_256_ffhq.yaml

python tools/extract_weight.py output_dir/YOUR_TRAINED_WEIGHT.pdparams --net-name gen_ema --output YOUR_WEIGHT_PATH.pdparams

python tools/styleganv2.py --output_path stylegan01 --weight_path YOUR_WEIGHT_PATH.pdparams --size 256

@inproceedings{Karras2019stylegan2,
  title     = {Analyzing and Improving the Image Quality of {StyleGAN}},
  author    = {Tero Karras and Samuli Laine and Miika Aittala and Janne Hellsten and Jaakko Lehtinen and Timo Aila},
  booktitle = {Proc. CVPR},
  year      = {2020}
}