Deep Feature Consistent VAE With PaddlePaddle

November 15, 2021 · View on GitHub

1.Download CelebA and Pretrained VGG19

Download CelebA @AI Studio CelebA and put data at ./dataset

Download pretrained VGG19_bn @PaddlePaddle (password: 25il) and put data at ./paddle_dfcvae/architectures/pretrained

then

sh preparedata.sh

2.Train paddle dfcvae

cd ./paddle_dfcvae
python trainer.py

chose vgg layer feature

vim  extract_features @ ./paddle_dfcvae/architectures/dfcvae.py

3.Generated imgs

python generatedImg.py

4.Reconstruct

vae123 Reconstruct

vae345 Reconstruct

vae123 extract the low features,clearer than vae345

5.Generated

Generated Generated

6.Logs , Models and More Imgs

BaiduYun (password: 9vs9)

19967 Reconstruct pics(2x10)

100 Generated pics(10x1)

7.Measure

IS:

meanstd
IS1.16360.0221
cifar101.16980.0355