Pytorch and Torch testing code of CartoonGAN [Chen et al., CVPR18]
. With the released pretrained models by the authors, I made these simple scripts for a quick test.
- Linux
- NVIDIA GPU
- Pytorch 0.3
- Torch
git clone https://github.com/Yijunmaverick/CartoonGAN-Test-Pytorch-Torch
cd CartoonGAN-Test-Pytorch-Torch
The original pretrained models are Torch nngraph
models, which cannot be loaded in Pytorch through load_lua
. So I manually copy the weights (bias) layer by layer and convert them to .pth
models.
- Download the converted models:
sh pretrained_model/download_pth.sh
- For testing:
python test.py --input_dir YourImgDir --style Hosoda --gpu 0
Working with the original models in Torch is also fine. I just convert the weights (bias) in their models from CudaTensor to FloatTensor so that cudnn
is not required for loading models.
- Download the converted models:
sh pretrained_model/download_t7.sh
- For testing:
th test.lua -input_dir YourImgDir -style Hosoda -gpu 0
- The training code should be similar to the popular GAN-based image-translation frameworks and thus is not included here.
-
Many thanks to the authors for this cool work.
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Part of the codes are borrowed from DCGAN, TextureNet, AdaIN and CycleGAN.