add readme

README.md

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 # CartoonGAN-Test-Pytorch-Torch
-Pytorch and Torch testing code of CartoonGAN [Chen et al., CVPR18]
+Pytorch and Torch testing code of [CartoonGAN]()http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/2205.pdf [Chen et al., CVPR18]. With the released pretrained models by authors, I made these simple scripts for a quick test. The training code should be similar to the popular GAN-based image-translation frameworks and is not included here.
+
+
+## Getting started
+
+```
+git clone https://github.com/Yijunmaverick/CartoonGAN-Test-Pytorch-Torch
+cd CartoonGAN-Test-Pytorch-Torch
+```
+
+## Pytorch
+
+The original pretrained models are Torch `nngraph` models, which cannot be loaded in Pytorch through `load_lua`. So I manully 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
+```
+
+## Torch
+
+Working with original models with 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 models:
+
+```
+sh pretrained_model/download_t7.sh
+```
+
+- For testing:
+
+```
+th test.lua -input_dir YourImgDir -style Hosoda -gpu 0
+```
+
+## Examples
+
+<p>
+    <img src='test_img/5--26.jpg' width=300 />
+    <img src='test_output/5--26_Hosoda.jpg' width=300 />
+</p>
+
+<p>
+    <img src='test_img/7--136.jpg' width=300 />
+    <img src='test_output/7--136_Hayao.jpg' width=300 />
+</p>
+
+## Acknowledgement
+
+- Many thanks to the authors for this cool work.
+
+- Part of the codes are borrowed from [DCGAN](https://github.com/soumith/dcgan.torch), [AdaIN](https://github.com/xunhuang1995/AdaIN-style) and [CycleGAN](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix).
+