this repo based on the original implementation of CycleGAN: https://github.com/jinfagang/pytorch_cycle_gan.git, in this version I reconstruct some code and made a generate API to simply generate image from your own single image and your trained model.
CycleGAN - Generate Image Like Magic
I have trained apple2orange and horse2zebra for now, here is the real result of convert
apple -> orange:
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I only trained about 50 epochs, but the result is fair enough for now. Laterly I will finish horse2zebra model, and update some more results.
Requirements
- Python3+
- PyTorch
- visdom
- PIL
Usage
- For Train
About how to train, simply run this:
python3 train.py --dataroot ./datasets/apple2orange --name apple2orange --model cycle_gan
One things have to mention that, --name indicates the model save dir, and --model is using cycle_gan or pixel2pixel , I only tried cycle_gan.
- For Generate
Train is very simple, but the original repo have not implement predict API, so I managed to write by myself. Here is the way to use:
python3 generate.py --image_path ./apple_test.jpg --name apple2orange --model cycle_gan --gpu_ids -1
As you can see, you only need to specific image path where stores your image to generate, and --name is the same as previous trained, as well as model type. --gpu_ids indicates we are inference using CPU.
OK, that's all.
Research and Discuss
I really love to connect to people, so if you have any question about this repo, you can find me on wechat jintianiloveu, I have some groups which discuss about GANs I will invite you in if you like.
Copyright
(c) 2017 Jin Fagang under LICENSE Apache 2.0
