This is the repository for a project that I am currently working on to verify whether the indicators in the current paper meet my expectations. I used the current mainstream four GAN models (DCGAN, WGAN, wgan-gp and LSGAN) to process the cat data I collected. All current models have been made into visual versions and are implemented using Django.
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Generate images of cats for Generative Adversarial Networks(GAN)
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Requirement
- Python >= 3.7
- Pytorch >= 1.3
- Torchvision >= 0.4
- Face dataset password:
g5qa
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Run
git clone https://github.com/lornatang/Deep-learning-with-cartoon.git
cd Deep-learning-with-cats/
# train dcgan 64 x 64 model.
python3 dcgan.py --cuda
# train wgan 64 x 64 model.
python3 wgan.py --cuda
# train wgan_gp 64 x 64 model.
python3 wgan_gp.py --cuda