A pytorch implementation of DCGAN "Deep Convolutional Generative Adversarial Networks"
for practice pytorch by reference to DCGAN Tutorial
cd PATH
mkdir _output
mkdir _model
python main.py --opt train
you should set the parameter in main.py (i.e., epoch, batch_size, worker, and so on) and the dataset is CelebA in default. You can download img_align_celeba.zip in Google Drive, then unzip the images into ./_data/img_align_celeba/ you can modify the path in main.py also. While training, you can check the image in ./_output folder, and you can get the checkpoint file in ./_model every 2 epoch.
python main.py --opt test
You can download the checkpoint file for four epoch in here
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| in 0 epoch and 100 iterations | in 0 epoch and 200 iterations | in 0 epoch and 400 iterations | in 0 epoch and 600 iterations | in 0 epoch and 800 iterations |
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| after 1 epochs | after 2 epochs | after 3 epochs | after 4 epochs | after 5 epochs |