Download the dataset (script borrowed from torch code):
bash ./download_dataset.sh facades
Train the model
python main.py --phase train
Test the model:
python main.py --phase test
Results
Here is the results generated from this implementation:
Facades:
More results on other datasets coming soon!
Note: To avoid the fast convergence of D
(discriminator) network, G (generator) network is updated twice for each
D network update, which differs from original paper but same as DCGAN-tensorflow, which this project based on.
Train
Code currently supports CMP Facades
dataset. To reproduce results presented above, it takes 200 epochs of
training. Exact computing time depends on own hardware conditions.
Test
Test the model on validation set of CMP Facades dataset. It will generate synthesized images provided corresponding labels under directory ./test.