SEGAN pytorch implementation https://arxiv.org/abs/1703.09452
GPL-3.0 License
Implementation of SEGAN by Pascual et al. in 2017, using pytorch. Original Tensorflow version can be found here.
requirements.txt
pip install -r requirements.txt
Use data_preprocess.py
file to preprocess downloaded data.
Adjust the file paths at the beginning of the file to properly locate the data files, output folder, etc.
Uncomment functions in __main__
to perform desired preprocessing stage.
Data preprocessing consists of three main stages:
Note that the second stage takes a fairly long time - more than an hour.
python model.py
Again, fix and adjust datapaths in model.py
according to your needs.
Especially, provide accurate path to where serialized data are stored.
In order to use tensorboard, you need to first install tensorboard:
pip install tensorboard
Then run tensorboard by specifing the log directory.
tensorboard --logdir=segan_data_out/tblogs