def __init__(self, args):
super(MultiLevelWCT, self).__init__()
self.svd_device = torch.device('cpu')
self.cnn_device = args.device
self.alpha = args.alpha
self.beta = args.beta
if args.mask:
self.mask_mode = True
self.mask = Image.open(args.mask).convert('1')
else:
self.mask_mode = False
self.mask = None
self.e1 = Encoder(1)
self.e2 = Encoder(2)
self.e3 = Encoder(3)
self.e4 = Encoder(4)
self.e5 = Encoder(5)
self.encoders = [self.e5, self.e4, self.e3, self.e2, self.e1]
self.d1 = Decoder(1)
self.d2 = Decoder(2)
self.d3 = Decoder(3)
self.d4 = Decoder(4)
self.d5 = Decoder(5)
self.decoders = [self.d5, self.d4, self.d3, self.d2, self.d1]
def __init__(self, args):
super(SingleLevelWCT, self).__init__()
# ss('in singlelevelwct init')
self.svd_device = torch.device(
'cpu'
) # on average svd takes 4604ms on cpu vs gpu 5312ms on a 512x512 content/591x800 style (comprehensive of data transferring)
self.cnn_device = args.device
self.alpha = args.alpha
self.beta = args.beta
# ss('in singlelevelwct init')
self.mask_mode = False
self.mask = None
self.e5 = Encoder(5)
self.encoders = [self.e5]
self.d5 = Decoder(5)
self.decoders = [self.d5]
def __init__(self, args):
super(SingleLevelWCT, self).__init__()
self.svd_device = torch.device('cpu') # on average svd takes 4604ms on cpu vs gpu 5312ms on a 512x512 content/591x800 style (comprehensive of data transferring)
self.cnn_device = args.device
self.alpha = args.alpha
self.beta = args.beta
if args.mask:
self.mask_mode = True
self.mask = Image.open(args.mask).convert('1')
else:
self.mask_mode = False
self.mask = None
self.e5 = Encoder(5)
self.encoders = [self.e5]
self.d5 = Decoder(5)
self.decoders = [self.d5]