def __init__(self,args):
super(WCT, self).__init__()
# load pre-trained network
vgg1 = load_lua(args.vgg1,long_size=8)
decoder1_torch = load_lua(args.decoder1,long_size=8)
vgg2 = load_lua(args.vgg2,long_size=8)
decoder2_torch = load_lua(args.decoder2,long_size=8)
vgg3 = load_lua(args.vgg3,long_size=8)
decoder3_torch = load_lua(args.decoder3,long_size=8)
vgg4 = load_lua(args.vgg4,long_size=8)
decoder4_torch = load_lua(args.decoder4,long_size=8)
vgg5 = load_lua(args.vgg5,long_size=8)
decoder5_torch = load_lua(args.decoder5,long_size=8)
self.e1 = encoder1(vgg1)
self.d1 = decoder1(decoder1_torch)
self.e2 = encoder2(vgg2)
self.d2 = decoder2(decoder2_torch)
self.e3 = encoder3(vgg3)
self.d3 = decoder3(decoder3_torch)
self.e4 = encoder4(vgg4)
self.d4 = decoder4(decoder4_torch)
self.e5 = encoder5(vgg5)
self.d5 = decoder5(decoder5_torch)
def __init__(self,args):
super(WCT, self).__init__()
# load pre-trained network
vgg1 = torchfile.load(args.vgg1)
decoder1_torch = torchfile.load(args.decoder1)
vgg2 = torchfile.load(args.vgg2)
decoder2_torch = torchfile.load(args.decoder2)
vgg3 = torchfile.load(args.vgg3)
decoder3_torch = torchfile.load(args.decoder3)
vgg4 = torchfile.load(args.vgg4)
decoder4_torch = torchfile.load(args.decoder4)
vgg5 = torchfile.load(args.vgg5)
decoder5_torch = torchfile.load(args.decoder5)
self.e1 = encoder1(vgg1)
self.d1 = decoder1(decoder1_torch)
self.e2 = encoder2(vgg2)
self.d2 = decoder2(decoder2_torch)
self.e3 = encoder3(vgg3)
self.d3 = decoder3(decoder3_torch)
self.e4 = encoder4(vgg4)
self.d4 = decoder4(decoder4_torch)
self.e5 = encoder5(vgg5)
self.d5 = decoder5(decoder5_torch)
self.wct1 = ThumbWhitenColorTransform()
self.wct2 = ThumbWhitenColorTransform()
self.wct3 = ThumbWhitenColorTransform()
self.wct4 = ThumbWhitenColorTransform()
self.wct5 = ThumbWhitenColorTransform()
def __init__(self, args):
super(WCT, self).__init__()
# load pre-trained network
vgg1 = load_lua(args.vgg1)
decoder1_torch = load_lua(args.decoder1)
vgg2 = load_lua(args.vgg2)
decoder2_torch = load_lua(args.decoder2)
vgg3 = load_lua(args.vgg3)
decoder3_torch = load_lua(args.decoder3)
vgg4 = load_lua(args.vgg4)
decoder4_torch = load_lua(args.decoder4)
vgg5 = load_lua(args.vgg5)
decoder5_torch = load_lua(args.decoder5)
self.e1 = encoder1(vgg1)
self.d1 = decoder1(decoder1_torch)
self.e2 = encoder2(vgg2)
self.d2 = decoder2(decoder2_torch)
self.e3 = encoder3(vgg3)
self.d3 = decoder3(decoder3_torch)
self.e4 = encoder4(vgg4)
self.d4 = decoder4(decoder4_torch)
self.e5 = encoder5(vgg5)
self.d5 = decoder5(decoder5_torch)
self.args = args
def __init__(self, args):
super(WCT, self).__init__()
# 加载预训练的vgg：
vgg1 = load(args.vgg1, force_8bytes_long=True)
# vgg1 = vgg1.eval()
decoder1_torch = load(args.decoder1, force_8bytes_long=True)
vgg2 = load(args.vgg2, force_8bytes_long=True)
decoder2_torch = load(args.decoder2, force_8bytes_long=True)
vgg3 = load(args.vgg3, force_8bytes_long=True)
decoder3_torch = load(args.decoder3, force_8bytes_long=True)
vgg4 = load(args.vgg4, force_8bytes_long=True)
decoder4_torch = load(args.decoder4, force_8bytes_long=True)
vgg5 = load(args.vgg5, force_8bytes_long=True)
decoder5_torch = load(args.decoder5, force_8bytes_long=True)
self.e1 = encoder1(vgg1)
self.d1 = decoder1(decoder1_torch)
self.e2 = encoder2(vgg2)
self.d2 = decoder2(decoder2_torch)
self.e3 = encoder3(vgg3)
self.d3 = decoder3(decoder3_torch)
self.e4 = encoder4(vgg4)
self.d4 = decoder4(decoder4_torch)
self.e5 = encoder5(vgg5)
self.d5 = decoder5(decoder5_torch)
def __init__(self, args):
super(WCT, self).__init__()
# load pre-trained network
vgg1 = load(
args.vgg1,
force_8bytes_long=True) # windows下需要参数：force_8bytes_long=True
decoder1_torch = load(args.decoder1, force_8bytes_long=True)
vgg2 = load(args.vgg2, force_8bytes_long=True)
decoder2_torch = load(args.decoder2, force_8bytes_long=True)
vgg3 = load(args.vgg3, force_8bytes_long=True)
decoder3_torch = load(args.decoder3, force_8bytes_long=True)
vgg4 = load(args.vgg4, force_8bytes_long=True)
decoder4_torch = load(args.decoder4, force_8bytes_long=True)
vgg5 = load(args.vgg5, force_8bytes_long=True)
decoder5_torch = load(args.decoder5, force_8bytes_long=True)
self.e1 = encoder1(vgg1)
self.d1 = decoder1(decoder1_torch)
self.e2 = encoder2(vgg2)
self.d2 = decoder2(decoder2_torch)
self.e3 = encoder3(vgg3)
self.d3 = decoder3(decoder3_torch)
self.e4 = encoder4(vgg4)
self.d4 = decoder4(decoder4_torch)
self.e5 = encoder5(vgg5)
self.d5 = decoder5(decoder5_torch)
def __init__(self, vgg1, decoder1_torch, vgg2, decoder2_torch, vgg3,
decoder3_torch, vgg4, decoder4_torch, vgg5, decoder5_torch):
super(WCT, self).__init__()
# load pre-trained network
self.e1 = encoder1(vgg1)
self.d1 = decoder1(decoder1_torch)
self.e2 = encoder2(vgg2)
self.d2 = decoder2(decoder2_torch)
self.e3 = encoder3(vgg3)
self.d3 = decoder3(decoder3_torch)
self.e4 = encoder4(vgg4)
self.d4 = decoder4(decoder4_torch)
self.e5 = encoder5(vgg5)
self.d5 = decoder5(decoder5_torch)
def loadModel(args):
# load pre-trained network
vgg1 = load_lua(args.vgg1)
decoder1_torch = load_lua(args.decoder1)
vgg2 = load_lua(args.vgg2)
decoder2_torch = load_lua(args.decoder2)
vgg3 = load_lua(args.vgg3)
decoder3_torch = load_lua(args.decoder3)
vgg4 = load_lua(args.vgg4)
decoder4_torch = load_lua(args.decoder4)
vgg5 = load_lua(args.vgg5)
decoder5_torch = load_lua(args.decoder5)
e1 = encoder1(vgg1)
d1 = decoder1(decoder1_torch)
e2 = encoder2(vgg2)
d2 = decoder2(decoder2_torch)
e3 = encoder3(vgg3)
d3 = decoder3(decoder3_torch)
e4 = encoder4(vgg4)
d4 = decoder4(decoder4_torch)
e5 = encoder5(vgg5)
d5 = decoder5(decoder5_torch)
if (args.cuda):
e1.cuda()
e2.cuda()
e3.cuda()
e4.cuda()
e5.cuda()
d1.cuda()
d2.cuda()
d3.cuda()
d4.cuda()
d5.cuda()
# save some space
del vgg1
del decoder1_torch
del vgg2
del decoder2_torch
del vgg3
del decoder3_torch
del vgg4
del decoder4_torch
del vgg5
del decoder5_torch
return e1, d1, e2, d2, e3, d3, e4, d4, e5, d5