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