def __init__(self, num_channel=256):
super(BigBaseline_show, self).__init__()
self.feature_extractor = make_residual_block(blocknum=5,
input_channel=3,
output_channel=64)
#referenced by EDVR paper implementation code
#https://github.com/xinntao/EDVR/blob/master/basicsr/models/archs/edvr_arch.py line 251
self.downsampling_network = make_downsampling_network(layernum=2,
in_channels=3,
out_channels=256)
self.lrfeature_scaler1 = nn.Conv2d(in_channels=3,
out_channels=64,
kernel_size=3,
padding=1,
bias=False)
self.lrfeature_scaler2 = nn.Conv2d(in_channels=64,
out_channels=256,
kernel_size=3,
padding=1,
bias=False)
self.feature_extractor = make_residual_block(blocknum=5,
input_channel=256,
output_channel=256)
self.SSEN_Network = SSEN_show(in_channels=num_channel)
self.preprocessing_residual_block = nn.Conv2d(in_channels=512,
out_channels=256,
kernel_size=1,
bias=False)
self.residual_blocks = make_residual_block(blocknum=32,
input_channel=256,
output_channel=256)
self.upscaling_4x = nn.Sequential(
nn.Conv2d(in_channels=num_channel,
out_channels=4 * num_channel,
kernel_size=3,
padding=1,
bias=False),
nn.PixelShuffle(2),
nn.Conv2d(in_channels=num_channel,
out_channels=4 * num_channel,
kernel_size=3,
padding=1,
bias=False),
nn.PixelShuffle(2),
)
self.outconv = nn.Conv2d(in_channels=num_channel,
out_channels=3,
kernel_size=3,
padding=1,
bias=False)
def __init__(self, ):
super(EDSR_show, self).__init__()
self.relu = nn.ReLU(True)
self.mhead = nn.Conv2d(in_channels=128,
out_channels=64,
kernel_size=3,
padding=1,
bias=True)
self.body = make_residual_block(blocknum=16,
input_channel=64,
output_channel=64)
# define tail module
m_tail = [
nn.Conv2d(in_channels=64,
out_channels=4 * 64,
kernel_size=3,
padding=1,
bias=True),
nn.PixelShuffle(2),
nn.Conv2d(in_channels=64,
out_channels=3,
kernel_size=3,
padding=1,
bias=True)
]
self.tail = nn.Sequential(*m_tail)
def __init__(self, ):
super(EDSR, self).__init__()
self.relu = nn.ReLU(True)
# self.sub_mean = common.MeanShift(args.rgb_range)
# self.add_mean = common.MeanShift(args.rgb_range, sign=1)
# define head module
#m_head = [nn.Conv2d(in_channels=3, out_channels=64,kernel_size=3,padding=1, bias=True)]
self.mhead = nn.Conv2d(in_channels=128,
out_channels=64,
kernel_size=3,
padding=1,
bias=True)
# define body module
"""
m_body = [
common.ResBlock(
conv, n_feats, kernel_size, act=act, res_scale=args.res_scale
) for _ in range(n_resblocks)
]
m_body.append(conv(n_feats, n_feats, kernel_size))
"""
self.body = make_residual_block(blocknum=16,
input_channel=64,
output_channel=64)
# define tail module
"""
m_tail = [
common.Upsampler(conv, scale, n_feats, act=False),
conv(n_feats, args.n_colors, kernel_size)
]
"""
m_tail = [
nn.Conv2d(in_channels=64,
out_channels=4 * 64,
kernel_size=3,
padding=1,
bias=True),
nn.PixelShuffle(2),
nn.Conv2d(in_channels=64,
out_channels=3,
kernel_size=3,
padding=1,
bias=True),
nn.PixelShuffle(2),
nn.Conv2d(in_channels=64,
out_channels=3,
kernel_size=3,
padding=1,
bias=True)
]
#self.head = nn.Sequential(*m_head)
self.tail = nn.Sequential(*m_tail)