def __init__(self, in_channel=32):
super(NLFilter3d, self).__init__()
self.inner_channel = in_channel
self.conv = BasicConv(in_channel,
self.inner_channel,
bn=True,
relu=False,
kernel_size=3,
stride=1,
padding=1)
self.conv_refine = BasicConv(in_channel + self.inner_channel,
in_channel,
is_3d=True,
bn=True,
relu=True,
kernel_size=3,
stride=1,
padding=1)
self.getweights = GetWeights()
self.nlf = NLFIter()
def __init__(self, in_channel=32):
super(NLFilter, self).__init__()
self.inner_channel = in_channel
self.conv_refine = BasicConv(in_channel + self.inner_channel,
in_channel,
bn=True,
relu=True,
kernel_size=3,
stride=1,
padding=1)
self.getweights = nn.Sequential(
BasicConv(in_channel,
self.inner_channel,
bn=True,
l2=False,
relu=False,
kernel_size=3,
stride=1,
padding=1), GetWeights())
# self.amplify = nn.Conv2d(5, 5, kernel_size=1, stride=1, padding=0, bias=False)
# self.softmax = nn.Softmax(dim=1)
self.nlf = NLFIter()