def __init__(self,
nclass,
decoder_capacity,
input_height,
input_width,
norm_layer=nn.BatchNorm,
norm_kwargs=None):
super(_LadderHead, self).__init__()
with self.name_scope():
self.conv_c4 = ConvBlock(decoder_capacity,
1,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs,
activation='relu')
self.fusion_c3 = LateralFusion(decoder_capacity,
input_height // 16,
input_width // 16,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_c2 = LateralFusion(decoder_capacity,
input_height // 8,
input_width // 8,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_c1 = LateralFusion(decoder_capacity,
input_height // 4,
input_width // 4,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.seg_head = FCNHead(nclass, decoder_capacity, norm_layer,
norm_kwargs)
def __init__(self,
nclass,
input_height,
input_width,
capacity=256,
norm_layer=nn.BatchNorm,
norm_kwargs=None):
super(_NextHead, self).__init__()
with self.name_scope():
self.conv_c4 = ConvBlock(capacity,
1,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_16x = LateralFusion(capacity,
input_height // 16,
input_width // 16,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_8x = LateralFusion(capacity,
input_height // 8,
input_width // 8,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.seg_head = FCNHead(nclass,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
def __init__(self,
nclass,
in_channels,
input_height,
input_width,
capacity=256,
norm_layer=nn.BatchNorm,
norm_kwargs=None):
super(_SwiftNetHead, self).__init__()
with self.name_scope():
self.ppool = PyramidPooling(in_channels, input_height // 32,
input_width // 32, norm_layer,
norm_kwargs)
self.conv_c4 = ConvBlock(capacity,
1,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_c3 = LateralFusion(capacity,
input_height // 16,
input_width // 16,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_c2 = LateralFusion(capacity,
input_height // 8,
input_width // 8,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_c1 = LateralFusion(capacity,
input_height // 4,
input_width // 4,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.seg_head = FCNHead(nclass, capacity, norm_layer, norm_kwargs)
def __init__(self,
nclass,
in_channels,
capacity=256,
norm_layer=nn.BatchNorm,
norm_kwargs=None):
super(_SwiftNetHead, self).__init__()
with self.name_scope():
self.ppool = PPModule(in_channels, norm_layer, norm_kwargs)
self.conv_c4 = ConvModule2d(capacity,
1,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_c3 = LateralFusion(capacity, norm_layer, norm_kwargs)
self.fusion_c2 = LateralFusion(capacity, norm_layer, norm_kwargs)
self.fusion_c1 = LateralFusion(capacity, norm_layer, norm_kwargs)
self.seg_head = FCNHead(nclass, capacity, norm_layer, norm_kwargs)
def __init__(self,
capacity=256,
norm_layer=nn.BatchNorm,
norm_kwargs=None):
super(_FPNBranch, self).__init__()
with self.name_scope():
self.conv = ConvModule2d(capacity,
1,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.lateral16x = LateralFusion(capacity,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.lateral8x = LateralFusion(capacity,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.lateral4x = LateralFusion(capacity,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
def __init__(self,
nclass,
decoder_capacity,
norm_layer=nn.BatchNorm,
norm_kwargs=None):
super(_LadderHead, self).__init__()
with self.name_scope():
self.conv_c4 = ConvModule2d(decoder_capacity,
1,
norm_layer=norm_layer,
norm_kwargs=norm_kwargs)
self.fusion_c3 = LateralFusion(decoder_capacity, norm_layer,
norm_kwargs)
self.fusion_c2 = LateralFusion(decoder_capacity, norm_layer,
norm_kwargs)
self.fusion_c1 = LateralFusion(decoder_capacity, norm_layer,
norm_kwargs)
self.seg_head = FCNHead(nclass, decoder_capacity, norm_layer,
norm_kwargs)