def execute(self, x):
imsize = x.shape
x_, x__, x_0, x = self.backbone(x)
## begin ocrhead
context = self.get_context(x_0)
x_feature = self.conv_3x3(x)
x = self.head(context, x_feature)
x = nn.resize(x, size=(imsize[2], imsize[3]), mode='bilinear')
context = nn.resize(context,
size=(imsize[2], imsize[3]),
mode='bilinear')
return context, x
def execute(self, x):
imsize = x.shape
_, _, _, x = self.backbone(x)
x = self.head(x)
x = nn.resize(x, size=(imsize[2], imsize[3]), mode='bilinear')
return x
def execute(self, x):
imsize = x.shape
_, _, _, x = self.backbone(x)
b, c, h, w = x.shape
x_k = self.conv_0(x)
x1 = self.layer5a(x_k).reshape(b, c, -1)
x2 = self.layer5b(x_k).reshape(b, c, -1)
x3 = self.layer5c(x_k).reshape(b, c, -1)
x4 = self.layer5d(x_k).reshape(b, c, -1)
x_k = concat([x1, x2, x3, x4], 2).transpose(0, 2, 1) # b 110 c
x_q = self.conv_1(x)
x_q = x_q.reshape(b, c, -1)
x_attention = nn.bmm(x_k, x_q) # b 110 N
x_v = self.conv_2(x)
x1 = self.layer5a(x_v).reshape(b, c, -1)
x2 = self.layer5b(x_v).reshape(b, c, -1)
x3 = self.layer5c(x_v).reshape(b, c, -1)
x4 = self.layer5d(x_v).reshape(b, c, -1)
x_v = concat([x1, x2, x3, x4], 2) # b c 110
x = nn.bmm(x_v, x_attention).reshape(b, c, h, w)
x = self.final_conv(x)
x = nn.resize(x,
size=(imsize[2], imsize[3]),
mode='bilinear',
align_corners=True)
return x
def execute(self, input):
x, low_level_feat = self.backbone(input)
x = self.aspp(x)
x = self.decoder(x, low_level_feat)
x = nn.resize(x,
size=(input.shape[2], input.shape[3]),
mode='bilinear')
return x
def interpolate(X,
size=None,
scale_factor=None,
mode='bilinear',
align_corners=False):
if scale_factor is not None:
size = [X.shape[-2] * scale_factor, X.shape[-1] * scale_factor]
if isinstance(size, int):
size = (size, size)
return nn.resize(X, size, mode, align_corners)
def execute(self, x, low_level_feat):
low_level_feat = self.conv1(low_level_feat)
low_level_feat = self.bn1(low_level_feat)
low_level_feat = self.relu(low_level_feat)
#print (low_level_feat.shape)
x = nn.resize(x,
size=(low_level_feat.shape[2], low_level_feat.shape[3]),
mode='bilinear')
x = concat((x, low_level_feat), dim=1)
x = self.last_conv(x)
return x
def execute(self, x):
size = x.shape
_, _, _, x = self.backbone(x)
x = self.final_conv(
concat([
x,
self.layer5a(x),
self.layer5b(x),
self.layer5c(x),
self.layer5d(x),
], 1))
return nn.resize(x, size=(size[2], size[3]), mode='bilinear')
def execute(self, x):
size = x.shape
output = nn.resize(self.conv(x),
size=(size[2], size[3]),
mode='bilinear')
return output
