segmentation.py 文件源码

def forward(self, x):
        x = F.relu(self.conv1_1(x))
        x = F.relu(self.conv1_2(x))
        p1 = self.prob1(x)
        x = F.max_pool2d(x,kernel_size=2, stride=2,return_indices=False)

        x = F.relu(self.conv2_1(x))
        x = F.relu(self.conv2_2(x))
        p2 = self.prob2(x)
        p2=F.upsample_nearest(p2, scale_factor=2)
        x = F.max_pool2d(x,kernel_size=2, stride=2,return_indices=False)

        x = F.relu(self.conv3_1(x))
        x = F.relu(self.conv3_2(x))
        x = F.relu(self.conv3_3(x))
        p4 = self.prob4(x)
        p4=F.upsample_nearest(p4, scale_factor=4)
        x = F.max_pool2d(x,kernel_size=2, stride=2,return_indices=False)

        x = F.relu(self.conv4_1(x))
        x = F.relu(self.conv4_2(x))
        x = F.relu(self.conv4_3(x))
        p8 = self.prob8(x)
        p8=F.upsample_nearest(p8, scale_factor=8)
        x = F.max_pool2d(x,kernel_size=2, stride=2,return_indices=False)

        x = F.relu(self.conv5_1(x))
        x = F.relu(self.conv5_2(x))
        x = F.relu(self.conv5_3(x))
        p16 = self.prob16(x)
        p16=F.upsample_nearest(p16, scale_factor=16)

        return p1/16+p2/8+p4/4+p8/2+p16