Open XmySz opened 1 year ago
According to the structure diagram of the paper, the final OutputTransition should look like the following:
class OutputTransition(nn.Module): def __init__(self, in_channels, classes, elu): super(OutputTransition, self).__init__() self.classes = classes # self.conv1 = nn.Conv3d(in_channels, classes, kernel_size=5, padding=2) # 修改 self.conv1 = nn.Conv3d(in_channels, classes, kernel_size=1) self.bn1 = torch.nn.BatchNorm3d(classes) self.conv2 = nn.Conv3d(classes, classes, kernel_size=1) self.relu1 = ELUCons(elu, classes) def forward(self, x): out = self.relu1(self.bn1(self.conv1(x))) # out = self.conv2(out) # 修改 return out
We simply use the only 111 convolutional layer to make the number of channels the same as the classes.
According to the structure diagram of the paper, the final OutputTransition should look like the following:
We simply use the only 111 convolutional layer to make the number of channels the same as the classes.