LinkNet
- class mmit.decoders.LinkNet(input_channels, input_reductions, decoder_channel=32, upsample_layer=<class 'mmit.base.upsamplers.ConvTranspose2d'>, norm_layer=<class 'torch.nn.modules.batchnorm.BatchNorm2d'>, activation_layer=<class 'torch.nn.modules.activation.ReLU'>, extra_layer=<class 'torch.nn.modules.linear.Identity'>, mismatch_layer=<class 'mmit.base.mismatch.Pad'>)
Implementation of the Linknet decoder. Paper: https://arxiv.org/abs/1707.03718
- Parameters:
input_channels (
List[int]) – The channels of the input features.input_reductions (
List[int]) – The reduction factor of the input features.decoder_channel (
int) – The channel for the output of the decoder.
- forward(*features)
Forward pass of the decoder.
- Parameters:
*features (Tensor) – Features from the encoder, the first is the input image, last one the deepest.
- property out_classes: int
Number of output classes.