Deep learning for NeuroImaging in Python.
Note
This page is a reference documentation. It only explains the class signature, and not how to use it. Please refer to the gallery for the big picture.
- class surfify.models.unet.DownBlock(conv_layer, in_ch, out_ch, conv_neigh_indices, down_neigh_indices, down_indices, pool_mode='mean', first=False)[source]¶
Downsampling block in spherical UNet: mean pooling => (conv => BN => ReLU) * 2
Init DownBlock.
- Parameters:
conv_layer : nn.Module
the convolutional layer on icosahedron discretized sphere.
in_ch : int
input features/channels.
out_ch : int
output features/channels.
conv_neigh_indices : array
conv layer’s filters’ neighborhood indices at sampling i.
down_neigh_indices : array
conv layer’s filters’ neighborhood indices at sampling i + 1.
down_indices : array
downsampling indices at sampling i.
pool_mode : str, default ‘mean’
the pooling mode: ‘mean’ or ‘max’.
first : bool, default False
if set skip the pooling block.
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