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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.

forward(x)[source]

Forward method.

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