DynamicUnet: DynamicUnet

View source: R/unet.R

DynamicUnetR Documentation

DynamicUnet

Description

Create a U-Net from a given architecture.

Usage

DynamicUnet(
  encoder,
  n_classes,
  img_size,
  blur = FALSE,
  blur_final = TRUE,
  self_attention = FALSE,
  y_range = NULL,
  last_cross = TRUE,
  bottle = FALSE,
  act_cls = nn()$ReLU,
  init = nn()$init$kaiming_normal_,
  norm_type = NULL
)

Arguments

encoder

encoder

n_classes

number of classes

img_size

image size

blur

blur is used to avoid checkerboard artifacts at each layer.

blur_final

blur final is specific to the last layer.

self_attention

self_attention determines if we use a self attention layer at the third block before the end.

y_range

If y_range is passed, the last activations go through a sigmoid rescaled to that range.

last_cross

last cross

bottle

bottle

act_cls

activation

init

initializer

norm_type

normalization type

Value

None


fastai documentation built on March 21, 2022, 9:07 a.m.