CycleGAN

CycleGAN model.

CycleGAN(
  ch_in = 3,
  ch_out = 3,
  n_features = 64,
  disc_layers = 3,
  gen_blocks = 9,
  lsgan = TRUE,
  drop = 0,
  norm_layer = NULL
)

Arguments

ch_in

input

ch_out

output

n_features

number of features

disc_layers

discriminator layers

gen_blocks

generator blocks

lsgan

ls gan

drop

dropout rate

norm_layer

normalziation layer

Value

None

Details

When called, takes in input batch of real images from both domains and outputs fake images for the opposite domains (with the generators). Also outputs identity images after passing the images into generators that outputs its domain type (needed for identity loss). Attributes: `G_A` (`nn.Module`): takes real input B and generates fake input A `G_B` (`nn.Module`): takes real input A and generates fake input B `D_A` (`nn.Module`): trained to make the difference between real input A and fake input A `D_B` (`nn.Module`): trained to make the difference between real input B and fake input B