DL-Art-School/codes/options/train/train_SRGAN.yml

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2019-08-23 13:42:47 +00:00
# Not exactly the same as SRGAN in <Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network>
# With 16 Residual blocks w/o BN
#### general settings
name: 002_SRGANx4_MSRResNetx4Ini_DIV2K
use_tb_logger: true
model: srgan
distortion: sr
scale: 4
gpu_ids: [1]
#### datasets
datasets:
train:
name: DIV2K
mode: LQGT
dataroot_GT: ../datasets/DIV2K/DIV2K800_sub.lmdb
dataroot_LQ: ../datasets/DIV2K/DIV2K800_sub_bicLRx4.lmdb
use_shuffle: true
n_workers: 6 # per GPU
batch_size: 16
GT_size: 128
use_flip: true
use_rot: true
color: RGB
val:
name: val_set14
mode: LQGT
dataroot_GT: ../datasets/val_set14/Set14
dataroot_LQ: ../datasets/val_set14/Set14_bicLRx4
#### network structures
network_G:
which_model_G: MSRResNet
in_nc: 3
out_nc: 3
nf: 64
nb: 16
upscale: 4
network_D:
which_model_D: discriminator_vgg_128
in_nc: 3
nf: 64
#### path
path:
pretrain_model_G: ../experiments/pretrained_models/MSRResNetx4.pth
strict_load: true
resume_state: ~
#### training settings: learning rate scheme, loss
train:
lr_G: !!float 1e-4
weight_decay_G: 0
beta1_G: 0.9
beta2_G: 0.99
lr_D: !!float 1e-4
weight_decay_D: 0
beta1_D: 0.9
beta2_D: 0.99
lr_scheme: MultiStepLR
niter: 400000
warmup_iter: -1 # no warm up
lr_steps: [50000, 100000, 200000, 300000]
lr_gamma: 0.5
pixel_criterion: l1
pixel_weight: !!float 1e-2
feature_criterion: l1
feature_weight: 1
gan_type: gan # gan | ragan
gan_weight: !!float 5e-3
D_update_ratio: 1
D_init_iters: 0
manual_seed: 10
val_freq: !!float 5e3
#### logger
logger:
print_freq: 100
save_checkpoint_freq: !!float 5e3