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train_DiffIRS2_GAN_x4_V2.yml
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train_DiffIRS2_GAN_x4_V2.yml
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# general settings
name: train_DiffIRGANS2v2_x4
model_type: DiffIRGANS2Model
scale: 4
num_gpu: auto # auto: can infer from your visible devices automatically. official: 4 GPUs
manual_seed: 0
# USM the ground-truth
l1_gt_usm: True
percep_gt_usm: True
gan_gt_usm: False
# the first degradation process
resize_prob: [0.2, 0.7, 0.1] # up, down, keep
resize_range: [0.15, 1.5]
gaussian_noise_prob: 0.5
noise_range: [1, 30]
poisson_scale_range: [0.05, 3]
gray_noise_prob: 0.4
jpeg_range: [30, 95]
# the second degradation process
second_blur_prob: 0.8
resize_prob2: [0.3, 0.4, 0.3] # up, down, keep
resize_range2: [0.3, 1.2]
gaussian_noise_prob2: 0.5
noise_range2: [1, 25]
poisson_scale_range2: [0.05, 2.5]
gray_noise_prob2: 0.4
jpeg_range2: [30, 95]
gt_size: 256
queue_size: 180
# dataset and data loader settings
datasets:
train:
name: DF2K+OST
type: RealESRGANDataset
dataroot_gt: /mnt/bn/xiabinpaint/dataset
meta_info: datasets/meta_info/meta_info_DF2Kmultiscale+OST_sub.txt
io_backend:
type: disk
blur_kernel_size: 21
kernel_list: ['iso', 'aniso', 'generalized_iso', 'generalized_aniso', 'plateau_iso', 'plateau_aniso']
kernel_prob: [0.45, 0.25, 0.12, 0.03, 0.12, 0.03]
sinc_prob: 0.1
blur_sigma: [0.2, 3]
betag_range: [0.5, 4]
betap_range: [1, 2]
blur_kernel_size2: 21
kernel_list2: ['iso', 'aniso', 'generalized_iso', 'generalized_aniso', 'plateau_iso', 'plateau_aniso']
kernel_prob2: [0.45, 0.25, 0.12, 0.03, 0.12, 0.03]
sinc_prob2: 0.1
blur_sigma2: [0.2, 1.5]
betag_range2: [0.5, 4]
betap_range2: [1, 2]
final_sinc_prob: 0.8
gt_size: 256
use_hflip: True
use_rot: False
# data loader
use_shuffle: true
num_worker_per_gpu: 12
batch_size_per_gpu: 9
dataset_enlarge_ratio: 1
prefetch_mode: ~
# Uncomment these for validation
val_1:
name: NTIRE2020-Track1
type: PairedImageDataset
dataroot_gt: /mnt/bn/xiabinpaint/dataset/NTIRE2020-Track1/track1-valid-gt
dataroot_lq: /mnt/bn/xiabinpaint/dataset/NTIRE2020-Track1/track1-valid-input
io_backend:
type: disk
val_2:
name: AIM2019-Track2
type: PairedImageDataset
dataroot_gt: /mnt/bn/xiabinpaint/dataset/AIM2019-Track2/valid-gt-clean
dataroot_lq: /mnt/bn/xiabinpaint/dataset/AIM2019-Track2/valid-input-noisy
io_backend:
type: disk
val_3:
name: RealSR
type: PairedImageDataset
dataroot_lq: /mnt/bn/xiabinpaint/dataset/RealSR/Canon/Test/4/LR
dataroot_gt: /mnt/bn/xiabinpaint/dataset/RealSR/Canon/Test/4/HR
io_backend:
type: disk
# network structures
network_g:
type: DiffIRS2
n_encoder_res: 9
inp_channels: 3
out_channels: 3
dim: 64
num_blocks: [13,1,1,1]
num_refinement_blocks: 13
heads: [1,2,4,8]
ffn_expansion_factor: 2.2
bias: False
LayerNorm_type: BiasFree
n_denoise_res: 1
linear_start: 0.1
linear_end: 0.99
timesteps: 4
# network structures
network_S1:
type: DiffIRS1
n_encoder_res: 9
inp_channels: 3
out_channels: 3
dim: 64
num_blocks: [13,1,1,1]
num_refinement_blocks: 13
heads: [1,2,4,8]
ffn_expansion_factor: 2.2
bias: False
LayerNorm_type: BiasFree
network_d:
type: UNetDiscriminatorSN
num_in_ch: 3
num_feat: 64
skip_connection: True
# path
path:
pretrain_network_S1: experiments/DiffIRS1.pth
pretrain_network_g: experiments/DiffIRS2.pth
param_key_g: params_ema
strict_load_g: True
resume_state: ~
ignore_resume_networks: network_S1
# training settings
train:
ema_decay: 0.999
optim_g:
type: Adam
lr: !!float 1e-4
weight_decay: 0
betas: [0.9, 0.99]
optim_d:
type: Adam
lr: !!float 1e-4
weight_decay: 0
betas: [0.9, 0.99]
scheduler:
type: MultiStepLR
milestones: [400000]
gamma: 0.5
encoder_iter: 100000
total_iter: 400000
lr_encoder: !!float 2e-4
lr_sr: !!float 1e-4
gamma_encoder: 0.1
gamma_sr: 0.5
lr_decay_encoder: 60000
lr_decay_sr: 300000
warmup_iter: -1 # no warm up
# losses
pixel_opt:
type: L1Loss
loss_weight: 1.0
reduction: mean
# perceptual loss (content and style losses)
perceptual_opt:
type: PerceptualLoss
layer_weights:
# before relu
'conv1_2': 0.1
'conv2_2': 0.1
'conv3_4': 1
'conv4_4': 1
'conv5_4': 1
vgg_type: vgg19
use_input_norm: true
perceptual_weight: !!float 1.0
style_weight: 0
range_norm: false
criterion: l1
# gan loss
gan_opt:
type: GANLoss
gan_type: vanilla
real_label_val: 1.0
fake_label_val: 0.0
loss_weight: !!float 1.0
kd_opt:
type: KDLoss
loss_weight: 1
temperature: 0.15
net_d_iters: 1
net_d_init_iters: 0
# Uncomment these for validation
# validation settings
val:
window_size: 8
val_freq: !!float 1e4
save_img: False
metrics:
psnr: # metric name
type: calculate_psnr
crop_border: 4
test_y_channel: true
ssim: # metric name
type: calculate_ssim
crop_border: 4
test_y_channel: true
# logging settings
logger:
print_freq: 100
save_checkpoint_freq: !!float 1e4
use_tb_logger: true
wandb:
project: ~
resume_id: ~
# dist training settings
dist_params:
backend: nccl
port: 29500