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# general settings | |
name: train_RealESRNetx4plus_1000k_B12G4 | |
model_type: RealESRNetModel | |
scale: 4 | |
num_gpu: auto # auto: can infer from your visible devices automatically. official: 4 GPUs | |
manual_seed: 0 | |
# ----------------- options for synthesizing training data in RealESRNetModel ----------------- # | |
gt_usm: True # USM the ground-truth | |
# 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: datasets/DF2K | |
meta_info: datasets/DF2K/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: 5 | |
batch_size_per_gpu: 12 | |
dataset_enlarge_ratio: 1 | |
prefetch_mode: ~ | |
# Uncomment these for validation | |
# val: | |
# name: validation | |
# type: PairedImageDataset | |
# dataroot_gt: path_to_gt | |
# dataroot_lq: path_to_lq | |
# io_backend: | |
# type: disk | |
# network structures | |
network_g: | |
type: RRDBNet | |
num_in_ch: 3 | |
num_out_ch: 3 | |
num_feat: 64 | |
num_block: 23 | |
num_grow_ch: 32 | |
# path | |
path: | |
pretrain_network_g: experiments/pretrained_models/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth | |
param_key_g: params_ema | |
strict_load_g: true | |
resume_state: ~ | |
# training settings | |
train: | |
ema_decay: 0.999 | |
optim_g: | |
type: Adam | |
lr: !!float 2e-4 | |
weight_decay: 0 | |
betas: [0.9, 0.99] | |
scheduler: | |
type: MultiStepLR | |
milestones: [1000000] | |
gamma: 0.5 | |
total_iter: 1000000 | |
warmup_iter: -1 # no warm up | |
# losses | |
pixel_opt: | |
type: L1Loss | |
loss_weight: 1.0 | |
reduction: mean | |
# Uncomment these for validation | |
# validation settings | |
# val: | |
# val_freq: !!float 5e3 | |
# save_img: True | |
# metrics: | |
# psnr: # metric name | |
# type: calculate_psnr | |
# crop_border: 4 | |
# test_y_channel: false | |
# logging settings | |
logger: | |
print_freq: 100 | |
save_checkpoint_freq: !!float 5e3 | |
use_tb_logger: true | |
wandb: | |
project: ~ | |
resume_id: ~ | |
# dist training settings | |
dist_params: | |
backend: nccl | |
port: 29500 | |