Hugging Face's logo

Spaces:
akhaliq
/
Real-ESRGAN
Runtime error

App Files Community
11
Real-ESRGAN
File size: 3,134 Bytes 
bf91721
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
 
# general settings
name: train_RealESRNetx4plus_1000k_B12G4_fromESRGAN
model_type: RealESRNetModel
scale: 4
num_gpu: 4
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: realesrgan/data/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, can be arbitrary
#       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