Hugging Face's logo

Spaces:
akhaliq
/
GFPGAN
Runtime error

App Files Community
17
GFPGAN
File size: 4,593 Bytes 
f7acea1
 
 
13fd34d
f7acea1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13fd34d
f7acea1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
 
# general settings
name: train_GFPGANv1_512
model_type: GFPGANModel
num_gpu: auto  # officially, we use 4 GPUs
manual_seed: 0

# dataset and data loader settings
datasets:
  train:
    name: FFHQ
    type: FFHQDegradationDataset
    # dataroot_gt: datasets/ffhq/ffhq_512.lmdb
    dataroot_gt: datasets/ffhq/ffhq_512
    io_backend:
      # type: lmdb
      type: disk

    use_hflip: true
    mean: [0.5, 0.5, 0.5]
    std: [0.5, 0.5, 0.5]
    out_size: 512

    blur_kernel_size: 41
    kernel_list: ['iso', 'aniso']
    kernel_prob: [0.5, 0.5]
    blur_sigma: [0.1, 10]
    downsample_range: [0.8, 8]
    noise_range: [0, 20]
    jpeg_range: [60, 100]

    # color jitter and gray
    color_jitter_prob: 0.3
    color_jitter_shift: 20
    color_jitter_pt_prob: 0.3
    gray_prob: 0.01

    # If you do not want colorization, please set
    # color_jitter_prob: ~
    # color_jitter_pt_prob: ~
    # gray_prob: 0.01
    # gt_gray: True

    crop_components: true
    component_path: experiments/pretrained_models/FFHQ_eye_mouth_landmarks_512.pth
    eye_enlarge_ratio: 1.4

    # data loader
    use_shuffle: true
    num_worker_per_gpu: 6
    batch_size_per_gpu: 3
    dataset_enlarge_ratio: 1
    prefetch_mode: ~

  val:
    # Please modify accordingly to use your own validation
    # Or comment the val block if do not need validation during training
    name: validation
    type: PairedImageDataset
    dataroot_lq: datasets/faces/validation/input
    dataroot_gt: datasets/faces/validation/reference
    io_backend:
      type: disk
    mean: [0.5, 0.5, 0.5]
    std: [0.5, 0.5, 0.5]
    scale: 1

# network structures
network_g:
  type: GFPGANv1
  out_size: 512
  num_style_feat: 512
  channel_multiplier: 1
  resample_kernel: [1, 3, 3, 1]
  decoder_load_path: experiments/pretrained_models/StyleGAN2_512_Cmul1_FFHQ_B12G4_scratch_800k.pth
  fix_decoder: true
  num_mlp: 8
  lr_mlp: 0.01
  input_is_latent: true
  different_w: true
  narrow: 1
  sft_half: true

network_d:
  type: StyleGAN2Discriminator
  out_size: 512
  channel_multiplier: 1
  resample_kernel: [1, 3, 3, 1]

network_d_left_eye:
  type: FacialComponentDiscriminator

network_d_right_eye:
  type: FacialComponentDiscriminator

network_d_mouth:
  type: FacialComponentDiscriminator

network_identity:
  type: ResNetArcFace
  block: IRBlock
  layers: [2, 2, 2, 2]
  use_se: False

# path
path:
  pretrain_network_g: ~
  param_key_g: params_ema
  strict_load_g: ~
  pretrain_network_d: ~
  pretrain_network_d_left_eye: ~
  pretrain_network_d_right_eye: ~
  pretrain_network_d_mouth: ~
  pretrain_network_identity: experiments/pretrained_models/arcface_resnet18.pth
  # resume
  resume_state: ~
  ignore_resume_networks: ['network_identity']

# training settings
train:
  optim_g:
    type: Adam
    lr: !!float 2e-3
  optim_d:
    type: Adam
    lr: !!float 2e-3
  optim_component:
    type: Adam
    lr: !!float 2e-3

  scheduler:
    type: MultiStepLR
    milestones: [600000, 700000]
    gamma: 0.5

  total_iter: 800000
  warmup_iter: -1  # no warm up

  # losses
  # pixel loss
  pixel_opt:
    type: L1Loss
    loss_weight: !!float 1e-1
    reduction: mean
  # L1 loss used in pyramid loss, component style loss and identity loss
  L1_opt:
    type: L1Loss
    loss_weight: 1
    reduction: mean

  # image pyramid loss
  pyramid_loss_weight: 1
  remove_pyramid_loss: 50000
  # 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
    style_weight: 50
    range_norm: true
    criterion: l1
  # gan loss
  gan_opt:
    type: GANLoss
    gan_type: wgan_softplus
    loss_weight: !!float 1e-1
  # r1 regularization for discriminator
  r1_reg_weight: 10
  # facial component loss
  gan_component_opt:
    type: GANLoss
    gan_type: vanilla
    real_label_val: 1.0
    fake_label_val: 0.0
    loss_weight: !!float 1
  comp_style_weight: 200
  # identity loss
  identity_weight: 10

  net_d_iters: 1
  net_d_init_iters: 0
  net_d_reg_every: 16

# validation settings
val:
  val_freq: !!float 5e3
  save_img: true

  metrics:
    psnr: # metric name
      type: calculate_psnr
      crop_border: 0
      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

find_unused_parameters: true