Config file update

codes/options/test/test_ESRGAN_adrianna_full.yml

@@ -1,26 +1,28 @@
-name: RRDB_ESRGAN_x4
+name: adrianna
 suffix: ~  # add suffix to saved images
 model: sr
 distortion: sr
 scale: 4
 crop_border: ~  # crop border when evaluation. If None(~), crop the scale pixels
 gpu_ids: [0]
+amp_opt_level: O3
 
 datasets:
   test_1:  # the 1st test dataset
-    name: set5
+    name: kayden
     mode: LQ
-    batch_size: 3
+    batch_size: 13
-    dataroot_LQ: ..\..\datasets\adrianna\full_extract
+    dataroot_LQ: ..\..\datasets\kayden\images
+    start_at: 10000
 
 #### network structures
 network_G:
-  which_model_G: RRDBNet
+  which_model_G: ResGen
-  in_nc: 3
+  nf: 256
-  out_nc: 3
+  nb_denoiser: 20
-  nf: 48
+  nb_upsampler: 10
-  nb: 23
+  upscale_applications: 1
 
 #### path
 path:
-  pretrain_model_G: ../experiments/rrdb_blacked_gan_g.pth
+  pretrain_model_G: ../experiments/resgen_vgg_disc_vixen_40000.pth

codes/options/train/train_ESRGAN_blacked.yml

@@ -1,85 +0,0 @@
-#### general settings
-name: blacked_fix_and_upconv
-use_tb_logger: true
-model: srgan
-distortion: sr
-scale: 4
-gpu_ids: [0]
-amp_opt_level: O1
-
-#### datasets
-datasets:
-  train:
-    name: vixcloseup
-    mode: LQGT
-    dataroot_GT: K:\4k6k\4k_closeup\hr
-    dataroot_LQ: K:\4k6k\4k_closeup\lr_corrupted
-    doCrop: false
-    use_shuffle: true
-    n_workers: 0  # per GPU
-    batch_size: 40
-    target_size: 256
-    color: RGB
-  val:
-    name: adrianna_val
-    mode: LQGT
-    dataroot_GT: E:\4k6k\datasets\adrianna\val\hhq
-    dataroot_LQ: E:\4k6k\datasets\adrianna\val\hr
-
-#### network structures
-network_G:
-  which_model_G: RRDBNet
-  in_nc: 3
-  out_nc: 3
-  nf: 48
-  nb: 23
-network_D:
-  which_model_D: discriminator_resnet
-  in_nc: 3
-  nf: 48
-
-#### path
-path:
-  pretrain_model_G: ../experiments/rrdb_blacked_gan_g.pth
-  pretrain_model_D: ~
-  strict_load: true
-  resume_state: ../experiments/blacked_fix_and_upconv/training_state/16500.state
-
-#### training settings: learning rate scheme, loss
-train:
-  lr_G: !!float 1e-5
-  weight_decay_G: 0
-  beta1_G: 0.9
-  beta2_G: 0.99
-  lr_D: !!float 4e-5
-  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: [5000, 20000, 40000, 60000]
-  lr_gamma: 0.5
-  mega_batch_factor: 4
-
-  pixel_criterion: l1
-  pixel_weight: !!float 1e-2
-  feature_criterion: l1
-  feature_weight: 0
-  feature_weight_decay: .9
-  feature_weight_decay_steps: 501
-  feature_weight_minimum: 0
-  gan_type: gan  # gan | ragan
-  gan_weight: 1
-
-  D_update_ratio: 1
-  D_init_iters: 997
-
-  manual_seed: 10
-  val_freq: !!float 5e2
-
-#### logger
-logger:
-  print_freq: 50
-  save_checkpoint_freq: !!float 5e2

codes/options/train/train_ESRGAN_blacked_xl.yml

@@ -12,13 +12,13 @@ datasets:
   train:
     name: vixcloseup
     mode: LQGT
-    dataroot_GT: E:\4k6k\datasets\4k_closeup\hr
+    dataroot_GT: E:\4k6k\datasets\vixen\4k_closeup\hr
-    dataroot_LQ: [E:\4k6k\datasets\4k_closeup\lr_corrupted, E:\4k6k\datasets\4k_closeup\lr_c_blurred]
+    dataroot_LQ: [E:\4k6k\datasets\vixen\4k_closeup\lr_corrupted, E:\4k6k\datasets\vixen\4k_closeup\lr_c_blurred]
     doCrop: false
     use_shuffle: true
-    n_workers: 12  # per GPU
+    n_workers: 20  # per GPU
-    batch_size: 15
+    batch_size: 32
-    target_size: 256
+    target_size: 192
     color: RGB
   val:
     name: adrianna_val
@@ -29,27 +29,27 @@ datasets:
 #### network structures
 network_G:
   which_model_G: ResGen
-  nf: 256
+  nf: 164
-  nb_denoiser: 20
+  nb_denoiser: 12
-  nb_upsampler: 10
+  nb_upsampler: 8
 network_D:
   which_model_D: discriminator_resnet_passthrough
-  nf: 64
+  nf: 52
 
 #### path
 path:
   #pretrain_model_G: ../experiments/pretrained_resnet_G.pth
   #pretrain_model_D: ~
   strict_load: true
-  resume_state: ../experiments/blacked_fix_and_upconv_xl/training_state/2500.state
+  resume_state: ../experiments/blacked_fix_and_upconv_xl/training_state/68000.state
 
 #### training settings: learning rate scheme, loss
 train:
-  lr_G: !!float 1e-4
+  lr_G: !!float 6e-5
   weight_decay_G: 0
   beta1_G: 0.9
   beta2_G: 0.99
-  lr_D: !!float 2e-4
+  lr_D: !!float 6e-5
   weight_decay_D: 0
   beta1_D: 0.9
   beta2_D: 0.99
@@ -57,9 +57,9 @@ train:
 
   niter: 400000
   warmup_iter: -1  # no warm up
-  lr_steps: [20000, 40000, 50000, 60000]
+  lr_steps: [20000, 60000, 80000, 100000]
   lr_gamma: 0.5
-  mega_batch_factor: 3
+  mega_batch_factor: 2
 
   pixel_criterion: l1
   pixel_weight: !!float 1e-2
@@ -71,7 +71,7 @@ train:
   gan_type: gan  # gan | ragan
   gan_weight: !!float 1e-2
 
-  D_update_ratio: 2
+  D_update_ratio: 1
   D_init_iters: 0
 
   manual_seed: 10

codes/options/train/train_resgen_movies.yml

@@ -0,0 +1,83 @@
+#### general settings
+name: resgen_movies
+use_tb_logger: true
+model: srgan
+distortion: sr
+scale: 4
+gpu_ids: [0]
+amp_opt_level: O1
+
+#### datasets
+datasets:
+  train:
+    name: movies
+    mode: LQGT
+    dataroot_GT: F:\\upsample_reg\\for_training\\hr
+    dataroot_LQ: F:\\upsample_reg\\for_training\\lr_corrupted
+    doCrop: false
+    use_shuffle: true
+    n_workers: 8  # per GPU
+    batch_size: 8
+    target_size: 256
+    color: RGB
+  val:
+    name: movies_val
+    mode: LQGT
+    dataroot_GT: F:\\upsample_reg\\for_training\\val\\hr
+    dataroot_LQ: F:\\upsample_reg\\for_training\\val\\lr
+
+#### network structures
+network_G:
+  which_model_G: ResGenV2
+  nf: 256
+  nb_denoiser: 20
+  nb_upsampler: 10
+network_D:
+  which_model_D: discriminator_resnet_passthrough
+  nf: 64
+
+#### path
+path:
+  #pretrain_model_G: ~
+  #pretrain_model_D: ~
+  strict_load: true
+  resume_state: ~
+
+#### training settings: learning rate scheme, loss
+train:
+  lr_G: !!float 6e-5
+  weight_decay_G: 0
+  beta1_G: 0.9
+  beta2_G: 0.99
+  lr_D: !!float 6e-5
+  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: [20000, 60000, 80000, 100000]
+  lr_gamma: 0.5
+  mega_batch_factor: 1
+
+  pixel_criterion: l1
+  pixel_weight: !!float 1e-2
+  feature_criterion: l1
+  feature_weight: 1
+  feature_weight_decay: 1
+  feature_weight_decay_steps: 1
+  feature_weight_minimum: 1
+  gan_type: gan  # gan | ragan
+  gan_weight: !!float 1e-2
+
+  D_update_ratio: 1
+  D_init_iters: 0
+
+  manual_seed: 10
+  val_freq: !!float 5e2
+
+#### logger
+logger:
+  print_freq: 50
+  save_checkpoint_freq: !!float 5e2

codes/options/train/train_vix_corrupt.yml

@@ -0,0 +1,87 @@
+#### general settings
+name: train_vix_corrupt
+use_tb_logger: true
+model: corruptgan
+distortion: downsample
+scale: 1
+gpu_ids: [0]
+amp_opt_level: O1
+
+#### datasets
+datasets:
+  train:
+    name: blacked
+    mode: downsample
+    dataroot_GT: K:\\4k6k\\4k_closeup\\lr_corrupted
+    dataroot_LQ: G:\\data\\pr_upsample\\ultra_lowq\\for_training\\lr
+    mismatched_Data_OK: true
+    use_shuffle: true
+    n_workers: 0 # per GPU
+    batch_size: 1
+    target_size: 64
+    use_flip: false
+    use_rot: false
+    doCrop: false
+    color: RGB
+  val:
+    name: blacked_val
+    mode: downsample
+    target_size: 64
+    dataroot_GT: E:\\4k6k\\datasets\\vixen\\val
+    dataroot_LQ: E:\\4k6k\\datasets\\vixen\\val
+
+#### network structures
+network_G:
+  which_model_G: ResGenV2
+  nf: 16
+  nb_denoiser: 5
+  nb_upsampler: 0
+  upscale_applications: 0
+
+network_D:
+  which_model_D: discriminator_vgg_128
+  in_nc: 3
+  nf: 16
+
+#### path
+path:
+  pretrain_model_G: ~
+  pretrain_model_D: ~
+  resume_state: ~
+  strict_load: true
+
+#### training settings: learning rate scheme, loss
+train:
+  lr_G: !!float 5e-5
+  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: [30000, 60000, 100000, 200000]
+  lr_gamma: 0.5
+
+  pixel_criterion: l2
+  pixel_weight: !!float 1e-2
+  feature_criterion: l1
+  feature_weight: 0
+  gan_type: gan  # gan | ragan
+  gan_weight: !!float 1e-1
+  mega_batch_factor: 1
+
+  D_update_ratio: 1
+  D_init_iters: -1
+
+  manual_seed: 10
+  val_freq: !!float 5e2
+
+#### logger
+logger:
+  print_freq: 50
+  save_checkpoint_freq: !!float 5e2