metaportrait

sr_model/Basicsr/options/test/EDVR/test_EDVR_L_deblurcomp_REDS.yml

+name: EDVR_L_REDS_deblurcomp_official
+model_type: EDVRModel
+scale: 1
+num_gpu: 4  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test:
+    name: REDS4
+    type: VideoTestDataset
+    dataroot_gt: datasets/REDS/train_sharp
+    dataroot_lq: datasets/REDS/train_blur_comp
+    meta_info_file: basicsr/data/meta_info/meta_info_REDS4_test_GT.txt
+    io_backend:
+      type: disk
+
+    cache_data: false
+    num_frame: 5
+    padding: replicate
+
+# network structures
+network_g:
+  type: EDVR
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 128
+  num_frame: 5
+  deformable_groups: 8
+  num_extract_block: 5
+  num_reconstruct_block: 40
+  center_frame_idx: ~
+  hr_in: true
+  with_predeblur: true
+  with_tsa: true
+
+# path
+path:
+  pretrain_network_g: experiments/pretrained_models/EDVR/EDVR_L_deblurcomp_REDS_official-0e988e5c.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: false

sr_model/Basicsr/options/test/EDVR/test_EDVR_L_x4_SR_REDS.yml

+name: EDVR_L_x4_REDS_SR_official
+model_type: EDVRModel
+scale: 4
+num_gpu: 4  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test:
+    name: REDS4
+    type: VideoTestDataset
+    dataroot_gt: datasets/REDS/train_sharp
+    dataroot_lq: datasets/REDS/train_sharp_bicubic
+    meta_info_file: basicsr/data/meta_info/meta_info_REDS4_test_GT.txt
+    io_backend:
+      type: disk
+
+    cache_data: false
+    num_frame: 5
+    padding: reflection_circle
+
+# network structures
+network_g:
+  type: EDVR
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 128
+  num_frame: 5
+  deformable_groups: 8
+  num_extract_block: 5
+  num_reconstruct_block: 40
+  center_frame_idx: ~
+  hr_in: false
+  with_predeblur: false
+  with_tsa: true
+
+# path
+path:
+  pretrain_network_g: experiments/pretrained_models/EDVR/EDVR_L_x4_SR_REDS_official-9f5f5039.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: false

sr_model/Basicsr/options/test/EDVR/test_EDVR_L_x4_SR_Vid4.yml

+name: EDVR_L_x4_Vimeo90K_SR_official
+model_type: EDVRModel
+scale: 4
+num_gpu: 4  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test:
+    name: Vid4
+    type: VideoTestDataset
+    dataroot_gt: datasets/Vid4/GT
+    dataroot_lq: datasets/Vid4/BIx4
+    io_backend:
+      type: disk
+
+    cache_data: false
+    num_frame: 7
+    padding: reflection_circle
+
+# network structures
+network_g:
+  type: EDVR
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 128
+  num_frame: 7
+  deformable_groups: 8
+  num_extract_block: 5
+  num_reconstruct_block: 40
+  center_frame_idx: ~
+  hr_in: false
+  with_predeblur: false
+  with_tsa: true
+
+# path
+path:
+  pretrain_network_g: experiments/pretrained_models/EDVR/EDVR_L_x4_SR_Vimeo90K_official-162b54e4.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: false

sr_model/Basicsr/options/test/EDVR/test_EDVR_L_x4_SR_Vimeo90K.yml

+name: EDVR_L_x4_Vimeo90K_SR_official
+model_type: EDVRModel
+scale: 4
+num_gpu: 8  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test:
+    name: Vimeo90K-Test
+    type: VideoTestVimeo90KDataset
+    dataroot_gt: datasets/vimeo90k/vimeo_septuplet/sequences
+    dataroot_lq: datasets/vimeo90k/vimeo_septuplet_matlabLRx4/sequences
+    meta_info_file: basicsr/data/meta_info/meta_info_Vimeo90K_test_GT.txt
+    io_backend:
+      type: disk
+
+    cache_data: false
+    num_frame: 7
+    padding: reflection_circle
+
+# network structures
+network_g:
+  type: EDVR
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 128
+  num_frame: 7
+  deformable_groups: 8
+  num_extract_block: 5
+  num_reconstruct_block: 40
+  center_frame_idx: ~
+  hr_in: false
+  with_predeblur: false
+  with_tsa: true
+
+# path
+path:
+  pretrain_network_g: experiments/pretrained_models/EDVR/EDVR_L_x4_SR_Vimeo90K_official-162b54e4.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: false

sr_model/Basicsr/options/test/EDVR/test_EDVR_L_x4_SRblur_REDS.yml

+name: EDVR_L_x4_REDS_SRblur_official
+model_type: EDVRModel
+scale: 4
+num_gpu: 4  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test:
+    name: REDS4
+    type: VideoTestDataset
+    dataroot_gt: datasets/REDS/train_sharp
+    dataroot_lq: datasets/REDS/train_blur_bicubic
+    meta_info_file: basicsr/data/meta_info/meta_info_REDS4_test_GT.txt
+    io_backend:
+      type: disk
+
+    cache_data: false
+    num_frame: 5
+    padding: replicate
+
+# network structures
+network_g:
+  type: EDVR
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 128
+  num_frame: 5
+  deformable_groups: 8
+  num_extract_block: 5
+  num_reconstruct_block: 40
+  center_frame_idx: ~
+  hr_in: false
+  with_predeblur: true
+  with_tsa: true
+
+# path
+path:
+  pretrain_network_g: experiments/pretrained_models/EDVR/EDVR_L_x4_SRblur_REDS_official-983d7b8e.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: false

sr_model/Basicsr/options/test/EDVR/test_EDVR_M_x4_SR_REDS.yml

+name: EDVR_M_x4_SR_REDS_official
+model_type: EDVRModel
+scale: 4
+num_gpu: 4  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test:
+    name: REDS4
+    type: VideoTestDataset
+    dataroot_gt: datasets/REDS/train_sharp
+    dataroot_lq: datasets/REDS/train_sharp_bicubic
+    meta_info_file: basicsr/data/meta_info/meta_info_REDS4_test_GT.txt
+    io_backend:
+      type: disk
+
+    cache_data: false
+    num_frame: 5
+    padding: reflection_circle
+
+# network structures
+network_g:
+  type: EDVR
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 64
+  num_frame: 5
+  deformable_groups: 8
+  num_extract_block: 5
+  num_reconstruct_block: 10
+  center_frame_idx: ~
+  hr_in: false
+  with_predeblur: false
+  with_tsa: true
+
+# path
+path:
+  pretrain_network_g: experiments/pretrained_models/EDVR/EDVR_M_x4_SR_REDS_official-32075921.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: false

sr_model/Basicsr/options/test/ESRGAN/test_ESRGAN_x4.yml

+name: ESRGAN_SRx4_DF2KOST_official
+model_type: ESRGANModel
+scale: 4
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: Set5
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set5/GTmod12
+    dataroot_lq: datasets/Set5/LRbicx4
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: Set14
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set14/GTmod12
+    dataroot_lq: datasets/Set14/LRbicx4
+    io_backend:
+      type: disk
+
+  test_3:
+    name: DIV2K100
+    type: PairedImageDataset
+    dataroot_gt: datasets/DIV2K/DIV2K_valid_HR
+    dataroot_lq: datasets/DIV2K/DIV2K_valid_LR_bicubic/X4
+    filename_tmpl: '{}x4'
+    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/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 4
+      test_y_channel: false
+    ssim:
+      type: calculate_ssim
+      crop_border: 4
+      test_y_channel: false

sr_model/Basicsr/options/test/ESRGAN/test_ESRGAN_x4_woGT.yml

+name: ESRGAN_SRx4_DF2KOST_official
+model_type: ESRGANModel
+scale: 4
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: Set5
+    type: SingleImageDataset
+    dataroot_lq: datasets/Set5/LRbicx4
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: Set14
+    type: SingleImageDataset
+    dataroot_lq: datasets/Set14/LRbicx4
+    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/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name

sr_model/Basicsr/options/test/ESRGAN/test_RRDBNet_PSNR_x4.yml

+name: ESRGAN_PSNR_SRx4_DF2K_official
+model_type: SRModel
+scale: 4
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: Set5
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set5/GTmod12
+    dataroot_lq: datasets/Set5/LRbicx4
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: Set14
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set14/GTmod12
+    dataroot_lq: datasets/Set14/LRbicx4
+    io_backend:
+      type: disk
+
+  test_3:
+    name: DIV2K100
+    type: PairedImageDataset
+    dataroot_gt: datasets/DIV2K/DIV2K_valid_HR
+    dataroot_lq: datasets/DIV2K/DIV2K_valid_LR_bicubic/X4
+    filename_tmpl: '{}x4'
+    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/ESRGAN_PSNR_SRx4_DF2K_official-150ff491.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 4
+      test_y_channel: false
+    ssim:
+      type: calculate_ssim
+      crop_border: 4
+      test_y_channel: false

sr_model/Basicsr/options/test/HiFaceGAN/test_hifacegan.yml

+name: HiFaceGAN_SR4x_test
+model_type: HiFaceGANModel
+scale: 1    # HiFaceGAN does not resize lq input
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_gt:  # the 2nd test dataset
+    name: FFHQ_sr4x_val
+    type: PairedImageDataset
+    dataroot_gt: datasets/FFHQ_512_gt_val
+    dataroot_lq: datasets/FFHQ_512_lq_val_sr4x
+    io_backend:
+      type: disk
+
+# network structures
+network_g:
+  type: HiFaceGAN
+  num_in_ch: 3
+  num_feat: 48
+  use_vae: false
+  z_dim: 256  # dummy var
+  crop_size: 512
+  #norm_g: 'spectralspadesyncbatch3x3'
+  #norm_g: 'spectralspadeinstance3x3'
+  norm_g: 'spectralspadebatch3x3'  # 20210519: Use batchnorm for now.
+  is_train: false                  # HifaceGAN supports progressive training
+                                   # so network architecture depends on it
+
+# path
+path:
+  pretrain_network_g: experiments/HiFaceGAN_SR4x_train_full/models/net_g_latest.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 4
+      test_y_channel: false
+    ssim:
+      type: calculate_ssim
+      crop_border: 4
+      test_y_channel: false
+
+    # More metrics will be supported in the next update
+    #
+    # msssim:
+    #   type: calculate_msssim
+    #   crop_border: 4
+    #   test_y_channel: false
+    # lpips:
+    #   type: calculate_lpips
+    #   crop_border: 4
+    #   test_y_channel: false
+    # niqe:
+    #   type: calculate_niqe
+    #   crop_border: 4
+    #   num_thread: 8
+    # fid:
+    #   type: calculate_fid
+    #   crop_border: 0
+    #   test_y_channel: false
+    #   use_bgr_order: true
+    # face_embedding_distance:
+    #   type: calculate_fed
+    #   crop_border: 0
+    #   test_y_channel: false
+    # face_landmark_distance:
+    #   type: calculate_lle
+    #   crop_border: 0
+    #   test_y_channel: false

sr_model/Basicsr/options/test/HiFaceGAN/test_hifacegan_woGT.yml

+name: HiFaceGAN_generic_test
+model_type: HiFaceGANModel
+scale: 1    # HiFaceGAN does not resize lq input
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_wild:  # the 1st test dataset
+    name: FFHQ_in_the_wild
+    type: SingleImageDataset
+    dataroot_lq: datasets/real-world-lq
+    io_backend:
+      type: disk
+
+# network structures
+network_g:
+  type: HiFaceGAN # or SPADEGenerator
+  num_in_ch: 3
+  num_feat: 48
+  use_vae: false
+  z_dim: 256  # dummy var
+  crop_size: 512
+  #norm_g: 'spectralspadesyncbatch3x3'
+  norm_g: 'spectralspadebatch3x3'  # 20210519: Use instance norm for now.
+  is_train: false                  # HifaceGAN supports progressive training
+                                   # so network architecture depends on it
+
+# path
+path:
+  pretrain_network_g: experiments/pretrained_models/generic/latest_net_G.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: generic  # add suffix to saved images, if None, use exp name
+  # No metrics

sr_model/Basicsr/options/test/RCAN/test_RCAN.yml

+name: RCAN_BIX4-official
+suffix: ~  # add suffix to saved images
+model_type: SRModel
+scale: 4
+crop_border: ~  # crop border when evaluation. If None, crop the scale pixels
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: val_set5
+    type: PairedImageDataset
+    dataroot_gt: ./datasets/val_set5/Set5
+    dataroot_lq: ./datasets/val_set5/Set5_bicLRx4
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: val_set14
+    type: PairedImageDataset
+    dataroot_gt: ./datasets/val_set14/Set14
+    dataroot_lq: ./datasets/val_set14/Set14_bicLRx4
+    io_backend:
+      type: disk
+
+  test_3:
+    name: div2k100
+    type: PairedImageDataset
+    dataroot_gt: ./datasets/DIV2K100/DIV2K_valid_HR
+    dataroot_lq: ./datasets/DIV2K100/DIV2K_valid_bicLRx4
+    filename_tmpl: '{}x4'
+    io_backend:
+      type: disk
+
+# network structures
+network_g:
+  type: RCAN
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 64
+  num_group: 10
+  num_block: 20
+  squeeze_factor: 16
+  upscale: 4
+  res_scale: 1
+  img_range: 255.
+  rgb_mean: [0.4488, 0.4371, 0.4040]
+
+save_img: true
+
+# path
+path:
+  pretrain_network_g: ./experiments/pretrained_models/RCAN/RCAN_BIX4-official.pth
+  strict_load_g: true

sr_model/Basicsr/options/test/SRResNet_SRGAN/test_MSRGAN_x4.yml

+name: 004_MSRGAN_x4_f64b16_DIV2K_400k_B16G1_wandb
+model_type: SRGANModel
+scale: 4
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: Set5
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set5/GTmod12
+    dataroot_lq: datasets/Set5/LRbicx4
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: Set14
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set14/GTmod12
+    dataroot_lq: datasets/Set14/LRbicx4
+    io_backend:
+      type: disk
+
+  test_3:
+    name: DIV2K100
+    type: PairedImageDataset
+    dataroot_gt: datasets/DIV2K/DIV2K_valid_HR
+    dataroot_lq: datasets/DIV2K/DIV2K_valid_LR_bicubic/X4
+    filename_tmpl: '{}x4'
+    io_backend:
+      type: disk
+
+# network structures
+network_g:
+  type: MSRResNet
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 64
+  num_block: 16
+  upscale: 4
+
+# path
+path:
+  pretrain_network_g: experiments/004_MSRGAN_x4_f64b16_DIV2K_400k_B16G1_wandb/models/net_g_400000.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 4
+      test_y_channel: false
+    ssim:
+      type: calculate_ssim
+      crop_border: 4
+      test_y_channel: false

sr_model/Basicsr/options/test/SRResNet_SRGAN/test_MSRResNet_x2.yml

+name: 002_MSRResNet_x2_f64b16_DIV2K_1000k_B16G1_001pretrain_wandb
+model_type: SRModel
+scale: 2
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: Set5
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set5/GTmod12
+    dataroot_lq: datasets/Set5/LRbicx2
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: Set14
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set14/GTmod12
+    dataroot_lq: datasets/Set14/LRbicx2
+    io_backend:
+      type: disk
+
+  test_3:
+    name: DIV2K100
+    type: PairedImageDataset
+    dataroot_gt: datasets/DIV2K/DIV2K_valid_HR
+    dataroot_lq: datasets/DIV2K/DIV2K_valid_LR_bicubic/X2
+    filename_tmpl: '{}x2'
+    io_backend:
+      type: disk
+
+# network structures
+network_g:
+  type: MSRResNet
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 64
+  num_block: 16
+  upscale: 2
+
+# path
+path:
+  pretrain_network_g: experiments/002_MSRResNet_x2_f64b16_DIV2K_1000k_B16G1_001pretrain_wandb/models/net_g_1000000.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 2
+      test_y_channel: false
+    ssim:
+      type: calculate_ssim
+      crop_border: 2
+      test_y_channel: false

sr_model/Basicsr/options/test/SRResNet_SRGAN/test_MSRResNet_x3.yml

+name: 003_MSRResNet_x3_f64b16_DIV2K_1000k_B16G1_001pretrain_wandb
+model_type: SRModel
+scale: 3
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: Set5
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set5/GTmod12
+    dataroot_lq: datasets/Set5/LRbicx3
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: Set14
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set14/GTmod12
+    dataroot_lq: datasets/Set14/LRbicx3
+    io_backend:
+      type: disk
+
+  test_3:
+    name: DIV2K100
+    type: PairedImageDataset
+    dataroot_gt: datasets/DIV2K/DIV2K_valid_HR
+    dataroot_lq: datasets/DIV2K/DIV2K_valid_LR_bicubic/X3
+    filename_tmpl: '{}x3'
+    io_backend:
+      type: disk
+
+# network structures
+network_g:
+  type: MSRResNet
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 64
+  num_block: 16
+  upscale: 3
+
+# path
+path:
+  pretrain_network_g: experiments/003_MSRResNet_x3_f64b16_DIV2K_1000k_B16G1_001pretrain_wandb/models/net_g_1000000.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 3
+      test_y_channel: false
+    ssim:
+      type: calculate_ssim
+      crop_border: 3
+      test_y_channel: false

sr_model/Basicsr/options/test/SRResNet_SRGAN/test_MSRResNet_x4.yml

+name: 001_MSRResNet_x4_f64b16_DIV2K_1000k_B16G1_wandb
+model_type: SRModel
+scale: 4
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: Set5
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set5/GTmod12
+    dataroot_lq: datasets/Set5/LRbicx4
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: Set14
+    type: PairedImageDataset
+    dataroot_gt: datasets/Set14/GTmod12
+    dataroot_lq: datasets/Set14/LRbicx4
+    io_backend:
+      type: disk
+
+  test_3:
+    name: DIV2K100
+    type: PairedImageDataset
+    dataroot_gt: datasets/DIV2K/DIV2K_valid_HR
+    dataroot_lq: datasets/DIV2K/DIV2K_valid_LR_bicubic/X4
+    filename_tmpl: '{}x4'
+    io_backend:
+      type: disk
+
+# network structures
+network_g:
+  type: MSRResNet
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 64
+  num_block: 16
+  upscale: 4
+
+# path
+path:
+  pretrain_network_g: experiments/001_MSRResNet_x4_f64b16_DIV2K_1000k_B16G1_wandb/models/net_g_1000000.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 4
+      test_y_channel: false
+    ssim:
+      type: calculate_ssim
+      crop_border: 4
+      test_y_channel: false

sr_model/Basicsr/options/test/SRResNet_SRGAN/test_MSRResNet_x4_woGT.yml

+name: 001_MSRResNet_x4_f64b16_DIV2K_1000k_B16G1_wandb
+model_type: SRModel
+scale: 4
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test_1:  # the 1st test dataset
+    name: Set5
+    type: SingleImageDataset
+    dataroot_lq: datasets/Set5/LRbicx4
+    io_backend:
+      type: disk
+  test_2:  # the 2nd test dataset
+    name: Set14
+    type: SingleImageDataset
+    dataroot_lq: datasets/Set14/LRbicx4
+    io_backend:
+      type: disk
+
+# network structures
+network_g:
+  type: MSRResNet
+  num_in_ch: 3
+  num_out_ch: 3
+  num_feat: 64
+  num_block: 16
+  upscale: 4
+
+# path
+path:
+  pretrain_network_g: experiments/001_MSRResNet_x4_f64b16_DIV2K_1000k_B16G1_wandb/models/net_g_1000000.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name

sr_model/Basicsr/options/test/TOF/test_TOF_official.yml

+name: TOF_official
+model_type: VideoBaseModel
+scale: 4
+num_gpu: 1  # set num_gpu: 0 for cpu mode
+manual_seed: 0
+
+datasets:
+  test:
+    name: Vid4
+    type: VideoTestDataset
+    dataroot_gt: datasets/Vid4/GT
+    dataroot_lq: datasets/Vid4/BIx4up_direct
+    io_backend:
+      type: disk
+
+    cache_data: false
+    num_frame: 7
+    padding: reflection_circle
+
+# network structures
+network_g:
+  type: TOFlow
+  adapt_official_weights: true
+
+save_img: true
+
+# path
+path:
+  pretrain_network_g: experiments/pretrained_models/TOF/tof_x4_vimeo90k_official-32c9e01f.pth
+  strict_load_g: true
+
+# validation settings
+val:
+  save_img: true
+  suffix: ~  # add suffix to saved images, if None, use exp name
+
+  metrics:
+    psnr_y: # metric name, can be arbitrary
+      type: calculate_psnr
+      crop_border: 0
+      test_y_channel: true
+    ssim_y:
+      type: calculate_ssim
+      crop_border: 0
+      test_y_channel: true

sr_model/Basicsr/options/train/BasicVSR/0928_train_BasicVSR_REDS.yml

+# general settings
+# CUDA_VISIBLE_DEVICES=6 python basicsr/train.py -opt options/train/BasicVSR/0928_train_BasicVSR_REDS.yml --debug
+name: 0928_train_BasicVSR_REDS
+model_type: VideoRecurrentModel
+scale: 4
+num_gpu: auto  # official: 8 GPUs
+manual_seed: 0
+
+# dataset and data loader settings
+datasets:
+  train:
+    name: REDS
+    type: REDSRecurrentDataset
+    dataroot_gt: datasets/data/REDS/train/train_sharp
+    dataroot_lq: datasets/data/REDS/train/train_sharp_bicubic/X4
+    meta_info_file: basicsr/data/meta_info/meta_info_REDS_GT.txt
+    val_partition: REDS4  # set to 'official' when use the official validation partition
+    test_mode: False
+    io_backend:
+      type: disk
+
+    num_frame: 15
+    gt_size: 256
+    interval_list: [1]
+    random_reverse: false
+    use_hflip: true
+    use_rot: true
+
+    # data loader
+    use_shuffle: true
+    num_worker_per_gpu: 6
+    batch_size_per_gpu: 4
+    dataset_enlarge_ratio: 200
+    prefetch_mode: ~
+
+  val:
+    name: REDS4
+    type: VideoRecurrentTestDataset
+    dataroot_gt: datasets/data/REDS4/GT
+    dataroot_lq: datasets/data/REDS4/sharp_bicubic
+    cache_data: True
+    io_backend:
+      type: disk
+    num_frame: -1  # not needed
+
+# network structures
+network_g:
+  type: BasicVSR
+  num_feat: 64
+  num_block: 30
+  spynet_path: experiments/pretrained_models/flownet/spynet_sintel_final-3d2a1287.pth
+
+# path
+path:
+  pretrain_network_g: ~
+  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: CosineAnnealingRestartLR
+    periods: [300000]
+    restart_weights: [1]
+    eta_min: !!float 1e-7
+
+  total_iter: 300000
+  warmup_iter: -1  # no warm up
+  fix_flow: 5000
+  flow_lr_mul: 0.125
+
+  # losses
+  pixel_opt:
+    type: CharbonnierLoss
+    loss_weight: 1.0
+    reduction: mean
+
+# validation settings
+val:
+  val_freq: !!float 5e3
+  save_img: false
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      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

sr_model/Basicsr/options/train/BasicVSR/0928_train_BasicVSR_hdtf3.yml

+# general settings
+# CUDA_VISIBLE_DEVICES=5 python basicsr/train.py -opt options/train/BasicVSR/0928_train_BasicVSR_hdtf3.yml --debug
+name: 0928_train_BasicVSR_hdtf3
+model_type: VideoRecurrentModel
+scale: 2
+num_gpu: auto  # official: 8 GPUs
+manual_seed: 0
+
+# dataset and data loader settings
+datasets:
+  train:
+    name: HDTF
+    type: HDTFRecurrentDataset
+    dataroot_gt: datasets/data/HDTF_images_100/512
+    dataroot_lq: datasets/data/HDTF_images_100/256
+    test_mode: False
+    io_backend:
+      type: disk
+
+    num_frame: 7
+    gt_size: 512
+    interval_list: [1]
+    random_reverse: false
+    use_hflip: true
+    use_rot: False
+
+    # data loader
+    use_shuffle: true
+    num_worker_per_gpu: 6
+    batch_size_per_gpu: 1
+    dataset_enlarge_ratio: 200
+    prefetch_mode: ~
+
+  val:
+    name: REDS4
+    type: VideoRecurrentTestDataset
+    dataroot_gt: datasets/data/HDTF_images_100/512
+    dataroot_lq: datasets/data/HDTF_images_100/256
+    cache_data: True
+    io_backend:
+      type: disk
+    num_frame: -1  # not needed
+
+# network structures
+network_g:
+  type: BasicVSR
+  num_feat: 64
+  num_block: 30
+  spynet_path: experiments/pretrained_models/flownet/spynet_sintel_final-3d2a1287.pth
+  scale: 2
+
+# path
+path:
+  pretrain_network_g: ~
+  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: CosineAnnealingRestartLR
+    periods: [300000]
+    restart_weights: [1]
+    eta_min: !!float 1e-7
+
+  total_iter: 300000
+  warmup_iter: -1  # no warm up
+  fix_flow: 5000
+  flow_lr_mul: 0.125
+
+  # losses
+  pixel_opt:
+    type: CharbonnierLoss
+    loss_weight: 1.0
+    reduction: mean
+
+# validation settings
+val:
+  val_freq: !!float 5e3
+  save_img: true
+
+  metrics:
+    psnr: # metric name, can be arbitrary
+      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