test_CAT_R_sr_x2.yml

# general settings
name: test_SR_CAT_R_x2
model_type: CATModel
scale: 2
num_gpu: 1
manual_seed: 10

datasets:
  test_1:  # the 1st test dataset
    task: SR
    name: Set5
    type: PairedImageDataset
    dataroot_gt: datasets/benchmark/Set5/HR
    dataroot_lq: datasets/benchmark/Set5/LR_bicubic/X2
    filename_tmpl: '{}x2'
    io_backend:
      type: disk

  test_2:  # the 2st test dataset
    task: SR
    name: Set14
    type: PairedImageDataset
    dataroot_gt: datasets/benchmark/Set14/HR
    dataroot_lq: datasets/benchmark/Set14/LR_bicubic/X2
    filename_tmpl: '{}x2'
    io_backend:
      type: disk

  test_3:  # the 3st test dataset
    task: SR
    name: B100
    type: PairedImageDataset
    dataroot_gt: datasets/benchmark/B100/HR
    dataroot_lq: datasets/benchmark/B100/LR_bicubic/X2
    filename_tmpl: '{}x2'
    io_backend:
      type: disk

  test_4:  # the 4st test dataset
    task: SR
    name: Urban100
    type: PairedImageDataset
    dataroot_gt: datasets/benchmark/Urban100/HR
    dataroot_lq: datasets/benchmark/Urban100/LR_bicubic/X2
    filename_tmpl: '{}x2'
    io_backend:
      type: disk

  test_5:  # the 5st test dataset
    task: SR
    name: Manga109
    type: PairedImageDataset
    dataroot_gt: datasets/benchmark/Manga109/HR
    dataroot_lq: datasets/benchmark/Manga109/LR_bicubic/X2
    filename_tmpl: '{}_LRBI_x2'
    io_backend:
      type: disk


# network structures
network_g:
  type: CAT
  upscale: 2
  in_chans: 3
  img_size: 64
  split_size_0: [4,4,4,4,4,4]
  split_size_1: [16,16,16,16,16,16] # The other side is H or W
  img_range: 1.
  depth: [6,6,6,6,6,6]
  embed_dim: 180
  num_heads: [6,6,6,6,6,6]
  mlp_ratio: 4
  resi_connection: '1conv'
  block_name: 'CATB_regular'
  upsampler: 'pixelshuffle'


# path
path:
  pretrain_network_g: experiments/pretrained_models/CAT-R/SR_CAT_R_x2.pth
  strict_load_g: True

# validation settings
val:
  save_img: False
  suffix: ~  # add suffix to saved images, if None, use exp name
  use_chop: False

  metrics:
    psnr: # metric name, can be arbitrary
      type: calculate_psnr
      crop_border: 2
      test_y_channel: True
    ssim:
      type: calculate_ssim
      crop_border: 2
      test_y_channel: True