raise1k.yaml

# Experiment Name - used to store files
id: raise1k

# Wandb settings
wandb:
  run_id: ${experiment.id}

# Training settings
train:
  max_epochs: 150
  max_steps: 2000
  batch_size: 128
  early_stopping_patience: 5
  device: "gpu"
  random_seed: 123
  load_from_checkpoint: ""

# Model settings
model:
  depth: 20
  in_channels: 3
  channels: 64
  kernel_size: 3
  normalization: "BN"

# Data settings
data:
  dataset: "raise1k"
  patch_size: 64
  max_patches_per_image: 200
  # noise type to add "awgn_only" or "combined"
  train_noise_type: "awgn_only"
  train_noise_level_interval: [0, 55]
  #train_noise_level_interval: [0, 15]
  train_up_down_factors: [2, 3, 4]
  train_jpeg_min_max: [5, 99]
  val_noise_type: "awgn_only"
  val_up_down_factors: [2, 3, 4]
  val_jpeg_min_max: [5, 99]
  val_noise_level_interval: [25, 25]
  #val_noise_level_interval: [10, 10]