deep-tempest/end-to-end/options/train_drunet.json

{
  "task": "drunet"  //  root/task/images-models-options
  , "model": "plain" // "plain"
  , "gpu_ids": [0]

  , "scale": 0       // broadcast to "netG" if SISR
  , "n_channels": 1  // broadcast to "datasets", 1 for grayscale, 3 for color
  , "n_channels_datasetload": 3 // broadcast to image training set
  , "use_abs_value": true // use absolute value of capture (true) or use real and complex values (false)

  , "path": {
    "root": "drunet_training"            // "denoising" | "superresolution"
    , "pretrained_netG": "path/to/model"    // path of pretrained model, if model from scratch type: null
  }

  , "datasets": {
    "train": {
      "name": "train_dataset"           // just name
      , "dataset_type": "ffdnet"         // "dncnn" | "dnpatch" for dncnn,  | "fdncnn" | "ffdnet" | "sr" | "srmd" | "dpsr" | "plain" | "plainpatch"
      , "dataroot_H": "path/to/train_original"// path of H training dataset
      , "dataroot_L": "path/to/train_degraded" // path of L training dataset, if using noisy H type: null
      , "sigma": [0, 20]      // 15, 25, 50 for DnCNN | [0, 75] for FFDNet and FDnCNN
      , "use_all_patches": true     // use or not all image patches
      , "skip_natural_patches": false// keep only non-natural image patches/text based image patches
      , "num_patches_per_image": 21   // number of random patches of training image, if not using all patches
      , "H_size": 256                    // patch size 40 | 64 | 96 | 128 | 192
      , "dataloader_shuffle": true
      , "dataloader_num_workers": 8
      , "dataloader_batch_size": 32     // batch size 1 | 16 | 32 | 48 | 64 | 128
    }
    , "test": {
      "name": "test_dataset"            // just name
      , "dataset_type": "ffdnet"         // "dncnn" | "dnpatch" for dncnn,  | "fdncnn" | "ffdnet" | "sr" | "srmd" | "dpsr" | "plain" | "plainpatch"
      , "dataroot_H": "path/to/val_original"  // path of H testing dataset
      , "dataroot_L": "path/to/val_degraded"   // path of L testing dataset
      , "sigma_test": 15 // 15, 25, 50 for DnCNN and ffdnet
    }
  }

  , "netG": {
    "net_type": "drunet" // "dncnn" | "fdncnn" | "ffdnet" | "srmd" | "dpsr" | "srresnet0" |  "srresnet1" | "rrdbnet" 
    , "in_nc": 2        // input channel number
    , "out_nc": 1       // ouput channel number
    , "nc": [64, 128, 256, 512]          // 64 for "dncnn"
    , "nb": 4          // 17 for "dncnn", 20 for dncnn3, 16 for "srresnet"
    , "gc": 32          // unused
    , "ng": 2           // unused
    , "reduction": 16  // unused
    , "act_mode": "R"  // "BR" for BN+ReLU | "R" for ReLU
    , "upsample_mode": "convtranspose"  // "pixelshuffle" | "convtranspose" | "upconv"
    , "downsample_mode": "strideconv"   // "strideconv" | "avgpool" | "maxpool"
    , "bias": false//
    , "init_type": "kaiming_normal"         // "orthogonal" | "normal" | "uniform" | "xavier_normal" | "xavier_uniform" | "kaiming_normal" | "kaiming_uniform"
    , "init_bn_type": "uniform"         // "uniform" | "constant"
    , "init_gain": 0.2
  }

  , "train": {
      "epochs": 10                       // number of epochs to train
    , "G_lossfn_type": "tv"               // "l1" preferred | tv | "l2sum" | "l2" | "ssim" 
    , "G_lossfn_weight": 1.0              // default
    , "G_tvloss_weight": 2.225479128512864e-13         // total variation weight
    , "G_tvloss_reduction": "mean"        // "sum" | "mean": Reduction for TV loss 

    , "G_optimizer_type": "adam"        // fixed, adam is enough
    , "G_optimizer_lr": 1.5435483950260915e-05       // learning rate
    , "G_optimizer_clipgrad": null      // unused

    , "G_scheduler_type": "MultiStepLR" // "MultiStepLR" is enough
    , "G_scheduler_milestones": [] // as batch iters
    , "G_scheduler_iter_step": 90180000 // use gamma factor on lr every this number of iter steps, null if using milestones
    , "G_scheduler_gamma": 0.5  //

    , "G_regularizer_orthstep": null    // unused
    , "G_regularizer_clipstep": null    // unused
    
    // epoch checkpoints
    , "checkpoint_test": 1            // for testing print
    , "checkpoint_test_save": 5       // for testing image saving
    , "checkpoint_save": 10           // for saving model
    , "checkpoint_print": 1           // for loss print
  }
}