model_config_test.json

{
  "command": "eval",
  "gpu": 0,
  "path_output": "testing_script",
  "debugging": false,
  "model_name": "model_unet_test",
  "object_detection_params": {
    "object_detection_path": null
  },
  "loader_parameters": {
    "target_suffix": ["_lesion-manual"],
    "roi_suffix": null,
    "path_data": "testing_data/",
    "roi_params": {
      "suffix": null,
      "slice_filter_roi": null
    },
    "contrast_params": {
      "random_seed": 1313,
      "training_validation": [
        "T2w"
      ],
      "balance": {},
      "testing": [
        "T2w"
      ],
      "center_test": []
    },
    "slice_filter_params": {
      "filter_empty_mask": false,
      "filter_empty_input": true
    },
    "slice_axis": "axial",
    "split_method": "per_patient",
    "multichannel": false,
    "soft_input": false
  },
  "split_dataset": {
    "fname_split": null,
    "random_seed": 1313,
    "method": "per_patient",
    "train_fraction": 0.66,
    "test_fraction": 0.33,
    "center_test": []
  },
  "training_parameters": {
    "batch_size": 32,
    "loss": {
      "name": "DiceLoss"
    },
    "training_time": {
      "num_epochs": 1,
      "early_stopping_patience": 50,
      "early_stopping_epsilon": 0.001
    },
    "scheduler": {
      "initial_lr": 0.001,
      "lr_scheduler": {
        "name": "CosineAnnealingLR",
        "base_lr": 1e-5,
        "max_lr": 1e-2
      }
    },
    "balance_samples": false,
    "mixup_alpha": null,
    "transfer_learning": {
      "retrain_model": null,
      "retrain_fraction": 1.0
    }
  },
  "default_model": {
    "name": "Unet",
    "dropout_rate": 0.3,
    "bn_momentum": 0.1,
    "out_channel": 1,
    "depth": 1
  },
  "FiLMedUnet": {
    "applied": false,
    "metadata": "contrasts",
    "film_layers": [0, 1, 0, 0, 0, 0, 0, 0, 0, 0]
  },
  "missing_modality": false,
  "attention_unet": false,
  "mixup_bool": false,
  "metadata": null,
  "uncertainty": {
    "epistemic": true,
    "aleatoric": true,
    "n_it": 2
  },
  "postprocessing": {
    "remove_noise": {"thr": 0.01},
    "keep_largest": {},
    "binarize_prediction": {"thr": 0.5},
    "fill_holes": {},
    "remove_small": {"unit": "vox", "thr": 3},
    "uncertainty": {"thr": 0.4, "suffix": "_unc-vox.nii.gz"}
  },
  "evaluation_parameters": {
    "targetSize": {
      "unit": "vox",
      "thr": [
        20,
        100
      ]
    },
    "overlap": {
      "unit": "vox",
      "thr": 3
    }
  },
  "transformation": {
    "Resample": {
      "wspace": 0.75,
      "hspace": 0.75
    },
    "NumpyToTensor": {},
    "NormalizeInstance": {
      "applied_to": ["im"]
    }
  }
}