Predictor:
  Model:
    classpath: model:Unet_TS_CT
    Unet_TS_CT:
      outputs_criterions: None
      channels:
      - 1
      - 32
      - 64
      - 128
      - 256
      - 320
  Dataset:
    groups_src:
      Volume_0:
        groups_dest:
          Volume:
            transforms:
              TensorCast:
                dtype: float32
                inverse: false
              Canonical:
                inverse: true
              ResampleToResolution:
                spacing:
                - 3
                - 3
                - 3
                inverse: true
              Standardize:
                lazy: false
                mean: None
                std: None
                mask: None
                inverse: false
              Padding:
                padding:
                - 32
                - 32
                - 32
                - 32
                - 32
                - 32
                mode: constant
                inverse: true
            patch_transforms: None
            is_input: true
    augmentations: None
    Patch:
      patch_size:
      - 96
      - 128
      - 160
      overlap: 32
      mask: None
      pad_value: 0
      extend_slice: 0
    subset: None
    filter: None
    dataset_filenames:
    - ./Dataset/:mha
    use_cache: false
    batch_size: 1
  outputs_dataset:
    Head:Softmax:
      OutputDataset:
        name_class: OutSameAsGroupDataset
        before_reduction_transforms: 
          Softmax:
            dim: 0
          Argmax:
            dim: 0
          TensorCast:
            dtype: uint8
            inverse: true
        after_reduction_transforms: 
          Sum:
            dim: 0
        final_transforms: None
        dataset_filename: Output:mha
        group: Output
        same_as_group: Volume_0:Volume
        patch_combine: Cosinus
        inverse_transform: true
        reduction: Mean
  train_name: TotalSegmentator
  manual_seed: 32
  gpu_checkpoints: None
  images_log: None
  combine: Concat
  autocast: false
  data_log: None