train_config.yml

# Sample configuration file for training a 3D U-Net on a task of predicting the boundaries in 3D stack of the Arabidopsis
# ovules acquired with the confocal microscope. Training done with a combination of Binary Cross-Entropy and DiceLoss.
# Download train data from: https://osf.io/x9yns/
# Download validation data from: https://osf.io/xp5uf/
# Download test data from: https://osf.io/8jz7e/

eval_metric:
  name: BoundaryAdaptedRandError
  threshold: 0.4
  use_first_input: true
  use_last_target: true
loaders:
  dataset: StandardHDF5Dataset
  batch_size: 4
  label_internal_path: /label
  num_workers: 8
  raw_internal_path: /raw
  train:
    file_paths:
      - "/home/adrian/Datasets/Ovules/Train"

    slice_builder:
      name: FilterSliceBuilder
      patch_shape:
      - 48
      - 80
      - 80
      slack_acceptance: 0.01
      stride_shape:
      - 20
      - 40
      - 40
      threshold: 0.6
    transformer:
      label:
      - name: RandomFlip
      - name: RandomRotate90
      - angle_spectrum: 20
        axes:
        - - 2
          - 1
        mode: reflect
        name: RandomRotate
      - name: ElasticDeformation
        spline_order: 0
      - append_label: true
        blur: true
        name: StandardLabelToBoundary
        sigma: 1.0
      - expand_dims: false
        name: ToTensor
      raw:
      - name: Standardize
      - name: RandomFlip
      - name: RandomRotate90
      - angle_spectrum: 20
        axes:
        - - 2
          - 1
        mode: reflect
        name: RandomRotate
      - name: ElasticDeformation
        spline_order: 3
      - expand_dims: true
        name: ToTensor
  val:
    file_paths:
    - "/home/adrian/Datasets/Ovules/Val"

    slice_builder:
      name: FilterSliceBuilder
      patch_shape:
      - 48
      - 80
      - 80
      slack_acceptance: 0.01
      stride_shape:
      - 48
      - 80
      - 80
      threshold: 0.4
    transformer:
      label:
      - append_label: true
        blur: true
        name: StandardLabelToBoundary
        sigma: 1.0
      - expand_dims: false
        name: ToTensor
      raw:
      - name: Standardize
      - expand_dims: true
        name: ToTensor
loss:
  ignore_index: null
  name: BCEWithLogitsLoss
  skip_last_target: true
lr_scheduler:
  factor: 0.2
  mode: min
  name: ReduceLROnPlateau
  patience: 15
manual_seed: 0
model:
  f_maps: 32
  final_sigmoid: true
  in_channels: 1
  layer_order: bcr
  name: UNet3D
  num_groups: null
  out_channels: 1
optimizer:
  learning_rate: 0.0002
  weight_decay: 1.0e-05
trainer:
  checkpoint_dir: "/home/adrian/Datasets/Ovules"
  max_num_epochs: 1000
  max_num_iterations: 150000
  eval_score_higher_is_better: false
  log_after_iters: 250
  resume: null
  validate_after_iters: 1000