pytorch_connectomics/tutorials/mito_lucchi++.yaml at master · PytorchConnectomics/pytorch_connectomics · GitHub

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experiment_name: mito_lucchi++
description: Binary mitochondria segmentation on Lucchi++ EM dataset

_base_:
  - ../connectomics/config/all_profiles.yaml

default:
  pipeline_profile: binary
  system:
    profile: all-gpu-cpu
  model:
    arch:
      profile: monai_unet
    input_size: [112, 112, 112]
    output_size: [112, 112, 112]
    monai:
      dropout: 0.1
  data:
    dataloader:
      profile: cached
      patch_size: [112, 112, 112]
      batch_size: 8
    augmentation:
      profile: aug_standard
  inference:
    sliding_window:
      window_size: [112, 112, 112]
    test_time_augmentation:
      enabled: true
      flip_axes: all
    evaluation:
      enabled: true
      metrics: [jaccard]

train:
  data:
    train:
      image: datasets/lucchi++/train_im.h5
      label: datasets/lucchi++/train_mito.h5
      resolution: [5, 5, 5]
  optimization:
    profile: warmup_cosine_lr
    n_steps_per_epoch: 1000
    max_epochs: 100

  monitor:
    logging:
      scalar:
        loss_every_n_steps: 50
      images:
        log_every_n_epochs: 10
        max_images: 8
        num_slices: 2
    checkpoint:
      save_top_k: 3
      monitor: train_loss_total_epoch

test:
  data:
    test:
      image: datasets/lucchi++/test_im.h5
      label: datasets/lucchi++/test_mito.h5
      resolution: [5, 5, 5]