monai_dynUnet_inference_config.yml

# Copyright 2020 Marta Bianca Maria Ranzini and contributors
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#     http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

device:
  num_workers: 1              # number of workers to use in pytorch for multi-processing

inference:
  nr_out_channels: 2          # number of channels in the network output
  inplane_size: [448, 512]    # 2D patch size, slices are either randomly cropped or padded to this dimension based on their size
  spacing: [0.8, 0.8, -1.0]   # images are resampled to this spacing in mm (use -1.0 to preserve the original spacing in given direction)
  batch_size_inference: 1     # batch size at inferece, 1 is recommended
  probability_threshold: 0.5  # probability threshold to convert network output predictions to hard label
  model_to_load: "default"    # path to pretrained network to be used for inference. If default, model in monaifbs/models/checkpoint_dynUnet_DiceXent.pt is used