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test_config.yml
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test_config.yml
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# Download test data from: https://osf.io/8jz7e/
model_path: PATH_TO_BEST_CHECKPOINT
model:
name: UNet3D
# number of input channels to the model
in_channels: 1
# number of output channels
out_channels: 1
# determines the order of operators in a single layer (crg - Conv3d+ReLU+GroupNorm)
layer_order: gcr
# initial number of feature maps
f_maps: 32
# number of groups in the groupnorm
num_groups: 8
# apply element-wise nn.Sigmoid after the final 1x1x1 convolution, otherwise apply nn.Softmax
final_sigmoid: true
predictor:
name: 'StandardPredictor'
loaders:
# save predictions to output_dir
output_dir: PATH_TO_OUTPUT_DIR
# batch dimension; if number of GPUs is N > 1, then a batch_size of N * batch_size will automatically be taken for DataParallel
batch_size: 1
# mirror pad the raw data in each axis for sharper prediction near the boundaries of the volume
mirror_padding: [16, 32, 32]
# how many subprocesses to use for data loading
num_workers: 8
# test loaders configuration
test:
file_paths:
- PATH_TO_TEST_DIR
slice_builder:
name: SliceBuilder
patch_shape: [80, 170, 170]
stride_shape: [40, 90, 90]
transformer:
raw:
- name: Standardize
- name: ToTensor
expand_dims: true