Fixed errors once again
@@ -229,8 +229,9 @@ class DenseVNet(BaseNet):
n_spatial_dims = input_tensor.shape.ndims - 2
# Refine segmentation with prior
- if self.hyperparams['use_prior']:
- spatial_prior = SpatialPriorBlock([12] * n_spatial_dims, \
+ if hyperparams['use_prior']:
+ spatial_prior = SpatialPriorBlock(
+ [hyperparams.prior_size] * n_spatial_dims,
feature_map_shape)
output += spatial_prior()
