loading

loading#

Source code: armscan_env/volumes/loading.py

class RegisteredLabelmap(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
get_file_path() → str[source]#
get_labelmap_id() → int[source]#
get_optimal_action() → ManipulatorAction[source]#
classmethod load_all_cropped_labelmaps(normalize_spacing: bool = True) → list[ImageVolume][source]#
classmethod load_all_labelmaps(normalize_spacing: bool = True) → list[ImageVolume][source]#
load_cropped_labelmap() → ImageVolume[source]#
load_labelmap() → ImageVolume[source]#
v1 = 1#
v11 = 11#
v13 = 13#
v17 = 17#
v18 = 18#
v2 = 2#
v35 = 35#
v42 = 42#
load_sitk_volumes(normalize: bool = True, cropped: bool = False) → list[ImageVolume][source]#

Load a SimpleITK volume from a file.

Parameters:

  • normalize -- whether to normalize the volumes to a single spacing

  • cropped -- whether to load the cropped volumes for simplified experiment

Returns:

the loaded volume

normalize_sitk_volumes_to_highest_spacing(volumes: list[ImageVolume]) → list[ImageVolume][source]#

Resize a SimpleITK volume to a normalized spacing, and interpolate to get right amount of voxels. Have a look at [this](https://stackoverflow.com/questions/48065117/simpleitk-resize-images) link to see potential problems.

Parameters:

  • volumes -- the volumes to resize

  • n_spacing -- the normalized spacing to set

Returns:

the resized volume

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