Merge branch 'master' of github.com:fepegar/torchio

docs/source/conf.py

@@ -26,7 +26,7 @@
 
 # version is the short X.Y version
 # release is the full version, including alpha/beta/rc tags
-version = release = '0.16.15'
+version = release = '0.16.17'
 
 
 # -- General configuration ---------------------------------------------------

setup.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.16.15
+current_version = 0.16.17
 commit = True
 tag = True
 
@@ -22,3 +22,4 @@ universal = 1
 exclude = docs
 
 [aliases]
+

setup.py

@@ -57,6 +57,6 @@
     test_suite='tests',
     tests_require=[],
     url='https://github.com/fepegar/torchio',
-    version='0.16.15',
+    version='0.16.17',
     zip_safe=False,
 )

torchio/__init__.py

@@ -2,7 +2,7 @@
 
 __author__ = """Fernando Perez-Garcia"""
 __email__ = 'fernando.perezgarcia.17@ucl.ac.uk'
-__version__ = '0.16.15'
+__version__ = '0.16.17'
 
 from . import utils
 from .torchio import *

torchio/data/image.py

@@ -4,6 +4,7 @@
 
 import torch
 import numpy as np
+import nibabel as nib
 import SimpleITK as sitk
 
 from ..utils import nib_to_sitk
@@ -19,6 +20,7 @@
     INTENSITY,
 )
 from .io import read_image
+from .orientation import name_dimensions
 
 
 class Image(dict):
@@ -77,6 +79,10 @@ def shape(self) -> Tuple[int, int, int, int]:
     def spatial_shape(self) -> TypeTripletInt:
         return self.shape[1:]
 
+    @property
+    def orientation(self):
+        return nib.aff2axcodes(self[AFFINE])
+
     @staticmethod
     def _parse_path(path: TypePath) -> Path:
         if path is None:
@@ -134,7 +140,13 @@ def load(self, check_nans: bool = True) -> Tuple[torch.Tensor, np.ndarray]:
         tensor, affine = read_image(self.path)
         # https://github.com/pytorch/pytorch/issues/9410#issuecomment-404968513
         tensor = tensor[(None,) * (3 - tensor.ndim)]  # force to be 3D
+        # Remove next line and uncomment the two following ones once/if this issue
+        # gets fixed:
+        # https://github.com/pytorch/pytorch/issues/29010
+        # See also https://discuss.pytorch.org/t/collating-named-tensors/78650/4
         tensor = tensor.unsqueeze(0)  # add channels dimension
+        # name_dimensions(tensor, affine)
+        # tensor = tensor.align_to('channels', ...)
         if check_nans and torch.isnan(tensor).any():
             warnings.warn(f'NaNs found in file "{self.path}"')
         return tensor, affine

torchio/data/orientation.py

@@ -0,0 +1,24 @@
+import warnings
+import nibabel as nib
+
+
+AXCODES_TO_WORDS = {
+    'L': 'left',
+    'R': 'right',
+    'P': 'posterior',
+    'A': 'anterior',
+    'I': 'inferior',
+    'S': 'superior',
+    # 'C': 'caudal',
+    # 'R': 'rostral',  # conflic with right
+    # 'D': 'dorsal',
+    # 'V': 'ventral',
+}
+
+
+def name_dimensions(tensor, affine):
+    axcodes = nib.aff2axcodes(affine)
+    names = [AXCODES_TO_WORDS[axcode] for axcode in axcodes]
+    with warnings.catch_warnings():
+        warnings.simplefilter('ignore', UserWarning)
+        tensor.rename_(*names)