Fix multi-channel hdf5 volume loader

inferno/io/volumetric/volume.py

@@ -212,6 +212,7 @@ def __init__(self, path, path_in_h5_dataset=None, data_slice=None, transforms=No
         else:
             raise NotImplementedError
 
+        # get the dataslice
         if data_slice is None or isinstance(data_slice, (str, list)):
             self.data_slice = vu.parse_data_slice(data_slice)
         elif isinstance(data_slice, dict):
@@ -223,17 +224,20 @@ def __init__(self, path, path_in_h5_dataset=None, data_slice=None, transforms=No
 
         slicing_config_for_name = pyu.get_config_for_name(slicing_config, name)
 
+        # adapt data-slice if this is a multi-channel volume (slice is not applied to channel dimension)
+        if self.data_slice is not None and slicing_config_for_name.get('is_multichannel', False):
+            self.data_slice = (slice(None),) + self.data_slice
+
         assert 'window_size' in slicing_config_for_name
         assert 'stride' in slicing_config_for_name
 
         # Read in volume from file (can be hdf5, n5 or zarr)
-        dataslice_ = None if self.data_slice is None else tuple(self.data_slice)
         if self.is_h5(self.path):
             volume = iou.fromh5(self.path, self.path_in_h5_dataset,
-                                dataslice=dataslice_)
+                                dataslice=self.data_slice)
         else:
             volume = iou.fromz5(self.path, self.path_in_h5_dataset,
-                                dataslice=dataslice_)
+                                dataslice=self.data_slice)
         # Initialize superclass with the volume
         super(HDF5VolumeLoader, self).__init__(volume=volume, name=name, transforms=transforms,
                                                **slicing_config_for_name)

inferno/io/volumetric/volumetric_utils.py

@@ -139,7 +139,7 @@ def parse_data_slice(data_slice):
         return data_slice
     elif isinstance(data_slice, (list, tuple)) and \
             all([isinstance(_slice, slice) for _slice in data_slice]):
-        return list(data_slice)
+        return tuple(data_slice)
     else:
         assert isinstance(data_slice, str)
     # Get rid of whitespace
@@ -162,5 +162,4 @@ def parse_data_slice(data_slice):
         step = int(step) if step is not None and step != '' else None
         # Build slices
         slices.append(slice(start, stop, step))
-    # Done.
-    return slices
+    return tuple(slices)