[DLMED] update according to comments

Signed-off-by: Nic Ma <nma@nvidia.com>

monai/data/csv_saver.py

@@ -16,6 +16,7 @@
 
 import numpy as np
 import torch
+from monai.utils import ImageMetaKey as Key
 
 
 class CSVSaver:
@@ -73,7 +74,7 @@ def save(self, data: Union[torch.Tensor, np.ndarray], meta_data: Optional[Dict]
             meta_data: the meta data information corresponding to the data.
 
         """
-        save_key = meta_data["filename_or_obj"] if meta_data else str(self._data_index)
+        save_key = meta_data[Key.FILENAME_OR_OBJ] if meta_data else str(self._data_index)
         self._data_index += 1
         if isinstance(data, torch.Tensor):
             data = data.detach().cpu().numpy()

monai/data/nifti_saver.py

@@ -18,6 +18,7 @@
 from monai.data.nifti_writer import write_nifti
 from monai.data.utils import create_file_basename
 from monai.utils import GridSampleMode, GridSamplePadMode
+from monai.utils import ImageMetaKey as Key
 
 
 class NiftiSaver:
@@ -95,7 +96,7 @@ def save(self, data: Union[torch.Tensor, np.ndarray], meta_data: Optional[Dict]
         See Also
             :py:meth:`monai.data.nifti_writer.write_nifti`
         """
-        filename = meta_data["filename_or_obj"] if meta_data else str(self._data_index)
+        filename = meta_data[Key.FILENAME_OR_OBJ] if meta_data else str(self._data_index)
         self._data_index += 1
         original_affine = meta_data.get("original_affine", None) if meta_data else None
         affine = meta_data.get("affine", None) if meta_data else None

monai/data/png_saver.py

@@ -17,6 +17,7 @@
 from monai.data.png_writer import write_png
 from monai.data.utils import create_file_basename
 from monai.utils import InterpolateMode
+from monai.utils import ImageMetaKey as Key
 
 
 class PNGSaver:
@@ -82,7 +83,7 @@ def save(self, data: Union[torch.Tensor, np.ndarray], meta_data: Optional[Dict]
             :py:meth:`monai.data.png_writer.write_png`
 
         """
-        filename = meta_data["filename_or_obj"] if meta_data else str(self._data_index)
+        filename = meta_data[Key.FILENAME_OR_OBJ] if meta_data else str(self._data_index)
         self._data_index += 1
         spatial_shape = meta_data.get("spatial_shape", None) if meta_data and self.resample else None
 

monai/handlers/classification_saver.py

@@ -15,6 +15,7 @@
 from monai.data import CSVSaver
 from monai.handlers.utils import evenly_divisible_all_gather, string_list_all_gather
 from monai.utils import exact_version, optional_import
+from monai.utils import ImageMetaKey as Key
 
 idist, _ = optional_import("ignite", "0.4.2", exact_version, "distributed")
 Events, _ = optional_import("ignite.engine", "0.4.2", exact_version, "Events")
@@ -86,9 +87,9 @@ def __call__(self, engine: Engine) -> None:
             engine: Ignite Engine, it can be a trainer, validator or evaluator.
         """
         _meta_data = self.batch_transform(engine.state.batch)
-        if "filename_or_obj" in _meta_data:
+        if Key.FILENAME_OR_OBJ in _meta_data:
             # all gather filenames across ranks
-            _meta_data["filename_or_obj"] = string_list_all_gather(_meta_data["filename_or_obj"])
+            _meta_data[Key.FILENAME_OR_OBJ] = string_list_all_gather(_meta_data[Key.FILENAME_OR_OBJ])
         # all gather predictions across ranks
         _engine_output = evenly_divisible_all_gather(self.output_transform(engine.state.output))
 

monai/handlers/metrics_saver.py

@@ -13,6 +13,7 @@
 
 from monai.handlers.utils import string_list_all_gather, write_metrics_reports
 from monai.utils import ensure_tuple, exact_version, optional_import
+from monai.utils import ImageMetaKey as Key
 
 Events, _ = optional_import("ignite.engine", "0.4.2", exact_version, "Events")
 idist, _ = optional_import("ignite", "0.4.2", exact_version, "distributed")
@@ -92,7 +93,7 @@ def _started(self, engine: Engine) -> None:
 
     def _get_filenames(self, engine: Engine) -> None:
         if self.metric_details is not None:
-            _filenames = list(ensure_tuple(self.batch_transform(engine.state.batch)["filename_or_obj"]))
+            _filenames = list(ensure_tuple(self.batch_transform(engine.state.batch)[Key.FILENAME_OR_OBJ]))
             self._filenames += _filenames
 
     def __call__(self, engine: Engine) -> None:

monai/transforms/io/array.py

@@ -21,6 +21,7 @@
 from monai.data.image_reader import ImageReader, ITKReader, NibabelReader, NumpyReader, PILReader
 from monai.transforms.compose import Transform
 from monai.utils import ensure_tuple, optional_import
+from monai.utils import ImageMetaKey as Key
 
 nib, _ = optional_import("nibabel")
 Image, _ = optional_import("PIL.Image")
@@ -126,5 +127,5 @@ def __call__(
 
         if self.image_only:
             return img_array
-        meta_data["filename_or_obj"] = ensure_tuple(filename)[0]
+        meta_data[Key.FILENAME_OR_OBJ] = ensure_tuple(filename)[0]
         return img_array, meta_data

monai/utils/__init__.py

@@ -19,6 +19,7 @@
     ChannelMatching,
     GridSampleMode,
     GridSamplePadMode,
+    ImageMetaKey,
     InterpolateMode,
     LossReduction,
     Method,

monai/utils/enums.py

@@ -28,6 +28,7 @@
     "ChannelMatching",
     "SkipMode",
     "Method",
+    "ImageMetaKey",
 ]
 
 
@@ -214,3 +215,11 @@ class Method(Enum):
 
     SYMMETRIC = "symmetric"
     END = "end"
+
+
+class ImageMetaKey(Enum):
+    """
+    Common key names in the meta data header of images
+    """
+
+    FILENAME_OR_OBJ = "filename_or_obj"