Address a removed monai function, fix CUDA 11 runtime lib, and resurrect option to omit or not DICOM SEG empty frame

.github/workflows/pr.yml

@@ -30,8 +30,9 @@ jobs:
           python3 -c 'import sys; print(sys.executable)'
           python3 -c 'import site; print(site.getsitepackages())'
           python3 -m pip freeze
+          export LD_LIBRARY_PATH=`pwd`/.venv/lib/python3.8/site-packages/nvidia/cuda_runtime/lib:$LD_LIBRARY_PATH
           python3 -c 'from holoscan.core import *'
-          ./run check -f          
+          ./run check -f
       - name: Run Unit tests
         run: |
           source .venv/bin/activate

examples/apps/ai_unetr_seg_app/unetr_seg_operator.py

@@ -18,10 +18,10 @@
 from monai.deploy.operators.monai_seg_inference_operator import InMemImageReader, MonaiSegInferenceOperator
 from monai.transforms import (
     Activationsd,
-    AddChanneld,
     AsDiscreted,
     Compose,
     CropForegroundd,
+    EnsureChannelFirstd,
     Invertd,
     LoadImaged,
     Orientationd,
@@ -132,7 +132,7 @@ def pre_process(self, img_reader, out_dir: str = "./input_images") -> Compose:
         return Compose(
             [
                 LoadImaged(keys=my_key, reader=img_reader),
-                AddChanneld(keys=my_key),
+                EnsureChannelFirstd(keys=my_key),
                 # The SaveImaged transform can be commented out to save a couple seconds.
                 # Uncompress NIfTI file, nii, is used favoring speed over size, but can be changed to nii.gz
                 SaveImaged(

examples/apps/mednist_classifier_monaideploy/mednist_classifier_monaideploy.py

@@ -19,7 +19,7 @@
 from monai.deploy.conditions import CountCondition
 from monai.deploy.core import AppContext, Application, ConditionType, Fragment, Image, Operator, OperatorSpec
 from monai.deploy.operators.dicom_text_sr_writer_operator import DICOMTextSRWriterOperator, EquipmentInfo, ModelInfo
-from monai.transforms import AddChannel, Compose, EnsureType, ScaleIntensity
+from monai.transforms import Compose, EnsureChannelFirst, EnsureType, ScaleIntensity
 
 MEDNIST_CLASSES = ["AbdomenCT", "BreastMRI", "CXR", "ChestCT", "Hand", "HeadCT"]
 
@@ -170,7 +170,7 @@ def setup(self, spec: OperatorSpec):
 
     @property
     def transform(self):
-        return Compose([AddChannel(), ScaleIntensity(), EnsureType()])
+        return Compose([EnsureChannelFirst(channel_dim="no_channel"), ScaleIntensity(), EnsureType()])
 
     def compute(self, op_input, op_output, context):
         import json
@@ -218,7 +218,7 @@ def compose(self):
             self, app_context=app_context, output_folder=app_output_path, model_path=model_path, name="classifier_op"
         )
 
-        my_model_info = ModelInfo("MONAI WG Trainer", "MEDNIST Classifier", "0.1", "xyz")
+        my_model_info = ModelInfo("MONAI WG Trainer", "MEDNIST Classifier", "0.1", "1234")
         my_equipment = EquipmentInfo(manufacturer="MOANI Deploy App SDK", manufacturer_model="DICOM SR Writer")
         my_special_tags = {"SeriesDescription": "Not for clinical use. The result is for research use only."}
         dicom_sr_operator = DICOMTextSRWriterOperator(

monai/deploy/operators/dicom_seg_writer_operator.py

@@ -184,6 +184,7 @@
         segment_descriptions: List[SegmentDescription],
         output_folder: Path,
         custom_tags: Optional[Dict[str, str]] = None,
+        omit_empty_frames: bool = True,
         **kwargs,
     ):
         """Instantiates the DICOM Seg Writer instance with optional list of segment label strings.
@@ -205,12 +206,16 @@
                 Object encapsulating the description of each segment present in the segmentation.
             output_folder: Folder for file output, overridden by named input on compute.
                            Defaults to current working dir's child folder, output.
-            custom_tags: OptonalDict[str, str], optional
+            custom_tags: Optonal[Dict[str, str]], optional
                 Dictionary for setting custom DICOM tags using Keywords and str values only
+            omit_empty_frames: bool, optional
+                Whether to omit frames that contain no segmented pixels from the output segmentation.
+                Defaults to True, same as the underlying lib API.
         """
 
         self._seg_descs = [sd.to_segment_description(n) for n, sd in enumerate(segment_descriptions, 1)]
         self._custom_tags = custom_tags
+        self._omit_empty_frames = omit_empty_frames
         self.output_folder = output_folder if output_folder else DICOMSegmentationWriterOperator.DEFAULT_OUTPUT_FOLDER
 
         self.input_name_seg = "seg_image"
@@ -323,6 +328,7 @@
             manufacturer_model_name="MONAI Deploy App SDK",
             software_versions=version_str,
             device_serial_number="0000",
+            omit_empty_frames=self._omit_empty_frames,
         )
 
         # Adding a few tags that are not in the Dataset