Update requirements and fix data shape handling in Monai nUNet Bundle Inference Operator

Signed-off-by: Simone Bendazzoli <[email protected]>

Author: SimoneBendazzoli93

examples/apps/ai_spleen_nnunet_seg_app/requirements.txt

@@ -7,12 +7,6 @@ numpy-stl>=2.12.0
 trimesh>=3.8.11
 nibabel>=3.2.1
 torch>=1.12.0
-<<<<<<< HEAD
-nvflare
 git+https://github.com/SimoneBendazzoli93/dynamic-network-architectures.git
 git+https://github.com/SimoneBendazzoli93/MONAI.git@dev
 git+https://github.com/SimoneBendazzoli93/nnUNet.git
-=======
-monai>=1.0.0
-nnunetv2>=2.5.1
->>>>>>> dacfaa9 (Add nnUNet segmentation application and dependencies)

monai/deploy/operators/monai_nnunet_bundle_inference_operator.py

@@ -75,7 +75,6 @@ def _init_config(self, config_names):
 
         super()._init_config(config_names)
         parser = get_bundle_config(str(self._bundle_path), config_names)       
-        parser['bundle_root'] = str(Path(self._bundle_path).parent.parent.parent)
         self._parser = parser
 
         self._nnunet_predictor = parser.get_parsed_content("network_def")
@@ -85,4 +84,6 @@ def predict(self, data: Any, *args, **kwargs) -> Union[Image, Any, Tuple[Any, ..
 
         self._nnunet_predictor.predictor.network = self._model_network
         #os.environ['nnUNet_def_n_proc'] = "1"
-        return self._nnunet_predictor(torch.unsqueeze(data, 0))
+        if len(data.shape) == 4:
+            data = data[None]
+        return self._nnunet_predictor(data)