fix #1290

Author: FabianIsensee

nnunet/evaluation/evaluator.py

@@ -481,3 +481,11 @@ def nnunet_evaluate_folder():
                                                                        "information.")
     args = parser.parse_args()
     return evaluate_folder(args.ref, args.pred, args.l)
+
+
+if __name__ == '__main__':
+    evaluate_folder(
+        '/media/isensee/raw_data/nnUNet_raw/Dataset004_Hippocampus/labelsTr',
+        '/home/isensee/drives/checkpoints/nnUNet_results_remake/Dataset999_IntegrationTest_Hippocampus/ensembles/ensemble___nnUNetTrainer_5epochs__nnUNetPlans__3d_cascade_fullres___nnUNetTrainer_5epochs__nnUNetPlans__3d_fullres___0_1_2_3_4',
+        (1, 2), advanced=True
+    )

nnunet/experiment_planning/task_specific_planner/amos2022/residual_bfnnunet_planner.py

@@ -128,28 +128,6 @@ def get_properties_for_stage(self, current_spacing, original_spacing, original_s
         }
         return plan
 
-    def run_preprocessing(self, num_threads):
-        pass
-
-
-class ExperimentPlanner3D_residual_v21_bfnnUNet_31(ExperimentPlanner3D_residual_v21_bfnnUNet):
-    def __init__(self, folder_with_cropped_data, preprocessed_output_folder):
-        super().__init__(folder_with_cropped_data, preprocessed_output_folder)
-        self.data_identifier = "nnUNetData_bfnnUNet_31"
-        self.plans_fname = join(self.preprocessed_output_folder,
-                                "nnUNetPlans_bfnnUNet_fabresnet_31_plans_3D.pkl")
-        self.preprocessor_name = 'Preprocessor3DBetterResampling'
-
-    def plan_experiment(self):
-        super().plan_experiment()
-
-        self.plans['segmentation_export_params'] = {
-            'force_separate_z': False,
-            'interpolation_order': 1,
-            'interpolation_order_z': 999999 # not used
-        }
-        self.save_my_plans()
-
     def run_preprocessing(self, num_threads):
         if os.path.isdir(join(self.preprocessed_output_folder, "gt_segmentations")):
             shutil.rmtree(join(self.preprocessed_output_folder, "gt_segmentations"))
@@ -173,6 +151,25 @@ def run_preprocessing(self, num_threads):
                          self.plans['data_identifier'], num_threads, force_separate_z=False)
 
 
+class ExperimentPlanner3D_residual_v21_bfnnUNet_31(ExperimentPlanner3D_residual_v21_bfnnUNet):
+    def __init__(self, folder_with_cropped_data, preprocessed_output_folder):
+        super().__init__(folder_with_cropped_data, preprocessed_output_folder)
+        self.data_identifier = "nnUNetData_bfnnUNet_31"
+        self.plans_fname = join(self.preprocessed_output_folder,
+                                "nnUNetPlans_bfnnUNet_fabresnet_31_plans_3D.pkl")
+        self.preprocessor_name = 'Preprocessor3DBetterResampling'
+
+    def plan_experiment(self):
+        super().plan_experiment()
+
+        self.plans['segmentation_export_params'] = {
+            'force_separate_z': False,
+            'interpolation_order': 1,
+            'interpolation_order_z': 999999 # not used
+        }
+        self.save_my_plans()
+
+
 class ExperimentPlanner3D_residual_v21_bfnnUNet_31_spRegnnU(ExperimentPlanner3D_residual_v21_bfnnUNet_31):
     def __init__(self, folder_with_cropped_data, preprocessed_output_folder):
         super().__init__(folder_with_cropped_data, preprocessed_output_folder)