Merge 66ef232 into 0004df9

deepcell/applications/mesmer.py

@@ -237,8 +237,8 @@ def predict(self,
                 preprocess_kwargs={},
                 compartment='whole-cell',
                 pad_mode='constant',
-                postprocess_kwargs_whole_cell=None,
-                postprocess_kwargs_nuclear=None):
+                postprocess_kwargs_whole_cell={},
+                postprocess_kwargs_nuclear={}):
         """Generates a labeled image of the input running prediction with
         appropriate pre and post processing functions.
 
@@ -268,28 +268,32 @@ def predict(self,
         Returns:
             numpy.array: Instance segmentation mask.
         """
+        default_kwargs_cell = {
+            'maxima_threshold': 0.1,
+            'maxima_smooth': 0,
+            'interior_threshold': 0.3,
+            'interior_smooth': 2,
+            'small_objects_threshold': 15,
+            'fill_holes_threshold': 15,
+            'radius': 2
+        }
+
+        default_kwargs_nuc = {
+            'maxima_threshold': 0.1,
+            'maxima_smooth': 0,
+            'interior_threshold': 0.3,
+            'interior_smooth': 2,
+            'small_objects_threshold': 15,
+            'fill_holes_threshold': 15,
+            'radius': 2
+        }
+
+        # overwrite defaults with any user-provided values
+        postprocess_kwargs_whole_cell = {**default_kwargs_cell,
+                                         **postprocess_kwargs_whole_cell}
 
-        if postprocess_kwargs_whole_cell is None:
-            postprocess_kwargs_whole_cell = {
-                'maxima_threshold': 0.1,
-                'maxima_smooth': 0,
-                'interior_threshold': 0.3,
-                'interior_smooth': 2,
-                'small_objects_threshold': 15,
-                'fill_holes_threshold': 15,
-                'radius': 2
-            }
-
-        if postprocess_kwargs_nuclear is None:
-            postprocess_kwargs_nuclear = {
-                'maxima_threshold': 0.1,
-                'maxima_smooth': 0,
-                'interior_threshold': 0.3,
-                'interior_smooth': 2,
-                'small_objects_threshold': 15,
-                'fill_holes_threshold': 15,
-                'radius': 2
-            }
+        postprocess_kwargs_nuclear = {**default_kwargs_nuc,
+                                      **postprocess_kwargs_nuclear}
 
         # create dict to hold all of the post-processing kwargs
         postprocess_kwargs = {

deepcell/applications/mesmer_test.py

@@ -33,6 +33,8 @@
 
 import numpy as np
 
+from unittest.mock import Mock
+
 from tensorflow.python.platform import test
 
 from deepcell.model_zoo import PanopticNet
@@ -222,6 +224,38 @@ def test_mesmer_app(self):
             self.assertEqual(x.shape[:-1], y.shape[:-1])
             self.assertEqual(y.shape[-1], 2)
 
+            # test that kwargs are passed through successfully
+            app._predict_segmentation = Mock()
+
+            # get defaults
+            _ = app.predict(x, compartment='whole-cell')
+            args = app._predict_segmentation.call_args[1]
+            default_cell_kwargs = args['postprocess_kwargs']['whole_cell_kwargs']
+            default_nuc_kwargs = args['postprocess_kwargs']['nuclear_kwargs']
+
+            # change one of the args for each compartment
+            maxima_threshold_cell = default_cell_kwargs['maxima_threshold'] + 0.1
+            radius_nuc = default_nuc_kwargs['radius'] + 2
+
+            _ = app.predict(x, compartment='whole-cell',
+                            postprocess_kwargs_whole_cell={'maxima_threshold':
+                                                           maxima_threshold_cell},
+                            postprocess_kwargs_nuclear={'radius': radius_nuc})
+
+            args = app._predict_segmentation.call_args[1]
+            cell_kwargs = args['postprocess_kwargs']['whole_cell_kwargs']
+            assert cell_kwargs['maxima_threshold'] == maxima_threshold_cell
+
+            nuc_kwargs = args['postprocess_kwargs']['nuclear_kwargs']
+            assert nuc_kwargs['radius'] == radius_nuc
+
+            # check that rest are unchanged
+            cell_kwargs['maxima_threshold'] = default_cell_kwargs['maxima_threshold']
+            assert cell_kwargs == default_cell_kwargs
+
+            nuc_kwargs['radius'] = default_nuc_kwargs['radius']
+            assert nuc_kwargs == default_nuc_kwargs
+
             # test legacy version
             old_app = MultiplexSegmentation(model)