Generate an InstanceSegmentationModel from an...

Generate an InstanceSegmentationModel from an IlastikObjectClassifierFromPixelPredictionsModel given binarization parameters

This helps workflows re-use models trained on pixel maps with inputs where the segmentation is already solved. Confirmed visually that all three object maps look the same: test_run_object_classifier_from_pixel_predictions test_make_seg_obj_model_from_pxmap_obj (this change) test_run_object_classifier_from_segmentation

model_server/extensions/ilastik/tests/test_ilastik.py

@@ -136,6 +136,23 @@ class TestIlastikPixelClassification(unittest.TestCase):
         )
         self.assertEqual(objmap.data.max(), 2)
 
+    def test_make_seg_obj_model_from_pxmap_obj(self):
+        self.test_run_pixel_classifier()
+        fp = czifile['path']
+        pxmap_model = ilm.IlastikObjectClassifierFromPixelPredictionsModel(
+            {'project_file': ilastik_classifiers['pxmap_to_obj']}
+        )
+        seg_model = pxmap_model.make_instance_segmentation_model(px_ch=0)
+        objmap = seg_model.label_instance_class(self.mono_image, self.mask)
+
+        self.assertTrue(
+            write_accessor_data_to_file(
+                output_path / f'obmap_seg_from_pxmap_{fp.stem}.tif',
+                objmap,
+            )
+        )
+        self.assertEqual(objmap.data.max(), 2)
+
     def test_run_object_classifier_from_segmentation(self):
         self.test_run_pixel_classifier()
         fp = czifile['path']