Changed labels to be a property

mediapipe/tasks/python/test/vision/image_segmenter_test.py

@@ -247,14 +247,16 @@ class ImageSegmenterTest(parameterized.TestCase):
           )
       )
 
-  def test_get_labels_succeeds(self):
+  def test_labels_succeeds(self):
     expected_labels = _EXPECTED_LABELS
     base_options = _BaseOptions(model_asset_path=self.model_path)
     options = _ImageSegmenterOptions(
-        base_options=base_options, output_type=_OutputType.CATEGORY_MASK)
+        base_options=base_options, output_category_mask=True,
+        output_confidence_masks=False
+    )
     with _ImageSegmenter.create_from_options(options) as segmenter:
       # Performs image segmentation on the input.
-      actual_labels = segmenter.get_labels()
+      actual_labels = segmenter.labels
       self.assertListEqual(actual_labels, expected_labels)
 
   def test_missing_result_callback(self):

mediapipe/tasks/python/vision/image_segmenter.py

@@ -151,7 +151,7 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi):
       Exception if there is an error during finding TensorsToSegmentationCalculator.
     :return:
     """
-    self.labels = []
+    self._labels = []
     graph_config = self._runner.get_graph_config()
     found_tensors_to_segmentation = False
 
@@ -170,7 +170,7 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi):
           for i in range(len(options.label_items)):
             if i not in options.label_items:
               raise Exception(f"The labelmap has no expected key: {i}.")
-            self.labels.append(options.label_items[i].name)
+            self._labels.append(options.label_items[i].name)
 
   @classmethod
   def create_from_model_path(cls, model_path: str) -> 'ImageSegmenter':
@@ -271,19 +271,6 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi):
         packets_callback if options.result_callback else None,
     )
 
-  def get_labels(self):
-    """ Get the category label list of the ImageSegmenter can recognize.
-
-    For CATEGORY_MASK type, the index in the category mask corresponds to the
-    category in the label list.
-    For CONFIDENCE_MASK type, the output mask list at index corresponds to the
-    category in the label list.
-
-    If there is no label map provided in the model file, empty label list is
-    returned.
-    """
-    return self.labels
-
   def segment(
       self,
       image: image_module.Image,
@@ -427,3 +414,17 @@ class ImageSegmenter(base_vision_task_api.BaseVisionTaskApi):
             normalized_rect.to_pb2()
         ).at(timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND),
     })
+
+  @property
+  def labels(self) -> List[str]:
+    """ Get the category label list of the ImageSegmenter can recognize.
+
+    For CATEGORY_MASK type, the index in the category mask corresponds to the
+    category in the label list.
+    For CONFIDENCE_MASK type, the output mask list at index corresponds to the
+    category in the label list.
+
+    If there is no label map provided in the model file, empty label list is
+    returned.
+    """
+    return self._labels