Fix for bottom-up models

sleap/nn/inference.py

@@ -611,6 +611,13 @@ def from_trained_models(cls, model_path: Text) -> "VisualPredictor":
 
         return cls(config=cfg, model=model)
 
+    def _initialize_inference_model(self):
+        """Initialize the inference model from the trained model and configuration."""
+        pass
+
+    def is_grayscale(self) -> bool:
+        return self.model.keras_model.input.shape[-1] == 1
+
     def head_specific_output_keys(self) -> List[Text]:
         keys = []
 

tests/nn/test_inference.py

@@ -2078,5 +2078,7 @@ def test_top_down_model(min_tracks_2node_labels: Labels, min_centroid_model_path
 
 
 def test_visual_predictor(min_bottomup_model_path):
+
+    # Test bottom-up model
     model_path: str = min_bottomup_model_path
     predictor = VisualPredictor.from_trained_models(model_path=model_path)