clean up

Author: Matt Sokoloff

labelbox/data/metrics/confusion_matrix/confusion_matrix.py

@@ -40,9 +40,7 @@ def confusion_matrix_metric(ground_truths: List[Union[
     if value is None:
         return []
 
-    metric_name = _get_metric_name(annotation_pairs[key][0],
-                                   annotation_pairs[key][1], iou)
-
+    metric_name = _get_metric_name(ground_truths, predictions, iou)
     return [ConfusionMatrixMetric(metric_name=metric_name, value=value)]
 
 
@@ -90,20 +88,19 @@ def _get_metric_name(ground_truths: List[Union[ObjectAnnotation,
                      predictions: List[Union[ObjectAnnotation,
                                              ClassificationAnnotation]],
                      iou: float):
+
     if _is_classification(ground_truths, predictions):
         return "classification"
-    else:
-        return f"{int(iou*100)}pct_iou"
+
+    return f"{int(iou*100)}pct_iou"
 
 
 def _is_classification(ground_truths: List[Union[ObjectAnnotation,
                                                  ClassificationAnnotation]],
                        predictions: List[Union[ObjectAnnotation,
                                                ClassificationAnnotation]]):
-    if len(predictions) and isinstance(predictions[0],
-                                       ClassificationAnnotation):
-        return True
-    elif len(ground_truths) and isinstance(ground_truths[0],
-                                           ClassificationAnnotation):
-        return True
-    return False
+    # Check if either the prediction or label contains a classification annotation
+    return (len(predictions) and
+            isinstance(predictions[0], ClassificationAnnotation) or
+            len(ground_truths) and
+            isinstance(ground_truths[0], ClassificationAnnotation))