Rename to batch_box_non_max_merge to box_non_max_merge_batch

supervision/__init__.py

@@ -43,9 +43,9 @@
 from supervision.detection.tools.polygon_zone import PolygonZone, PolygonZoneAnnotator
 from supervision.detection.tools.smoother import DetectionsSmoother
 from supervision.detection.utils import (
-    batch_box_non_max_merge,
     box_iou_batch,
     box_non_max_merge,
+    box_non_max_merge_batch,
     box_non_max_suppression,
     calculate_masks_centroids,
     clip_boxes,

supervision/detection/core.py

@@ -8,9 +8,9 @@
 
 from supervision.config import CLASS_NAME_DATA_FIELD, ORIENTED_BOX_COORDINATES
 from supervision.detection.utils import (
-    batch_box_non_max_merge,
     box_iou_batch,
     box_non_max_merge,
+    box_non_max_merge_batch,
     box_non_max_suppression,
     calculate_masks_centroids,
     extract_ultralytics_masks,
@@ -1226,7 +1226,7 @@ def with_nmm(
                     self.class_id.reshape(-1, 1),
                 )
             )
-            keep_to_merge_list = batch_box_non_max_merge(predictions, threshold)
+            keep_to_merge_list = box_non_max_merge_batch(predictions, threshold)
 
         result = []
         for keep_ind, merge_ind_list in keep_to_merge_list.items():

supervision/detection/utils.py

@@ -300,18 +300,12 @@ def box_non_max_merge(
     y2 = predictions[:, 3]
 
     scores = predictions[:, 4]
-
     areas = (x2 - x1) * (y2 - y1)
 
     order = scores.argsort()
 
-    keep = []
-
     while len(order) > 0:
         idx = order[-1]
-
-        keep.append(idx.tolist())
-
         order = order[:-1]
 
         if len(order) == 0:
@@ -353,7 +347,7 @@ def box_non_max_merge(
     return keep_to_merge_list
 
 
-def batch_box_non_max_merge(
+def box_non_max_merge_batch(
     predictions: np.ndarray, iou_threshold: float = 0.5
 ) -> Dict[int, List[int]]:
     """