Add Non-Maximum Suppression (NMS) inplace flag (ultralytics#8368)

ultralytics/utils/ops.py

@@ -173,6 +173,7 @@ def non_max_suppression(
     max_time_img=0.05,
     max_nms=30000,
     max_wh=7680,
+    in_place=True,
     rotated=False,
 ):
     """
@@ -197,7 +198,8 @@ def non_max_suppression(
         nc (int, optional): The number of classes output by the model. Any indices after this will be considered masks.
         max_time_img (float): The maximum time (seconds) for processing one image.
         max_nms (int): The maximum number of boxes into torchvision.ops.nms().
-        max_wh (int): The maximum box width and height in pixels
+        max_wh (int): The maximum box width and height in pixels.
+        in_place (bool): If True, the input prediction tensor will be modified in place.
 
     Returns:
         (List[torch.Tensor]): A list of length batch_size, where each element is a tensor of
@@ -224,7 +226,10 @@ def non_max_suppression(
 
     prediction = prediction.transpose(-1, -2)  # shape(1,84,6300) to shape(1,6300,84)
     if not rotated:
-        prediction[..., :4] = xywh2xyxy(prediction[..., :4])  # xywh to xyxy
+        if in_place:
+            prediction[..., :4] = xywh2xyxy(prediction[..., :4])  # xywh to xyxy
+        else:
+            prediction = torch.cat((xywh2xyxy(prediction[..., :4]), prediction[..., 4:]), dim=-1)  # xywh to xyxy
 
     t = time.time()
     output = [torch.zeros((0, 6 + nm), device=prediction.device)] * bs