[Fix]: convert scale_factors from list to array to prevent torch tensor UserWarning (#7937)

Author: austinmw

mmdet/models/dense_heads/yolo_head.py

@@ -3,6 +3,7 @@
 
 import warnings
 
+import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -235,7 +236,8 @@ def get_bboxes(self,
         """
         assert len(pred_maps) == self.num_levels
         cfg = self.test_cfg if cfg is None else cfg
-        scale_factors = [img_meta['scale_factor'] for img_meta in img_metas]
+        scale_factors = np.array(
+            [img_meta['scale_factor'] for img_meta in img_metas])
 
         num_imgs = len(img_metas)
         featmap_sizes = [pred_map.shape[-2:] for pred_map in pred_maps]

mmdet/models/dense_heads/yolox_head.py

@@ -1,6 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import math
 
+import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -249,7 +250,8 @@ def get_bboxes(self,
         """
         assert len(cls_scores) == len(bbox_preds) == len(objectnesses)
         cfg = self.test_cfg if cfg is None else cfg
-        scale_factors = [img_meta['scale_factor'] for img_meta in img_metas]
+        scale_factors = np.array(
+            [img_meta['scale_factor'] for img_meta in img_metas])
 
         num_imgs = len(img_metas)
         featmap_sizes = [cls_score.shape[2:] for cls_score in cls_scores]