avoid list[ndarray] -> tensor conversion in Boxes

Summary:
avoid wanings like:
```
detectron2/structures/boxes.py:158: UserWarning: Creating a tensor from a list
of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray
with numpy.array() before converting to a tensor. (Triggered internally at torch/csrc/utils/tensor_new.cpp:201.)
```

Reviewed By: wat3rBro

Differential Revision: D30172338

fbshipit-source-id: fbe044fead72722b3c6eb9916faa2a7dca3e6eae

Author: ppwwyyxx

detectron2/data/detection_utils.py

@@ -376,7 +376,9 @@ def annotations_to_instances(annos, image_size, mask_format="polygon"):
             "gt_masks", "gt_keypoints", if they can be obtained from `annos`.
             This is the format that builtin models expect.
     """
-    boxes = [BoxMode.convert(obj["bbox"], obj["bbox_mode"], BoxMode.XYXY_ABS) for obj in annos]
+    boxes = np.stack(
+        [BoxMode.convert(obj["bbox"], obj["bbox_mode"], BoxMode.XYXY_ABS) for obj in annos]
+    )
     target = Instances(image_size)
     target.gt_boxes = Boxes(boxes)