class_docstr: Base class for single-stage detectors.
  
  Single-stage detectors directly and densely predict bounding boxes on the
  output features of the backbone+neck.
docstr: Test function with test time augmentation.
  
  Args:
      imgs (list[Tensor]): the outer list indicates test-time
          augmentations and inner Tensor should have a shape NxCxHxW,
          which contains all images in the batch.
      img_metas (list[list[dict]]): the outer list indicates test-time
          augs (multiscale, flip, etc.) and the inner list indicates
          images in a batch. each dict has image information.
      rescale (bool, optional): Whether to rescale the results.
          Defaults to False.
  
  Returns:
      list[list[np.ndarray]]: BBox results of each image and classes.
          The outer list corresponds to each image. The inner list
          corresponds to each class.
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code: def aug_test(self, imgs, img_metas, rescale=False):
      """Test function with test time augmentation.
  
      Args:
          imgs (list[Tensor]): the outer list indicates test-time
              augmentations and inner Tensor should have a shape NxCxHxW,
              which contains all images in the batch.
          img_metas (list[list[dict]]): the outer list indicates test-time
              augs (multiscale, flip, etc.) and the inner list indicates
              images in a batch. each dict has image information.
          rescale (bool, optional): Whether to rescale the results.
              Defaults to False.
  
      Returns:
          list[list[np.ndarray]]: BBox results of each image and classes.
              The outer list corresponds to each image. The inner list
              corresponds to each class.
      """
      assert hasattr(self.bbox_head, "aug_test"), (
          f"{self.bbox_head.__class__.__name__}"
          " does not support test-time augmentation"
      )
      print("aug-test:", len(imgs))
      feats = self.extract_feats(imgs)
      return [
          self.bbox_head.aug_test(feats, img_metas, rescale=rescale)
      ]
  
file_path: insightface/detection/scrfd/mmdet/models/detectors/single_stage.py
imports: import torch
  import torch.nn
  from mmdet.core import bbox2result
  from ..builder import DETECTORS, build_backbone, build_head, build_neck
  from .base import BaseDetector
label_desc: Use image node_id 7 for calling the SingleStageDetector obj's underlying member method code with example usage: obj.aug_test(imgs, img_metas, rescale) and returns: list