class_docstr: Base class for two-stage detectors.
  
  Two-stage detectors typically consisting of a region proposal network and a
  task-specific regression head.
class_docstr_tok: ["Base","class","for","two-stage","detectors",".","Two-stage","detectors","typically","consisting","of","a","region","proposal","network","and","a","task-specific","regression","head","."]
docstr: Test with augmentations.
  
  If rescale is False, then returned bboxes and masks will fit the scale
  of imgs[0].
docstr_tok: ["Test","with","augmentations",".","If","rescale","is","False",",","then","returned","bboxes","and","masks","will","fit","the","scale","of","imgs","[","0","]","."]
code: def aug_test(self, imgs, img_metas, rescale=False):
      """Test with augmentations.
  
      If rescale is False, then returned bboxes and masks will fit the scale
      of imgs[0].
      """
      x = self.extract_feats(imgs)
      proposal_list = self.rpn_head.aug_test_rpn(x, img_metas)
      return self.roi_head.aug_test(
          x, proposal_list, img_metas, rescale=rescale
      )
  
file_path: insightface/detection/scrfd/mmdet/models/detectors/two_stage.py
imports: import torch
  import torch.nn
  from ..builder import DETECTORS, build_backbone, build_head, build_neck
  from .base import BaseDetector
label_desc: Use image node_id 9 for calling the TwoStageDetector obj's underlying member method code with example usage: obj.aug_test(imgs, img_metas, rescale) and returns: self