class_docstr: Implementation of `TridentNet <https://arxiv.org/abs/1901.01892>`_
class_docstr_tok: ["Implementation","of","`","TridentNet","<","https",":","\/\/arxiv.org\/abs\/1901.01892",">","`","_"]
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)
      num_branch = self.num_branch if self.test_branch_idx == -1 else 1
      trident_img_metas = [
          img_metas * num_branch for img_metas in img_metas
      ]
      proposal_list = self.rpn_head.aug_test_rpn(x, trident_img_metas)
      return self.roi_head.aug_test(
          x, proposal_list, img_metas, rescale=rescale
      )
  
file_path: mmdetection/mmdet/models/detectors/trident_faster_rcnn.py
imports: from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.structures import SampleList
  from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig
  from .faster_rcnn import FasterRCNN
label_desc: Use image node_id 5 for calling the TridentFasterRCNN obj's underlying member method code with example usage: obj.aug_test(imgs, img_metas, rescale) and returns: self