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: Directly extract features from the backbone+neck.
docstr_tok: ["Directly","extract","features","from","the","backbone+neck","."]
code: def extract_feat(self, img):
      """Directly extract features from the backbone+neck."""
      x = self.backbone(img)
      if self.with_neck:
          x = self.neck(x)
      return x
  
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 5 for calling the TwoStageDetector obj's underlying member method code with example usage: obj.extract_feat(img) and returns: x