class_docstr: Faster R-CNN network, see https://arxiv.org/abs/1506.01497
  
  Args:
      backbone (object): backbone instance
      rpn_head (object): `RPNHead` instance
      bbox_head (object): `BBoxHead` instance
      bbox_post_process (object): `BBoxPostProcess` instance
      neck (object): 'FPN' instance
class_docstr_tok: ["Faster","R-CNN","network",",","see","https",":","\/\/arxiv.org\/abs\/1506.01497","Args",":","backbone","(","object",")",":","backbone","instance","rpn_head","(","object",")",":","`","RPNHead","`","instance","bbox_head","(","object",")",":","`","BBoxHead","`","instance","bbox_post_process","(","object",")",":","`","BBoxPostProcess","`","instance","neck","(","object",")",":","'FPN","'","instance"]
code: def target_bbox_forward(self, data):
      body_feats = self.backbone(data)
      if self.neck is not None:
          body_feats = self.neck(body_feats)
      rois = [roi for roi in data["gt_bbox"]]
      rois_num = paddle.concat([paddle.shape(roi)[0:1] for roi in rois])
  
      preds, _ = self.bbox_head(
          body_feats, rois, rois_num, None, cot=True
      )
      return preds
  
file_path: PaddleDetection/ppdet/modeling/architectures/faster_rcnn.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
  import numpy
label_desc: Use image node_id 7 for calling the FasterRCNN obj's underlying member method code with example usage: obj.target_bbox_forward(data) and returns: preds