class_docstr: Base class of Faster R-CNN with FPN.
  
  This is a base class of Faster R-CNN with FPN.
  
  Args:
      extractor (Link): A link that extracts feature maps.
          This link must have :obj:`scales`, :obj:`mean` and
          :meth:`forward`.
      rpn (Link): A link that has the same interface as
          :class:`~chainercv.links.model.fpn.RPN`.
          Please refer to the documentation found there.
      bbox_head (Link): A link that has the same interface as
          :class:`~chainercv.links.model.fpn.BboxHead`.
          Please refer to the documentation found there.
      mask_head (Link): A link that has the same interface as
          :class:`~chainercv.links.model.fpn.MaskHead`.
          Please refer to the documentation found there.
      return_values (list of strings): Determines the values
          returned by :meth:`predict`.
      min_size (int): A preprocessing paramter for :meth:`prepare`. Please
          refer to a docstring found for :meth:`prepare`.
      max_size (int): A preprocessing paramter for :meth:`prepare`. Note
          that the result of :meth:`prepare` can exceed this size due to
          alignment with stride.
  
  Parameters:
      nms_thresh (float): The threshold value
          for :func:`~chainercv.utils.non_maximum_suppression`.
          The default value is :obj:`0.45`.
          This value can be changed directly or by using :meth:`use_preset`.
      score_thresh (float): The threshold value for confidence score.
          If a bounding box whose confidence score is lower than this value,
          the bounding box will be suppressed.
          The default value is :obj:`0.6`.
          This value can be changed directly or by using :meth:`use_preset`.
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code: def forward(self, x):
      assert not chainer.config.train
      hs = self.extractor(x)
      rpn_locs, rpn_confs = self.rpn(hs)
      anchors = self.rpn.anchors(h.shape[2:] for h in hs)
      rois, roi_indices = self.rpn.decode(
          rpn_locs, rpn_confs, anchors, x.shape
      )
      return hs, rois, roi_indices
  
file_path: chainercv/chainercv/links/model/fpn/faster_rcnn.py
imports: from __future__ import division
  import numpy
  import chainer
  from chainer.backends import cuda
  import chainer.functions
  from chainercv.links.model.fpn.misc import scale_img
label_desc: Use image node_id 3 for calling the FasterRCNN obj's underlying member method code with example usage: obj.forward(x) and returns: hs,  rois,  roi_indices