class_docstr: Assign object detection proposals to ground-truth targets. Produces proposal
  classification labels and bounding-box regression targets.
class_docstr_tok: ["Assign","object","detection","proposals","to","ground-truth","targets",".","Produces","proposal","classification","labels","and","bounding-box","regression","targets","."]
code: def serialize(self):
      internal_state = {}
      internal_state["param_str"] = self._param_str
      internal_state["batch_size"] = self._batch_size
      internal_state["fg_fraction"] = self._fg_fraction
      internal_state["normalize_targets"] = self._normalize_targets
      internal_state["normalize_means"] = self._normalize_means
      internal_state["normalize_stds"] = self._normalize_stds
      internal_state["fg_thresh"] = self._fg_thresh
      internal_state["bg_thresh_hi"] = self._bg_thresh_hi
      internal_state["bg_thresh_lo"] = self._bg_thresh_lo
      return internal_state
  
file_path: CNTK/Examples/Image/Detection/utils/rpn/proposal_target_layer.py
imports: from cntk import output_variable, FreeDimension
  from cntk.ops.functions import UserFunction
  import yaml
  import numpy
  import numpy.random
  from utils.rpn.bbox_transform import bbox_transform
  from utils.cython_modules.cython_bbox import bbox_overlaps
label_desc: Use image node_id 6 for calling the ProposalTargetLayer obj's underlying member method code with example usage: obj.serialize() and returns: internal_state