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 __init__(
      self,
      arg1,
      arg2,
      batch_size=128,
      fg_fraction=0.25,
      normalize_targets=True,
      normalize_means=[0.0, 0.0, 0.0, 0.0],
      normalize_stds=[0.1, 0.1, 0.2, 0.2],
      fg_thresh=0.5,
      bg_thresh_hi=0.5,
      bg_thresh_lo=0.0,
      param_str=None,
      name="ProposalTargetLayer",
      deterministic=False,
  ):
      super(ProposalTargetLayer, self).__init__([arg1, arg2], name=name)
      self._batch_size = batch_size
      self._fg_fraction = fg_fraction
      self._normalize_targets = normalize_targets
      self._normalize_means = normalize_means
      self._normalize_stds = normalize_stds
      self._fg_thresh = fg_thresh
      self._bg_thresh_hi = bg_thresh_hi
      self._bg_thresh_lo = bg_thresh_lo
      self._param_str = (
          param_str if param_str is not None else "'num_classes': 2"
      )
  
      # parse the layer parameter string, which must be valid YAML
      layer_params = yaml.load(self._param_str)
      self._num_classes = layer_params["num_classes"]
      self._determininistic_mode = deterministic
  
      self._count = 0
      self._fg_num = 0
      self._bg_num = 0
  
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 1 to create a new ProposalTargetLayer object from inherited base classes: UserFunction with example: obj = ProposalTargetLayer(arg1, arg2, batch_size, fg_fraction, normalize_targets, normalize_means, normalize_stds, fg_thresh, bg_thresh_hi, bg_thresh_lo, param_str, name, deterministic)