code: def __init__(
      self, num_classes=1, decode=None, nms=None, return_idx=True
  ):
      super(JDEBBoxPostProcess, self).__init__()
      self.num_classes = num_classes
      self.decode = decode
      self.nms = nms
      self.return_idx = return_idx
  
      self.fake_bbox_pred = paddle.to_tensor(
          np.array([[-1, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype="float32")
      )
      self.fake_bbox_num = paddle.to_tensor(
          np.array([1], dtype="int32")
      )
      self.fake_nms_keep_idx = paddle.to_tensor(
          np.array([[0]], dtype="int32")
      )
  
      self.fake_yolo_boxes_out = paddle.to_tensor(
          np.array([[[0.0, 0.0, 0.0, 0.0]]], dtype="float32")
      )
      self.fake_yolo_scores_out = paddle.to_tensor(
          np.array([[[0.0]]], dtype="float32")
      )
      self.fake_boxes_idx = paddle.to_tensor(
          np.array([[0]], dtype="int64")
      )
  
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from ppdet.modeling.bbox_utils import nonempty_bbox
  from .transformers import bbox_cxcywh_to_xyxy
label_desc: Use image node_id 1 to create a new JDEBBoxPostProcess object from inherited base classes: nn with example: obj = JDEBBoxPostProcess(num_classes, decode, nms, return_idx)