class_docstr: PicoHeadV2
  Args:
      conv_feat (object): Instance of 'PicoFeat'
      num_classes (int): Number of classes
      fpn_stride (list): The stride of each FPN Layer
      prior_prob (float): Used to set the bias init for the class prediction layer
      loss_class (object): Instance of VariFocalLoss.
      loss_dfl (object): Instance of DistributionFocalLoss.
      loss_bbox (object): Instance of bbox loss.
      assigner (object): Instance of label assigner.
      reg_max: Max value of integral set :math: `{0, ..., reg_max}`
              n QFL setting. Default: 7.
class_docstr_tok: ["PicoHeadV2","Args",":","conv_feat","(","object",")",":","Instance","of","'PicoFeat'","num_classes","(","int",")",":","Number","of","classes","fpn_stride","(","list",")",":","The","stride","of","each","FPN","Layer","prior_prob","(","float",")",":","Used","to","set","the","bias","init","for","the","class","prediction","layer","loss_class","(","object",")",":","Instance","of","VariFocalLoss",".","loss_dfl","(","object",")",":","Instance","of","DistributionFocalLoss",".","loss_bbox","(","object",")",":","Instance","of","bbox","loss",".","assigner","(","object",")",":","Instance","of","label","assigner",".","reg_max",":","Max","value","of","integral","set",":","math",":","`","{","0",",","...",",","reg_max","}","`","n","QFL","setting",".","Default",":","7","."]
code: def post_process(
      self, head_outs, scale_factor, export_nms=True, nms_cpu=False
  ):
      pred_scores, pred_bboxes = head_outs
      if not export_nms:
          return pred_bboxes, pred_scores
      else:
          # rescale: [h_scale, w_scale] -> [w_scale, h_scale, w_scale, h_scale]
          scale_y, scale_x = paddle.split(scale_factor, 2, axis=-1)
          scale_factor = paddle.concat(
              [scale_x, scale_y, scale_x, scale_y], axis=-1
          ).reshape([-1, 1, 4])
          # scale bbox to origin image size.
          pred_bboxes /= scale_factor
          bbox_pred, bbox_num, _ = self.nms(pred_bboxes, pred_scores)
          return bbox_pred, bbox_num
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.nn.initializer import Normal, Constant
  from ppdet.modeling.ops import get_static_shape
  from ..initializer import normal_
  from ..assigners.utils import generate_anchors_for_grid_cell
  from ..bbox_utils import bbox_center, batch_distance2bbox, bbox2distance
  from ppdet.core.workspace import register
  from ppdet.modeling.layers import ConvNormLayer
  from .simota_head import OTAVFLHead
  from .gfl_head import Integral, GFLHead
  from ppdet.modeling.necks.csp_pan import DPModule
label_desc: Use image node_id 7 for calling the PicoHeadV2 obj's underlying member method code with example usage: obj.post_process(head_outs, scale_factor, export_nms, nms_cpu) and returns: pred_bboxes,  pred_scores, bbox_pred,  bbox_num