class_docstr: Mask IoU Head.
  
  This head predicts the IoU of predicted masks and corresponding gt masks.
code: def loss(self, mask_iou_pred, mask_iou_targets):
      pos_inds = mask_iou_targets > 0
      if pos_inds.sum() > 0:
          loss_mask_iou = self.loss_iou(
              mask_iou_pred[pos_inds], mask_iou_targets[pos_inds]
          )
      else:
          loss_mask_iou = mask_iou_pred.sum() * 0
      return dict(loss_mask_iou=loss_mask_iou)
  
file_path: insightface/detection/scrfd/mmdet/models/roi_heads/mask_heads/maskiou_head.py
imports: import numpy
  import torch
  import torch.nn
  from mmcv.cnn import Conv2d, Linear, MaxPool2d, kaiming_init, normal_init
  from mmcv.runner import force_fp32
  from torch.nn.modules.utils import _pair
  from mmdet.models.builder import HEADS, build_loss
label_desc: Use image node_id 4 for calling the MaskIoUHead obj's underlying member method code with example usage: obj.loss(mask_iou_pred, mask_iou_targets) and returns: dict