class_docstr: Mask IoU Head.
  
  This head predicts the IoU of predicted masks and corresponding gt masks.
docstr: Get the mask scores.
  
  mask_score = bbox_score * mask_iou
docstr_tok: ["Get","the","mask","scores",".","mask_score","=","bbox_score","*","mask_iou"]
code: def get_mask_scores(self, mask_iou_pred, det_bboxes, det_labels):
      """Get the mask scores.
  
      mask_score = bbox_score * mask_iou
      """
      inds = range(det_labels.size(0))
      mask_scores = (
          mask_iou_pred[inds, det_labels] * det_bboxes[inds, -1]
      )
      mask_scores = mask_scores.cpu().numpy()
      det_labels = det_labels.cpu().numpy()
      return [
          mask_scores[det_labels == i] for i in range(self.num_classes)
      ]
  
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 7 for calling the MaskIoUHead obj's underlying member method code with example usage: obj.get_mask_scores(mask_iou_pred, det_bboxes, det_labels) and returns: unknown