multibox_target(anchor=None, label=None, cls_pred=None, overlap_threshold=_Null, ignore_label=_Null, negative_mining_ratio=_Null, negative_mining_thresh=_Null, minimum_negative_samples=_Null, variances=_Null, out=None, name=None, **kwargs)

Compute Multibox training targets

  • anchor (ndarray) – Generated anchor boxes.

  • label (ndarray) – Object detection labels.

  • cls_pred (ndarray) – Class predictions.

  • overlap_threshold (float, optional, default=0.5) – Anchor-GT overlap threshold to be regarded as a positive match.

  • ignore_label (float, optional, default=-1) – Label for ignored anchors.

  • negative_mining_ratio (float, optional, default=-1) – Max negative to positive samples ratio, use -1 to disable mining

  • negative_mining_thresh (float, optional, default=0.5) – Threshold used for negative mining.

  • minimum_negative_samples (int, optional, default='0') – Minimum number of negative samples.

  • variances (tuple of <float>, optional, default=[0.1,0.1,0.2,0.2]) – Variances to be encoded in box regression target.

  • out (ndarray, optional) – The output ndarray to hold the result.


out – The output of this function.

Return type

ndarray or list of ndarrays