Table Of Contents
Table Of Contents

Proposal

mxnet.ndarray.contrib.Proposal(cls_prob=None, bbox_pred=None, im_info=None, rpn_pre_nms_top_n=_Null, rpn_post_nms_top_n=_Null, threshold=_Null, rpn_min_size=_Null, scales=_Null, ratios=_Null, feature_stride=_Null, output_score=_Null, iou_loss=_Null, out=None, name=None, **kwargs)

Generate region proposals via RPN

Parameters:
  • cls_prob (NDArray) – Score of how likely proposal is object.
  • bbox_pred (NDArray) – BBox Predicted deltas from anchors for proposals
  • im_info (NDArray) – Image size and scale.
  • rpn_pre_nms_top_n (int, optional, default='6000') – Number of top scoring boxes to keep after applying NMS to RPN proposals
  • rpn_post_nms_top_n (int, optional, default='300') – Overlap threshold used for non-maximumsuppresion(suppress boxes with IoU >= this threshold
  • threshold (float, optional, default=0.7) – NMS value, below which to suppress.
  • rpn_min_size (int, optional, default='16') – Minimum height or width in proposal
  • scales (tuple of <float>, optional, default=[4,8,16,32]) – Used to generate anchor windows by enumerating scales
  • ratios (tuple of <float>, optional, default=[0.5,1,2]) – Used to generate anchor windows by enumerating ratios
  • feature_stride (int, optional, default='16') – The size of the receptive field each unit in the convolution layer of the rpn,for example the product of all stride’s prior to this layer.
  • output_score (boolean, optional, default=0) – Add score to outputs
  • iou_loss (boolean, optional, default=0) – Usage of IoU Loss
  • out (NDArray, optional) – The output NDArray to hold the result.
Returns:

out – The output of this function.

Return type:

NDArray or list of NDArrays