openvino.runtime.opset10.non_max_suppression

openvino.runtime.opset10.non_max_suppression(boxes: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], scores: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], max_output_boxes_per_class: Optional[Union[openvino._pyopenvino.Node, int, float, numpy.ndarray]] = None, iou_threshold: Optional[Union[openvino._pyopenvino.Node, int, float, numpy.ndarray]] = None, score_threshold: Optional[Union[openvino._pyopenvino.Node, int, float, numpy.ndarray]] = None, soft_nms_sigma: Optional[Union[openvino._pyopenvino.Node, int, float, numpy.ndarray]] = None, box_encoding: str = 'corner', sort_result_descending: bool = True, output_type: str = 'i64', name: Optional[str] = None) → openvino._pyopenvino.Node

Return a node which performs NonMaxSuppression.

Parameters

  • boxes – Tensor with box coordinates.

  • scores – Tensor with box scores.

  • max_output_boxes_per_class – Tensor Specifying maximum number of boxes to be selected per class.

  • iou_threshold – Tensor specifying intersection over union threshold

  • score_threshold – Tensor specifying minimum score to consider box for the processing.

  • soft_nms_sigma – Tensor specifying the sigma parameter for Soft-NMS.

  • box_encoding – Format of boxes data encoding.

  • sort_result_descending – Flag that specifies whenever it is necessary to sort selected boxes across batches or not.

  • output_type – Output element type.

Returns

The new node which performs NonMaxSuppression