openvino.runtime.opset10.matrix_nms(boxes: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], scores: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], sort_result_type: str = 'none', sort_result_across_batch: bool = False, output_type: str = 'i64', score_threshold: float = 0.0, nms_top_k: int = - 1, keep_top_k: int = - 1, background_class: int = - 1, decay_function: str = 'linear', gaussian_sigma: float = 2.0, post_threshold: float = 0.0, normalized: bool = True) openvino._pyopenvino.Node

Return a node which performs MatrixNms.

  • boxes – Tensor with box coordinates.

  • scores – Tensor with box scores.

  • sort_result_type – Specifies order of output elements, possible values: ‘class’: sort selected boxes by class id (ascending) ‘score’: sort selected boxes by score (descending) ‘none’: do not guarantee the order.

  • sort_result_across_batch – Specifies whenever it is necessary to sort selected boxes across batches or not

  • output_type – Specifies the output tensor type, possible values: ‘i64’, ‘i32’

  • score_threshold – Specifies minimum score to consider box for the processing

  • nms_top_k – Specifies maximum number of boxes to be selected per class, -1 meaning to keep all boxes

  • keep_top_k – Specifies maximum number of boxes to be selected per batch element, -1 meaning to keep all boxes

  • background_class – Specifies the background class id, -1 meaning to keep all classes

  • decay_function – Specifies decay function used to decay scores, possible values: ‘gaussian’, ‘linear’

  • gaussian_sigma – Specifies gaussian_sigma parameter for gaussian decay_function

  • post_threshold – Specifies threshold to filter out boxes with low confidence score after decaying

  • normalized – Specifies whether boxes are normalized or not


The new node which performs MatrixNms