openvino.runtime.opset15.matrix_nms#
- openvino.runtime.opset15.matrix_nms(boxes: Node | int | float | ndarray, scores: Node | int | float | 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, name: str | None = None) Node #
Return a node which performs MatrixNms.
- Parameters:
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
name – Optional output node name.
- Returns:
The new node which performs MatrixNms