openvino.runtime.opset12.multiclass_nms#
- openvino.runtime.opset12.multiclass_nms(boxes: Node | int | float | ndarray, scores: Node | int | float | ndarray, roisnum: Node | int | float | ndarray | None = None, sort_result_type: str | None = 'none', sort_result_across_batch: bool | None = False, output_type: str | None = 'i64', iou_threshold: float | None = 0.0, score_threshold: float | None = 0.0, nms_top_k: int | None = -1, keep_top_k: int | None = -1, background_class: int | None = -1, nms_eta: float | None = 1.0, normalized: bool | None = True, name: str | None = None) Node #
Return a node which performs MulticlassNms.
- Parameters:
boxes – Tensor with box coordinates.
scores – Tensor with box scores.
roisnum – Tensor with roisnum. Specifies the number of rois in each image. Required when ‘scores’ is a 2-dimensional tensor.
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’
iou_threshold – Specifies intersection over union threshold
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
nms_eta – Specifies eta parameter for adpative NMS, in close range [0, 1.0]
normalized – Specifies whether boxes are normalized or not
name – The optional name for the output node
- Returns:
The new node which performs MuticlassNms