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dnn_NMSBoxes

Deep neural networksfunctionOpenCV 5.0.0
import { dnn_NMSBoxes } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

Performs non maximum suppression given boxes and corresponding scores.

dnn_NMSBoxes(bboxes: Rect2dVector, scores: FloatVector, score_threshold: number, nms_threshold: number, indices: IntVector, eta: number, top_k: number): void;
3 available overloads
dnn_NMSBoxes(bboxes: Rect2dVector, scores: FloatVector, score_threshold: number, nms_threshold: number, indices: IntVector): void;
dnn_NMSBoxes(bboxes: Rect2dVector, scores: FloatVector, score_threshold: number, nms_threshold: number, indices: IntVector, eta: number): void;
dnn_NMSBoxes(bboxes: Rect2dVector, scores: FloatVector, score_threshold: number, nms_threshold: number, indices: IntVector, eta: number, top_k: number): void;
bboxes

a set of bounding boxes to apply NMS.

scores

a set of corresponding confidences.

score_threshold

a threshold used to filter boxes by score.

nms_threshold

a threshold used in non maximum suppression.

indices

Output destination, filled by the native operation. the kept indices of bboxes after NMS.

eta

a coefficient in adaptive threshold formula: nms\_threshold_{i+1}=eta\cdot nms\_threshold_i.

top_k

if >0, keep at most top_k picked indices.

These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.