dnn_NMSBoxesBatched

Deep neural networksfunctionOpenCV 5.0.0

import { dnn_NMSBoxesBatched } from '@banou/opencv-wasm'

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

Explore visually: Non-maximum suppression →

Reduce overlapping detector proposals by retaining the most useful scored boxes.

VISUAL WALKTHROUGHDetection

REFERENCE INPUTOverlapping detections

Three boxes cover one object; another box covers a separate object.

→

RESULTTwo detections remain

Greedy hard NMS keeps the strongest overlapping box and the separate object. Soft-NMS instead adjusts competing scores.

Illustrative example. The stages explain the method; they are not a live OpenCV execution.

Performs batched non maximum suppression on given boxes and corresponding scores across different classes.

dnn_NMSBoxesBatched(bboxes: Rect2dVector, scores: FloatVector, class_ids: IntVector, score_threshold: number, nms_threshold: number, indices: IntVector, eta: number, top_k: number): void;

3 available overloads

dnn_NMSBoxesBatched(bboxes: Rect2dVector, scores: FloatVector, class_ids: IntVector, score_threshold: number, nms_threshold: number, indices: IntVector): void;

dnn_NMSBoxesBatched(bboxes: Rect2dVector, scores: FloatVector, class_ids: IntVector, score_threshold: number, nms_threshold: number, indices: IntVector, eta: number): void;

dnn_NMSBoxesBatched(bboxes: Rect2dVector, scores: FloatVector, class_ids: IntVector, 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.

class_ids

a set of corresponding class ids. Ids are integer and usually start from 0.

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.

Upstream declaration ↗

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.