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saliency_ObjectnessBING

saliencyclassOpenCV 5.0.0
import { saliency_ObjectnessBING } from '@banou/opencv-wasm'

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

Native object: release it with using or delete(). Factories can return null; check before calling methods. Inherits saliency_Objectness.

Specific Objectness Specialized Classes *********************************** Objectness algorithms based on [3] [3] Cheng, Ming-Ming, et al. "BING: Binarized normed gradients for objectness estimation at 300fps." IEEE CVPR. 2014. the Binarized normed gradients algorithm from [BING]

Constructors and members

static create

Create an owned saliency_ObjectnessBING instance with the supplied configuration.

Specific Objectness Specialized Classes *********************************** Objectness algorithms based on [3] [3] Cheng, Ming-Ming, et al. "BING: Binarized normed gradients for objectness estimation at 300fps." IEEE CVPR. 2014. the Binarized normed gradients algorithm from [BING]

create(): saliency_ObjectnessBING | null;
Returns

The saliency_ObjectnessBING | null result.

clone

Create another handle to the same native object. This retains the object without copying its pixels or algorithm state; dispose both handles separately.

clone(): this;
Returns

The this result.

computeSaliency

Compute the saliency

computeSaliency(image: Mat, saliencyMap: Mat): boolean;
image

The image.

saliencyMap

Output destination, filled by the native operation. The computed saliency map.

Returns

true if the saliency map is computed, false otherwise

getobjectnessValues

Return the list of the rectangles' objectness value,

in the same order as the *vector\<Vec4i\> objectnessBoundingBox* returned by the algorithm (in
computeSaliencyImpl function). The bigger value these scores are, it is more likely to be an
object window.
getobjectnessValues(): FloatVector;
Returns

The FloatVector result. Release returned native handles with using or delete(), including handles nested in results.

setTrainingPath

This is a utility function that allows to set the correct path from which the algorithm will load the trained model.

setTrainingPath(trainingPath: EmbindString): void;
trainingPath

trained model path

setBBResDir

This is a utility function that allows to set an arbitrary path in which the algorithm will save the optional results

(ie writing on file the total number and the list of rectangles returned by objectess, one for
each row).
setBBResDir(resultsDir: EmbindString): void;
resultsDir

results' folder path

getBase

Return the base configured on this saliency_ObjectnessBING object.

getBase(): number;
Returns

The number result.

setBase

Set the base used by this saliency_ObjectnessBING object.

setBase(val: number): void;
val

val argument (number).

getNSS

Return the nss configured on this saliency_ObjectnessBING object.

getNSS(): number;
Returns

The number result.

setNSS

Set the nss used by this saliency_ObjectnessBING object.

setNSS(val: number): void;
val

val argument (number).

getW

Return the w configured on this saliency_ObjectnessBING object.

getW(): number;
Returns

The number result.

setW

Set the w used by this saliency_ObjectnessBING object.

setW(val: number): void;
val

val argument (number).

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.