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opencv-wasm

text_TextDetectorCNN

textclassOpenCV 5.0.0
import { text_TextDetectorCNN } 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 text_TextDetector.

TextDetectorCNN class provides the functionallity of text bounding box detection. This class is representing to find bounding boxes of text words given an input image. This class uses OpenCV dnn module to load pre-trained model described in [LiaoSBWL17]. The original repository with the modified SSD Caffe version: https://github.com/MhLiao/TextBoxes. Model can be downloaded from DropBox. Modified .prototxt file with the model description can be found in opencv_contrib/modules/text/samples/textbox.prototxt.

Upstream declaration ↗

Constructors and members

static create

Creates an instance of the TextDetectorCNN class using the provided parameters.

create(modelArchFilename: EmbindString, modelWeightsFilename: EmbindString): text_TextDetectorCNN | null;
modelArchFilename

the relative or absolute path to the prototxt file describing the classifiers architecture.

modelWeightsFilename

the relative or absolute path to the file containing the pretrained weights of the model in caffe-binary form.

Returns

The text_TextDetectorCNN | null result.

Upstream declaration ↗

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.

detect

Method that provides a quick and simple interface to detect text inside an image

detect(inputImage: Mat, Bbox: RectVector, confidence: FloatVector): void;
inputImage

an image expected to be a CV_U8C3 of any size

Bbox

Output destination, filled by the native operation. a vector of Rect that will store the detected word bounding box

confidence

Output destination, filled by the native operation. a vector of float that will be updated with the confidence the classifier has for the selected bounding box

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.