wechat_qrcode_WeChatQRCode
import { wechat_qrcode_WeChatQRCode } 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.
WeChat QRCode includes two CNN-based models: A object detection model and a super resolution model. Object detection model is applied to detect QRCode with the bounding box. super resolution model is applied to zoom in QRCode when it is small.
Constructors and members
static new
Initialize the WeChatQRCode. It includes two CNN-based models in ONNX format: a detector model and a super resolution model.
new(detector_model_path: EmbindString, super_resolution_model_path: EmbindString): wechat_qrcode_WeChatQRCode;3 available overloads
new(): wechat_qrcode_WeChatQRCode;new(detector_model_path: EmbindString): wechat_qrcode_WeChatQRCode;new(detector_model_path: EmbindString, super_resolution_model_path: EmbindString): wechat_qrcode_WeChatQRCode;detector_model_pathonnx model file path for the detector
super_resolution_model_pathonnx model file path for the super resolution model
The wechat_qrcode_WeChatQRCode 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;The this result.
detectAndDecode
Both detects and decodes QR code. To simplify the usage, there is a only API: detectAndDecode
detectAndDecode(img: Mat, points: MatVector): StringVector;2 available overloads
detectAndDecode(img: Mat): StringVector;detectAndDecode(img: Mat, points: MatVector): StringVector;imgsupports grayscale or color (BGR) image.
pointsOutput destination, filled by the native operation. optional output array of vertices of the found QR code quadrangle. Will be empty if not found.
list of decoded string. Release returned native handles with using or delete(), including handles nested in results.
setScaleFactor
set scale factor QR code detector use neural network to detect QR. Before running the neural network, the input image is pre-processed by scaling. By default, the input image is scaled to an image with an area of 160000 pixels. The scale factor allows to use custom scale the input image: width = scaleFactorwidth height = scaleFactorwidth
scaleFactor valuse must be > 0 and <= 1, otherwise the scaleFactor value is set to -1 and use default scaled to an image with an area of 160000 pixels.
setScaleFactor(_scalingFactor: number): void;_scalingFactorscaling factor argument (number).
getScaleFactor
Read the scale factor.
set scale factor QR code detector use neural network to detect QR. Before running the neural network, the input image is pre-processed by scaling. By default, the input image is scaled to an image with an area of 160000 pixels. The scale factor allows to use custom scale the input image: width = scaleFactorwidth height = scaleFactorwidth
scaleFactor valuse must be > 0 and <= 1, otherwise the scaleFactor value is set to -1 and use default scaled to an image with an area of 160000 pixels.
getScaleFactor(): number;The number result.
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.