Class TextDetectionModel

Namespace

OpenCvSharp.Dnn

Assembly

OpenCvSharp.dll

Base class for text detection networks. This is an abstract base; use TextDetectionModelEAST or TextDetectionModelDB.

public abstract class TextDetectionModel : Model, IDisposable

Inheritance

object

CvObject

Model

TextDetectionModel

Implements

IDisposable

Derived

TextDetectionModelDB

TextDetectionModelEAST

Inherited Members

Model.SetHandle(nint, Func<nint, ExceptionStatus>)

Model.SetInputSize(Size)

Model.SetInputSize(int, int)

Model.SetInputMean(Scalar)

Model.SetInputScale(Scalar)

Model.SetInputCrop(bool)

Model.SetInputSwapRB(bool)

Model.SetOutputNames(IEnumerable<string>)

Model.SetInputParams(double, Size?, Scalar?, bool, bool)

Model.Predict(InputArray)

Model.SetPreferableBackend(Backend)

Model.SetPreferableTarget(Target)

Model.EnableWinograd(bool)

CvObject.IsDisposed

CvObject.ptr

CvObject.SetSafeHandle(OpenCvSafeHandle)

CvObject.Dispose()

CvObject.Dispose(bool)

CvObject.DisposeManaged()

CvObject.DisposeUnmanaged()

CvObject.ThrowIfDisposed()

CvObject.CvPtr

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

TextDetectionModel()

For derived classes that construct the native object themselves.

protected TextDetectionModel()

Methods

Detect(InputArray, out Point[][], out float[])

Performs detection. Given the input @p frame, prepare network input, run network inference, post-process network output and return result detections. Each result is quadrangle's 4 points in this order: bottom-left, top-left, top-right, bottom-right.

public void Detect(InputArray frame, out Point[][] detections, out float[] confidences)

Parameters

frame InputArray

The input image.

detections Point[][]

array with detections' quadrangles (4 points per result).

confidences float[]

array with detection confidences.

DetectTextRectangles(InputArray, out RotatedRect[], out float[])

Performs detection. Given the input @p frame, prepare network input, run network inference, post-process network output and return result detections. Each result is rotated rectangle.

public void DetectTextRectangles(InputArray frame, out RotatedRect[] detections, out float[] confidences)

Parameters

frame InputArray

The input image.

detections RotatedRect[]

array with detections' RotatedRect results.

confidences float[]

array with detection confidences.