Class DetectionModel

Namespace

OpenCvSharp.Dnn

Assembly

OpenCvSharp.dll

This class represents high-level API for object detection networks. DetectionModel allows to set params for preprocessing input image. DetectionModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and return result detections.

public class DetectionModel : Model, IDisposable

Inheritance

object

CvObject

Model

DetectionModel

Implements

IDisposable

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.SetPostReleaseAction(Action)

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

DetectionModel(Net)

Create model from deep learning network.

DetectionModel(string, string?)

Create detection model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.

Methods

Detect(InputArray, out int[], out float[], out Rect[], float, float)

Given the @p input frame, create input blob, run net and return result detections.

GetNmsAcrossClasses()

Getter for nmsAcrossClasses. This variable defaults to false, such that when non max suppression is used during the detect() function, it will do so only per-class.

SetNmsAcrossClasses(bool)

nmsAcrossClasses defaults to false, such that when non max suppression is used during the detect() function, it will do so per-class. This function allows you to toggle this behaviour.