/// <summary>
/// Release the unmanaged memory associated with this object.
/// </summary>
protected override void DisposeObject()
{
if (_ptr != IntPtr.Zero)
{
FaceInvoke.cveFacemarkLBFParamsRelease(ref _ptr);
}
}
/// <summary>
/// Release all the unmanaged memory associated with this Facemark
/// </summary>
protected override void DisposeObject()
{
if (_ptr != IntPtr.Zero)
{
FaceInvoke.cveFacemarkAAMRelease(ref _ptr, ref _sharedPtr);
}
}
/// <summary>
/// train it on positive features compute the mace filter: h = D(-1) * X * (X(+) * D(-1) * X)(-1) * C also calculate a minimal threshold for this class, the smallest self-similarity from the train images
/// </summary>
/// <param name="images">A VectorOfMat with the train images</param>
public void Train(IInputArrayOfArrays images)
{
using (InputArray iaImages = images.GetInputArray())
{
FaceInvoke.cveMaceTrain(_ptr, iaImages);
}
}
/// <summary>
/// optionally encrypt images with random convolution
/// </summary>
/// <param name="passphrase">a crc64 random seed will get generated from this</param>
public void Salt(String passphrase)
{
using (CvString csPassphrase = new CvString(passphrase))
{
FaceInvoke.cveMaceSalt(_ptr, csPassphrase);
}
}
/// <summary>
/// correlate query img and threshold to min class value
/// </summary>
/// <param name="query">a Mat with query image</param>
/// <returns>True if the query is the same</returns>
public bool Same(IInputArray query)
{
using (InputArray iaQuery = query.GetInputArray())
{
return(FaceInvoke.cveMaceSame(_ptr, iaQuery));
}
}
/// <summary>
/// Sets string info for the specified model's label.
/// </summary>
/// <param name="label">The label</param>
/// <param name="strInfo">The string info</param>
/// <remarks>The string info is replaced by the provided value if it was set before for the specified label.</remarks>
public void SetLabelInfo(int label, String strInfo)
{
using (CvString csStrInfo = new CvString(strInfo))
{
FaceInvoke.cveFaceRecognizerSetLabelInfo(_faceRecognizerPtr, label, csStrInfo);
}
}
/// <summary>
/// Gets string information by label. If an unknown label id is provided or there is no label information associated with the specified label id the method returns an empty string.
/// </summary>
/// <param name="label">The label</param>
/// <returns>The string associated with this label.</returns>
public String GetLabelInfo(int label)
{
using (CvString csStrInfo = new CvString())
{
FaceInvoke.cveFaceRecognizerGetLabelInfo(_faceRecognizerPtr, label, csStrInfo);
return(csStrInfo.ToString());
}
}
/// <summary>
/// Release the unmanaged memory associated with this FisherFaceRecognizer
/// </summary>
protected override void DisposeObject()
{
if (_sharedPtr == IntPtr.Zero)
{
FaceInvoke.cveLBPHFaceRecognizerRelease(ref _sharedPtr);
}
base.DisposeObject();
}
/// <summary>
/// Release the unmanaged memory associated with this BIF
/// </summary>
protected override void DisposeObject()
{
if (_sharedPtr != IntPtr.Zero)
{
FaceInvoke.cveBIFRelease(ref _sharedPtr);
_ptr = IntPtr.Zero;
}
}
/// <summary>
/// Create a LBPH face recognizer
/// </summary>
/// <param name="radius">Radius</param>
/// <param name="neighbors">Neighbors</param>
/// <param name="gridX">Grid X</param>
/// <param name="gridY">Grid Y</param>
/// <param name="threshold">The distance threshold</param>
public LBPHFaceRecognizer(int radius = 1, int neighbors = 8, int gridX = 8, int gridY = 8,
double threshold = Double.MaxValue)
{
_ptr = FaceInvoke.cveLBPHFaceRecognizerCreate(
radius,
neighbors,
gridX,
gridY,
threshold,
ref _faceRecognizerPtr,
ref _sharedPtr);
}
/// <summary>
/// Predict the label of the image
/// </summary>
/// <param name="image">The image where prediction will be based on</param>
/// <returns>The prediction label</returns>
public PredictionResult Predict(IInputArray image)
{
int label = -1;
double distance = -1;
using (InputArray iaImage = image.GetInputArray())
FaceInvoke.cveFaceRecognizerPredict(_faceRecognizerPtr, iaImage, ref label, ref distance);
return(new PredictionResult()
{
Label = label, Distance = distance
});
}
/// <summary>
/// Updates a FaceRecognizer with given data and associated labels.
/// </summary>
/// <param name="images">The training images, that means the faces you want to learn. The data has to be given as a VectorOfMat.</param>
/// <param name="labels">The labels corresponding to the images</param>
public void Update(IInputArray images, IInputArray labels)
{
using (InputArray iaImages = images.GetInputArray())
using (InputArray iaLabels = labels.GetInputArray())
FaceInvoke.cveFaceRecognizerUpdate(_faceRecognizerPtr, iaImages, iaLabels);
}
/// <summary>
/// Create a FisherFaceRecognizer
/// </summary>
/// <param name="numComponents">The number of components</param>
/// <param name="threshold">The distance threshold</param>
public FisherFaceRecognizer(int numComponents = 0, double threshold = double.MaxValue)
{
_ptr = FaceInvoke.cveFisherFaceRecognizerCreate(numComponents, threshold, ref _faceRecognizerPtr, ref _basicFaceRecognizerPtr, ref _sharedPtr);
}
/// <summary>
/// Computes features by input image.
/// </summary>
/// <param name="image">Input image (CV_32FC1)</param>
/// <param name="features">Feature vector (CV_32FC1)</param>
public void Compute(IInputArray image, IOutputArray features)
{
using (InputArray iaImage = image.GetInputArray())
using (OutputArray oaFeatures = features.GetOutputArray())
FaceInvoke.cveBIFCompute(_ptr, iaImage, oaFeatures);
}
/// <summary>
/// Create an instance of bio-inspired features
/// </summary>
/// <param name="numBands">The number of filter bands used for computing BIF.</param>
/// <param name="numRotations">The number of image rotations.</param>
public BIF(int numBands, int numRotations)
{
_ptr = FaceInvoke.cveBIFCreate(numBands, numRotations, ref _sharedPtr);
}
/// <summary>
/// Release the unmanaged memory associated with this BIF
/// </summary>
protected override void DisposeObject()
{
FaceInvoke.cveBIFRelease(ref _ptr);
}
/// <summary>
/// Load the FaceRecognizer from the file
/// </summary>
/// <param name="fileName">The file where the FaceRecognizer will be loaded from</param>
public void Read(String fileName)
{
using (CvString s = new CvString(fileName))
FaceInvoke.cveFaceRecognizerRead(_ptr, s);
}
/// <summary>
/// Create an instance of FacemarkAAM model
/// </summary>
/// <param name="parameters">The model parameters</param>
public FacemarkAAM(FacemarkAAMParams parameters)
{
_ptr = FaceInvoke.cveFacemarkAAMCreate(parameters, ref _facemarkPtr, ref _algorithmPtr, ref _sharedPtr);
}
/// <summary>
/// Release the unmanaged memory associated with this FaceRecognizer
/// </summary>
protected override void DisposeObject()
{
FaceInvoke.cveFaceRecognizerRelease(ref _ptr, ref _sharedPtr);
}
/// <summary>
/// Create an EigenFaceRecognizer
/// </summary>
/// <param name="numComponents">The number of components</param>
/// <param name="threshold">The distance threshold</param>
public EigenFaceRecognizer(int numComponents = 0, double threshold = double.MaxValue)
{
_ptr = FaceInvoke.cveEigenFaceRecognizerCreate(numComponents, threshold, ref _sharedPtr);
}
/// <summary>
/// Create an instance of the FacemarkLBF model
/// </summary>
/// <param name="parameters">The model parameters</param>
public FacemarkLBF(FacemarkLBFParams parameters)
{
_ptr = FaceInvoke.cveFacemarkLBFCreate(parameters, ref _facemarkPtr, ref _algorithmPtr);
}
/// <summary>
/// Create a new MACE object
/// </summary>
/// <param name="imgSize">images will get resized to this (should be an even number)</param>
public MACE(int imgSize)
{
_ptr = FaceInvoke.cveMaceCreate(imgSize, ref _sharedPtr);
}
/// <summary>
/// Save the FaceRecognizer to a file
/// </summary>
/// <param name="fileName">The file name to be saved to</param>
public void Write(String fileName)
{
using (CvString s = new CvString(fileName))
FaceInvoke.cveFaceRecognizerWrite(_faceRecognizerPtr, s);
}
/// <summary>
/// Create the paramaters with the default values.
/// </summary>
public FacemarkAAMParams()
{
_ptr = FaceInvoke.cveFacemarkAAMParamsCreate();
}
/// <summary>
/// Create an instance of bio-inspired features
/// </summary>
/// <param name="numBands">The number of filter bands used for computing BIF.</param>
/// <param name="numRotations">The number of image rotations.</param>
public BIF(int numBands, int numRotations)
{
_ptr = FaceInvoke.cveBIFCreate(numBands, numRotations);
}
/// <summary>
/// Create a FisherFaceRecognizer
/// </summary>
/// <param name="numComponents">The number of components</param>
/// <param name="threshold">The distance threshold</param>
public FisherFaceRecognizer(int numComponents = 0, double threshold = double.MaxValue)
{
_ptr = FaceInvoke.cveFisherFaceRecognizerCreate(numComponents, threshold);
}
/// <summary>
/// Train the face recognizer with the specific images and labels
/// </summary>
/// <param name="images">The images used in the training. This can be a VectorOfMat</param>
/// <param name="labels">The labels of the images. This can be a VectorOfInt</param>
public void Train(IInputArray images, IInputArray labels)
{
using (InputArray iaImage = images.GetInputArray())
using (InputArray iaLabels = labels.GetInputArray())
FaceInvoke.cveFaceRecognizerTrain(_faceRecognizerPtr, iaImage, iaLabels);
}
