org.opencv.face

Class Facemark

java.lang.Object

org.opencv.core.Algorithm

org.opencv.face.Facemark

Direct Known Subclasses:

FacemarkKazemi, FacemarkTrain

public class Facemark
extends Algorithm

Abstract base class for all facemark models To utilize this API in your program, please take a look at the REF: tutorial_table_of_content_facemark ### Description Facemark is a base class which provides universal access to any specific facemark algorithm. Therefore, the users should declare a desired algorithm before they can use it in their application. Here is an example on how to declare a facemark algorithm: // Using Facemark in your code: Ptr<Facemark> facemark = createFacemarkLBF(); The typical pipeline for facemark detection is as follows:

• Load the trained model using Facemark::loadModel.
• Perform the fitting on an image via Facemark::fit.

Field Summary

Fields inherited from class org.opencv.core.Algorithm

nativeObj

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	Facemark(long addr)

Method Summary

Modifier and Type	Method and Description
static Facemark	__fromPtr__(long addr)
protected void	finalize()
boolean	fit(Mat image, MatOfRect faces, List<MatOfPoint2f> landmarks) Detect facial landmarks from an image.
void	loadModel(String model) A function to load the trained model before the fitting process.

Methods inherited from class org.opencv.core.Algorithm

clear, empty, getDefaultName, getNativeObjAddr, save

Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Facemark

protected Facemark(long addr)

Method Detail

__fromPtr__

public static Facemark __fromPtr__(long addr)

fit

public boolean fit(Mat image,
                   MatOfRect faces,
                   List<MatOfPoint2f> landmarks)

Detect facial landmarks from an image.

Parameters:

image - Input image.

faces - Output of the function which represent region of interest of the detected faces. Each face is stored in cv::Rect container.

landmarks - The detected landmark points for each faces. <B>Example of usage</B> Mat image = imread("image.jpg"); std::vector<Rect> faces; std::vector<std::vector<Point2f> > landmarks; facemark->fit(image, faces, landmarks);

Returns:

automatically generated

loadModel

public void loadModel(String model)

A function to load the trained model before the fitting process.

Parameters:

model - A string represent the filename of a trained model. <B>Example of usage</B> facemark->loadModel("../data/lbf.model");

finalize

protected void finalize()
                 throws Throwable

Overrides:

finalize in class Algorithm

Throws:

Throwable