Package org.opencv.face
Class Facemark
- java.lang.Object
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- org.opencv.core.Algorithm
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- org.opencv.face.Facemark
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- 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.
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Constructor Summary
Constructors Modifier Constructor Description protected
Facemark(long addr)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static Facemark
__fromPtr__(long addr)
protected void
finalize()
boolean
fit(Mat image, MatOfRect faces, java.util.List<MatOfPoint2f> landmarks)
Detect facial landmarks from an image.void
loadModel(java.lang.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
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Method Detail
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__fromPtr__
public static Facemark __fromPtr__(long addr)
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loadModel
public void loadModel(java.lang.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");
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fit
public boolean fit(Mat image, MatOfRect faces, java.util.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
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