Facemark

Objective-C

@interface Facemark : Algorithm

Swift

class Facemark : 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 = 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.

Member of Face

Methods


                    
                    
                    -fit:faces:landmarks:

Detect facial landmarks from an image.

Declaration

Objective-C

- (BOOL)fit:(nonnull Mat *)image
        faces:(nonnull Mat *)faces
    landmarks:(nonnull NSMutableArray<Mat *> *)landmarks;

Swift

func fit(image: Mat, faces: Mat, landmarks: NSMutableArray) -> Bool

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. Example of usage Mat image = imread(“image.jpg”); std::vector faces; std::vectorstd::vector<Point2f > landmarks; facemark->fit(image, faces, landmarks);


                    
                    
                    -loadModel:

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

Declaration

Objective-C

- (void)loadModel:(nonnull NSString *)model;

Swift

func loadModel(model: String)

Parameters


                                model

A string represent the filename of a trained model.

Example of usage

facemark->loadModel(“../data/lbf.model”);