61 lines
3.0 KiB
C++
61 lines
3.0 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#ifndef __OPENCV_FACE_ALIGNMENT_HPP__
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#define __OPENCV_FACE_ALIGNMENT_HPP__
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#include "opencv2/face/facemark_train.hpp"
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namespace cv{
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namespace face{
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class CV_EXPORTS_W FacemarkKazemi : public Facemark
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{
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public:
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struct CV_EXPORTS Params
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{
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/**
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* \brief Constructor
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*/
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Params();
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/// cascade_depth This stores the deapth of cascade used for training.
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unsigned long cascade_depth;
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/// tree_depth This stores the max height of the regression tree built.
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unsigned long tree_depth;
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/// num_trees_per_cascade_level This stores number of trees fit per cascade level.
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unsigned long num_trees_per_cascade_level;
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/// learning_rate stores the learning rate in gradient boosting, also referred as shrinkage.
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float learning_rate;
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/// oversampling_amount stores number of initialisations used to create training samples.
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unsigned long oversampling_amount;
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/// num_test_coordinates stores number of test coordinates.
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unsigned long num_test_coordinates;
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/// lambda stores a value to calculate probability of closeness of two coordinates.
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float lambda;
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/// num_test_splits stores number of random test splits generated.
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unsigned long num_test_splits;
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/// configfile stores the name of the file containing the values of training parameters
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String configfile;
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};
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static Ptr<FacemarkKazemi> create(const FacemarkKazemi::Params ¶meters = FacemarkKazemi::Params());
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virtual ~FacemarkKazemi();
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/** @brief This function is used to train the model using gradient boosting to get a cascade of regressors
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*which can then be used to predict shape.
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*@param images A vector of type cv::Mat which stores the images which are used in training samples.
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*@param landmarks A vector of vectors of type cv::Point2f which stores the landmarks detected in a particular image.
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*@param scale A size of type cv::Size to which all images and landmarks have to be scaled to.
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*@param configfile A variable of type std::string which stores the name of the file storing parameters for training the model.
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*@param modelFilename A variable of type std::string which stores the name of the trained model file that has to be saved.
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*@returns A boolean value. The function returns true if the model is trained properly or false if it is not trained.
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*/
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virtual bool training(std::vector<Mat>& images, std::vector< std::vector<Point2f> >& landmarks,std::string configfile,Size scale,std::string modelFilename = "face_landmarks.dat")=0;
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/// set the custom face detector
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virtual bool setFaceDetector(bool(*f)(InputArray , OutputArray, void*), void* userData)=0;
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/// get faces using the custom detector
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virtual bool getFaces(InputArray image, OutputArray faces)=0;
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};
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}} // namespace
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#endif
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