#include "face_alignment.hpp"
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virtual | ~FacemarkKazemi () |
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virtual bool | fit (InputArray image, InputArray faces, InputOutputArray landmarks)=0 |
| This functions retrieves a centered and scaled face shape, according to the bounding rectangle. More...
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virtual bool | getFaces (InputArray image, OutputArray faces)=0 |
| get faces using the custom detector More...
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virtual void | loadModel (String filename)=0 |
| This function is used to load the trained model.. More...
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virtual bool | setFaceDetector (bool(*f)(InputArray, OutputArray, void *), void *userData)=0 |
| set the custom face detector More...
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virtual void | training (String imageList, String groundTruth)=0 |
| training the facemark model, input are the file names of image list and landmark annotation More...
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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 |
| This function is used to train the model using gradient boosting to get a cascade of regressors which can then be used to predict shape. More...
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state. More...
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virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
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virtual String | getDefaultName () const |
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virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage. More...
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virtual void | save (const String &filename) const |
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virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage. More...
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void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
| simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...
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§ ~FacemarkKazemi()
virtual cv::face::FacemarkKazemi::~FacemarkKazemi |
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§ create()
§ fit()
This functions retrieves a centered and scaled face shape, according to the bounding rectangle.
- Parameters
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image | A variable of type cv::InputArray which stores the image whose landmarks have to be found |
faces | A variable of type cv::InputArray which stores the bounding boxes of faces found in a given image. |
landmarks | A variable of type cv::InputOutputArray which stores the landmarks of all the faces found in the imagefrom many ROIs |
§ getFaces()
get faces using the custom detector
§ loadModel()
virtual void cv::face::FacemarkKazemi::loadModel |
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String |
filename | ) |
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pure virtual |
This function is used to load the trained model..
- Parameters
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filename | A variable of type cv::String which stores the name of the file in which trained model is stored. |
§ setFaceDetector()
virtual bool cv::face::FacemarkKazemi::setFaceDetector |
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bool(*)(InputArray, OutputArray, void *) |
f, |
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void * |
userData |
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pure virtual |
set the custom face detector
§ training() [1/2]
virtual void cv::face::FacemarkKazemi::training |
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String |
imageList, |
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String |
groundTruth |
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) |
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pure virtual |
training the facemark model, input are the file names of image list and landmark annotation
§ training() [2/2]
virtual bool cv::face::FacemarkKazemi::training |
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std::vector< Mat > & |
images, |
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std::vector< std::vector< Point2f > > & |
landmarks, |
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std::string |
configfile, |
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Size |
scale, |
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std::string |
modelFilename = "face_landmarks.dat" |
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) |
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pure virtual |
This function is used to train the model using gradient boosting to get a cascade of regressors which can then be used to predict shape.
- Parameters
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images | A vector of type cv::Mat which stores the images which are used in training samples. |
landmarks | A vector of vectors of type cv::Point2f which stores the landmarks detected in a particular image. |
scale | A size of type cv::Size to which all images and landmarks have to be scaled to. |
configfile | A variable of type std::string which stores the name of the file storing parameters for training the model. |
modelFilename | A variable of type std::string which stores the name of the trained model file that has to be saved. |
- Returns
- A boolean value. The function returns true if the model is trained properly or false if it is not trained.
The documentation for this class was generated from the following file:
- /build/master-contrib_docs-lin64/opencv_contrib/modules/face/include/opencv2/face/face_alignment.hpp