346 lines
13 KiB
Objective-C
346 lines
13 KiB
Objective-C
//
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// This file is auto-generated. Please don't modify it!
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//
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#pragma once
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#ifdef __cplusplus
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//#import "opencv.hpp"
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#import "opencv2/face.hpp"
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#import "opencv2/face/facerec.hpp"
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#else
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#define CV_EXPORTS
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#endif
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#import <Foundation/Foundation.h>
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#import "FaceRecognizer.h"
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@class Mat;
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NS_ASSUME_NONNULL_BEGIN
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// C++: class LBPHFaceRecognizer
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/**
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* The LBPHFaceRecognizer module
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*
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* Member of `Face`
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*/
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CV_EXPORTS @interface LBPHFaceRecognizer : FaceRecognizer
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#ifdef __cplusplus
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@property(readonly)cv::Ptr<cv::face::LBPHFaceRecognizer> nativePtrLBPHFaceRecognizer;
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#endif
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#ifdef __cplusplus
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- (instancetype)initWithNativePtr:(cv::Ptr<cv::face::LBPHFaceRecognizer>)nativePtr;
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+ (instancetype)fromNative:(cv::Ptr<cv::face::LBPHFaceRecognizer>)nativePtr;
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#endif
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#pragma mark - Methods
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//
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// int cv::face::LBPHFaceRecognizer::getGridX()
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//
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/**
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* @see `-setGridX:`
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*/
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- (int)getGridX NS_SWIFT_NAME(getGridX());
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//
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// void cv::face::LBPHFaceRecognizer::setGridX(int val)
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//
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/**
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* getGridX @see `-getGridX:`
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*/
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- (void)setGridX:(int)val NS_SWIFT_NAME(setGridX(val:));
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//
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// int cv::face::LBPHFaceRecognizer::getGridY()
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//
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/**
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* @see `-setGridY:`
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*/
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- (int)getGridY NS_SWIFT_NAME(getGridY());
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//
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// void cv::face::LBPHFaceRecognizer::setGridY(int val)
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//
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/**
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* getGridY @see `-getGridY:`
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*/
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- (void)setGridY:(int)val NS_SWIFT_NAME(setGridY(val:));
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//
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// int cv::face::LBPHFaceRecognizer::getRadius()
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//
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/**
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* @see `-setRadius:`
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*/
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- (int)getRadius NS_SWIFT_NAME(getRadius());
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//
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// void cv::face::LBPHFaceRecognizer::setRadius(int val)
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//
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/**
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* getRadius @see `-getRadius:`
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*/
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- (void)setRadius:(int)val NS_SWIFT_NAME(setRadius(val:));
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//
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// int cv::face::LBPHFaceRecognizer::getNeighbors()
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//
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/**
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* @see `-setNeighbors:`
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*/
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- (int)getNeighbors NS_SWIFT_NAME(getNeighbors());
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//
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// void cv::face::LBPHFaceRecognizer::setNeighbors(int val)
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//
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/**
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* getNeighbors @see `-getNeighbors:`
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*/
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- (void)setNeighbors:(int)val NS_SWIFT_NAME(setNeighbors(val:));
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//
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// double cv::face::LBPHFaceRecognizer::getThreshold()
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//
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/**
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* @see `-setThreshold:`
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*/
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- (double)getThreshold NS_SWIFT_NAME(getThreshold());
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//
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// void cv::face::LBPHFaceRecognizer::setThreshold(double val)
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//
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/**
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* getThreshold @see `-getThreshold:`
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*/
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- (void)setThreshold:(double)val NS_SWIFT_NAME(setThreshold(val:));
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//
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// vector_Mat cv::face::LBPHFaceRecognizer::getHistograms()
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//
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- (NSArray<Mat*>*)getHistograms NS_SWIFT_NAME(getHistograms());
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//
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// Mat cv::face::LBPHFaceRecognizer::getLabels()
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//
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- (Mat*)getLabels NS_SWIFT_NAME(getLabels());
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//
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// static Ptr_LBPHFaceRecognizer cv::face::LBPHFaceRecognizer::create(int radius = 1, int neighbors = 8, int grid_x = 8, int grid_y = 8, double threshold = DBL_MAX)
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//
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/**
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* @param radius The radius used for building the Circular Local Binary Pattern. The greater the
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* radius, the smoother the image but more spatial information you can get.
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* @param neighbors The number of sample points to build a Circular Local Binary Pattern from. An
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* appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
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* the higher the computational cost.
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* @param grid_x The number of cells in the horizontal direction, 8 is a common value used in
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* @param grid_y The number of cells in the vertical direction, 8 is a common value used in
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* @param threshold The threshold applied in the prediction. If the distance to the nearest neighbor
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* is larger than the threshold, this method returns -1.
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*
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* ### Notes:
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*
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* - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
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* grayscale images, use cvtColor to convert between the color spaces.
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* - This model supports updating.
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*
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* ### Model internal data:
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*
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* - radius see LBPHFaceRecognizer::create.
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* - neighbors see LBPHFaceRecognizer::create.
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* - grid_x see LLBPHFaceRecognizer::create.
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* - grid_y see LBPHFaceRecognizer::create.
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* - threshold see LBPHFaceRecognizer::create.
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* - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
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* none was given).
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* - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
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*/
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+ (LBPHFaceRecognizer*)create:(int)radius neighbors:(int)neighbors grid_x:(int)grid_x grid_y:(int)grid_y threshold:(double)threshold NS_SWIFT_NAME(create(radius:neighbors:grid_x:grid_y:threshold:));
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/**
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* @param radius The radius used for building the Circular Local Binary Pattern. The greater the
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* radius, the smoother the image but more spatial information you can get.
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* @param neighbors The number of sample points to build a Circular Local Binary Pattern from. An
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* appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
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* the higher the computational cost.
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* @param grid_x The number of cells in the horizontal direction, 8 is a common value used in
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* @param grid_y The number of cells in the vertical direction, 8 is a common value used in
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* is larger than the threshold, this method returns -1.
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*
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* ### Notes:
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*
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* - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
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* grayscale images, use cvtColor to convert between the color spaces.
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* - This model supports updating.
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*
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* ### Model internal data:
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*
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* - radius see LBPHFaceRecognizer::create.
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* - neighbors see LBPHFaceRecognizer::create.
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* - grid_x see LLBPHFaceRecognizer::create.
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* - grid_y see LBPHFaceRecognizer::create.
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* - threshold see LBPHFaceRecognizer::create.
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* - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
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* none was given).
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* - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
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*/
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+ (LBPHFaceRecognizer*)create:(int)radius neighbors:(int)neighbors grid_x:(int)grid_x grid_y:(int)grid_y NS_SWIFT_NAME(create(radius:neighbors:grid_x:grid_y:));
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/**
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* @param radius The radius used for building the Circular Local Binary Pattern. The greater the
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* radius, the smoother the image but more spatial information you can get.
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* @param neighbors The number of sample points to build a Circular Local Binary Pattern from. An
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* appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
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* the higher the computational cost.
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* @param grid_x The number of cells in the horizontal direction, 8 is a common value used in
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* is larger than the threshold, this method returns -1.
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*
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* ### Notes:
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*
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* - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
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* grayscale images, use cvtColor to convert between the color spaces.
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* - This model supports updating.
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*
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* ### Model internal data:
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*
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* - radius see LBPHFaceRecognizer::create.
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* - neighbors see LBPHFaceRecognizer::create.
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* - grid_x see LLBPHFaceRecognizer::create.
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* - grid_y see LBPHFaceRecognizer::create.
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* - threshold see LBPHFaceRecognizer::create.
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* - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
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* none was given).
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* - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
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*/
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+ (LBPHFaceRecognizer*)create:(int)radius neighbors:(int)neighbors grid_x:(int)grid_x NS_SWIFT_NAME(create(radius:neighbors:grid_x:));
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/**
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* @param radius The radius used for building the Circular Local Binary Pattern. The greater the
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* radius, the smoother the image but more spatial information you can get.
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* @param neighbors The number of sample points to build a Circular Local Binary Pattern from. An
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* appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
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* the higher the computational cost.
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* is larger than the threshold, this method returns -1.
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*
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* ### Notes:
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*
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* - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
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* grayscale images, use cvtColor to convert between the color spaces.
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* - This model supports updating.
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*
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* ### Model internal data:
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*
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* - radius see LBPHFaceRecognizer::create.
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* - neighbors see LBPHFaceRecognizer::create.
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* - grid_x see LLBPHFaceRecognizer::create.
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* - grid_y see LBPHFaceRecognizer::create.
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* - threshold see LBPHFaceRecognizer::create.
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* - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
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* none was given).
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* - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
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*/
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+ (LBPHFaceRecognizer*)create:(int)radius neighbors:(int)neighbors NS_SWIFT_NAME(create(radius:neighbors:));
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/**
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* @param radius The radius used for building the Circular Local Binary Pattern. The greater the
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* radius, the smoother the image but more spatial information you can get.
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* appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
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* the higher the computational cost.
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* is larger than the threshold, this method returns -1.
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*
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* ### Notes:
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*
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* - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
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* grayscale images, use cvtColor to convert between the color spaces.
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* - This model supports updating.
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*
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* ### Model internal data:
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*
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* - radius see LBPHFaceRecognizer::create.
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* - neighbors see LBPHFaceRecognizer::create.
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* - grid_x see LLBPHFaceRecognizer::create.
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* - grid_y see LBPHFaceRecognizer::create.
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* - threshold see LBPHFaceRecognizer::create.
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* - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
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* none was given).
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* - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
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*/
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+ (LBPHFaceRecognizer*)create:(int)radius NS_SWIFT_NAME(create(radius:));
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/**
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* radius, the smoother the image but more spatial information you can get.
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* appropriate value is to use `8` sample points. Keep in mind: the more sample points you include,
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* the higher the computational cost.
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* publications. The more cells, the finer the grid, the higher the dimensionality of the resulting
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* feature vector.
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* is larger than the threshold, this method returns -1.
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*
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* ### Notes:
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*
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* - The Circular Local Binary Patterns (used in training and prediction) expect the data given as
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* grayscale images, use cvtColor to convert between the color spaces.
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* - This model supports updating.
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*
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* ### Model internal data:
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*
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* - radius see LBPHFaceRecognizer::create.
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* - neighbors see LBPHFaceRecognizer::create.
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* - grid_x see LLBPHFaceRecognizer::create.
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* - grid_y see LBPHFaceRecognizer::create.
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* - threshold see LBPHFaceRecognizer::create.
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* - histograms Local Binary Patterns Histograms calculated from the given training data (empty if
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* none was given).
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* - labels Labels corresponding to the calculated Local Binary Patterns Histograms.
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*/
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+ (LBPHFaceRecognizer*)create NS_SWIFT_NAME(create());
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@end
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NS_ASSUME_NONNULL_END
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