Common functions and classes

Classes
class	cv::GraphicalCodeDetector
class	cv::SimilarRects
	This class is used for grouping object candidates detected by Cascade Classifier, HOG etc. More...

Functions
void	cv::groupRectangles (std::vector< Rect > &rectList, int groupThreshold, double eps=0.2)
	Groups the object candidate rectangles. More...
void	cv::groupRectangles (std::vector< Rect > &rectList, std::vector< int > &weights, int groupThreshold, double eps=0.2)
void	cv::groupRectangles (std::vector< Rect > &rectList, int groupThreshold, double eps, std::vector< int > *weights, std::vector< double > *levelWeights)
void	cv::groupRectangles (std::vector< Rect > &rectList, std::vector< int > &rejectLevels, std::vector< double > &levelWeights, int groupThreshold, double eps=0.2)
void	cv::groupRectangles_meanshift (std::vector< Rect > &rectList, std::vector< double > &foundWeights, std::vector< double > &foundScales, double detectThreshold=0.0, Size winDetSize=Size(64, 128))

Detailed Description

Function Documentation

groupRectangles() [1/4]

void cv::groupRectangles	(	std::vector< Rect > &	rectList,
		int	groupThreshold,
		double	eps = 0.2
	)

Python:
	cv.groupRectangles(	rectList, groupThreshold[, eps]	) ->	rectList, weights

#include <opencv2/objdetect.hpp>

Groups the object candidate rectangles.

Parameters

rectList	Input/output vector of rectangles. Output vector includes retained and grouped rectangles. (The Python list is not modified in place.)
groupThreshold	Minimum possible number of rectangles minus 1. The threshold is used in a group of rectangles to retain it.
eps	Relative difference between sides of the rectangles to merge them into a group.

The function is a wrapper for the generic function partition . It clusters all the input rectangles using the rectangle equivalence criteria that combines rectangles with similar sizes and similar locations. The similarity is defined by eps. When eps=0 , no clustering is done at all. If \(\texttt{eps}\rightarrow +\inf\) , all the rectangles are put in one cluster. Then, the small clusters containing less than or equal to groupThreshold rectangles are rejected. In each other cluster, the average rectangle is computed and put into the output rectangle list.

groupRectangles() [2/4]

void cv::groupRectangles	(	std::vector< Rect > &	rectList,
		std::vector< int > &	weights,
		int	groupThreshold,
		double	eps = 0.2
	)

Python:
	cv.groupRectangles(	rectList, groupThreshold[, eps]	) ->	rectList, weights

#include <opencv2/objdetect.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

groupRectangles() [3/4]

void cv::groupRectangles	(	std::vector< Rect > &	rectList,
		int	groupThreshold,
		double	eps,
		std::vector< int > *	weights,
		std::vector< double > *	levelWeights
	)

Python:
	cv.groupRectangles(	rectList, groupThreshold[, eps]	) ->	rectList, weights

#include <opencv2/objdetect.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

groupRectangles() [4/4]

void cv::groupRectangles	(	std::vector< Rect > &	rectList,
		std::vector< int > &	rejectLevels,
		std::vector< double > &	levelWeights,
		int	groupThreshold,
		double	eps = 0.2
	)

Python:
	cv.groupRectangles(	rectList, groupThreshold[, eps]	) ->	rectList, weights

#include <opencv2/objdetect.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

groupRectangles_meanshift()

void cv::groupRectangles_meanshift	(	std::vector< Rect > &	rectList,
		std::vector< double > &	foundWeights,
		std::vector< double > &	foundScales,
		double	detectThreshold = 0.0,
		Size	winDetSize = Size(64, 128)
	)

#include <opencv2/objdetect.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.