Framework for working with different datasets

Modules
	Action Recognition
	Face Recognition
	Gesture Recognition
	Human Pose Estimation
	Image Registration
	Image Segmentation
	Multiview Stereo Matching
	Object Recognition
	Pedestrian Detection
	SLAM
	Super Resolution
	Text Recognition
	Tracking

Classes
class	cv::datasets::Dataset
struct	cv::datasets::Object

Functions
void	cv::datasets::createDirectory (const std::string &path)
void	cv::datasets::getDirList (const std::string &dirName, std::vector< std::string > &fileNames)
void	cv::datasets::split (const std::string &s, std::vector< std::string > &elems, char delim)

Detailed Description

The datasets module includes classes for working with different datasets: load data, evaluate different algorithms on them, contains benchmarks, etc.

It is planned to have:

• basic: loading code for all datasets to help start work with them.
• next stage: quick benchmarks for all datasets to show how to solve them using OpenCV and implement evaluation code.
• finally: implement on OpenCV state-of-the-art algorithms, which solve these tasks.

Function Documentation

createDirectory()

void cv::datasets::createDirectory

(

const std::string &

path

)

#include <opencv2/datasets/util.hpp>

getDirList()

void cv::datasets::getDirList	(	const std::string &	dirName,
		std::vector< std::string > &	fileNames
	)

#include <opencv2/datasets/util.hpp>

split()

void cv::datasets::split	(	const std::string &	s,
		std::vector< std::string > &	elems,
		char	delim
	)

#include <opencv2/datasets/util.hpp>