| OpenCV 4.3.0 Open Source Computer Vision

Modules | Classes | Functions
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>`