Face Recognition

Detailed Description

Adience

Implements loading dataset:

“Adience”: http://www.openu.ac.il/home/hassner/Adience/data.html

Usage:

1. From link above download any dataset file: faces.tar.gz\aligned.tar.gz and files with splits: fold_0_data.txt-fold_4_data.txt, fold_frontal_0_data.txt-fold_frontal_4_data.txt. (For face recognition task another splits should be created)

2. Unpack dataset file to some folder and place split files into the same folder.

3. To load data run:

Labeled Faces in the Wild

Implements loading dataset:

“Labeled Faces in the Wild”: http://vis-www.cs.umass.edu/lfw/

Usage:

1. From link above download any dataset file: lfw.tgz\lfwa.tar.gz\lfw-deepfunneled.tgz\lfw-funneled.tgz and files with pairs: 10 test splits: pairs.txt and developer train split: pairsDevTrain.txt.

2. Unpack dataset file and place pairs.txt and pairsDevTrain.txt in created folder.

3. To load data run:

Classes

Name	Description
class cv::datasets::FR_adience	View details
struct cv::datasets::FR_adienceObj	View details
class cv::datasets::FR_lfw	View details
struct cv::datasets::FR_lfwObj	View details

Enumerations

enum cv::datasets::genderType {
    cv::datasets::male = 0,
    cv::datasets::female,
    cv::datasets::none
}

View details

Enumeration Type Documentation

genderType

enum cv::datasets::genderType

#include <opencv2/datasets/fr_adience.hpp>

Enumerator:

male Python: cv.datasets.male

female Python: cv.datasets.female

none Python: cv.datasets.none