An Interface for Face Recognition

Provides an interface to the 'Kairos' Face Recognition API < https://kairos.com/face-recognition-api>. The API detects faces in images and returns estimates for demographics like gender, ethnicity and age.


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An Interface for Face Recognition in R

This package provides an interface to the Kairos Face Recognition API. The API detects faces in images and returns estimates for demographics like gender, ethnicity and age. It is also capable of recognizing and verifying humans across several images.

How to Install

To install the CRAN version of facerec use install.packages('facerec').

You can also download and install the latest development version of the app by running devtools::install_github('methodds/facerec'). For Windows users installing from github requires proper setup of Rtools, for which a tutorial is available here.

How to Use

Authentification

After loading facerec you first need to initiate your authentification credentials. Kairos offers a free plan for API access. After signing up, you will receive an application id and an application key. Both credentials need to be set as environment variables before using the initialization function facerec_init():

Sys.setenv(kairos_id = "Your Kairos API id")
Sys.setenv(kairos_key = "Your Kairos API key")
library(facerec)
facerec_init()

You only need to call facerec_init() once after loading the package. In order to avoid entering your credentials for each session, you can permanently store them in your .Renviron. I recommend usethis::edit_r_environ() to find and edit your environment file.

Face Recognition

Kairos accepts image of file type JPG, PNG, or BMP. Images can be passed to several facerec functions, either as an url string or a local image prepared with prep_image(). In the following example, detect() is used to recognize the face of the Star Wars character Finn:

finn_image <- 'https://upload.wikimedia.org/wikipedia/en/2/2a/Finn-Force_Awakens_%282015%29.png'
finn_face <- detect(image = finn_image)

The function returns a dataframe with annotations for the recognized face in the input image. Variables include positional features of recognized faces, such as x and y coordinates for eyes. Moreover, demographic attributes like gender, ethnicity and age are available.

Features can be visualized with the packages magick and ggplot2:

library(magick)
library(ggplot2)
 
 finn_image %>% image_read() %>% image_ggplot() + 
   geom_rect(data = finn_face, 
             aes(xmin = top_left_x, xmax = top_left_x + width, 
                 ymin = top_left_y, ymax = top_left_y + height),
             fill = NA, linetype = 'dashed', size = 2, color = '#377eb8') +
   geom_label(data = finn_face,
             aes(x = chin_tip_x, y = chin_tip_y + 20, 
                 label = paste('Gender:', 
                               scales::percent(face_gender_male_confidence),
                 'Male')), size = 6, color = '#377eb8') +
   geom_label(data = finn_face,
             aes(x = chin_tip_x, y = chin_tip_y + 60, 
                 label = paste('Ethnicity:', scales::percent(face_black),
                 'Black')), size = 6, color = '#377eb8') +
   theme(legend.position="none")

Kairos has some recommendations to improve the quality of its recognition service, but in general, the API also works with multiple faces inside an image:

sw_img <- "https://upload.wikimedia.org/wikipedia/en/8/82/Leiadeathstar.jpg"
sw_faces <- detect(sw_img)
 
sw_img %>% image_read() %>% image_ggplot() + 
   geom_rect(data = sw_faces, 
             aes(xmin = top_left_x , xmax =  top_left_x + width, 
                 ymin = top_left_y, ymax = top_left_y + height, 
                 color = factor(face_id)),
             fill = NA, linetype = 'dashed', size = 2) +
   geom_label(data = sw_faces,
             aes(x = chin_tip_x, y = chin_tip_y + 15, 
                 label = face_gender_type,
                 color = factor(face_id)), size = 8) +
   theme(legend.position="none")

Besides annotating faces in single images, face recognition data can be stored permantly with the Kairos. This allows to assign multiple images to subject ids and to provide estimates about whether faces from different images belong to the same subjects.

finn_face <- enroll(image = finn_image, subject_id = 'finn', gallery = 'starwars')
finn_new <- 'https://upload.wikimedia.org/wikipedia/commons/b/b6/John_Boyega_by_Gage_Skidmore.jpg'
finn_rec <- recognize(image = finn_new, gallery = 'starwars',
                      show_candidate_images = FALSE)

The function recognize() returns a dataframe including the probability of a match in the column confidence.

Citation

If you use facerec for your publications please consider citing it:

  Carsten Schwemmer (2018). facerec: An interface for face recognition in R. R package version 0.1.0.
  https://github.com/methodds/facerec

A BibTeX entry for LaTeX users is:

  @Manual{,
    title = {facerec: An interface for face recognition in R},
    author = {Carsten Schwemmer},
    year = {2018},
    note = {R package version 0.1.0},
    url = {https://github.com/methodds/facerec},
  }

News

facerec 0.1.0

  • First release of the facerec package.

Reference manual

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install.packages("facerec")

0.1.0 by Carsten Schwemmer, 10 months ago


https://github.com/methodds/facerec


Report a bug at https://github.com/methodds/facerec/issues


Browse source code at https://github.com/cran/facerec


Authors: Carsten Schwemmer [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports magrittr, dplyr, httr, jsonlite, knitr, stringr, snakecase, rlang

Suggests magick, ggplot2, purrr, rmarkdown


See at CRAN