FaceRecognize

FaceRecognize[{example1name1,example2name2,…}]

generates a ClassifierFunction[…] based on the face examples and names given.

FaceRecognize[{example1,example2,…}{name1,name2,…}]

also generates a ClassifierFunction[…] based on the examples and names given.

FaceRecognize[name1{example11,…},name2{example21,…},…]

uses an association of names with their examples.

FaceRecognize[training,image]

attempts to find faces present in an image and classify them with the given training set.

FaceRecognize[training,image,prop]

returns the specified property prop.

Details and Options

  • FaceRecognize can be trained to be used for recognizing occurrences of people's faces in images.
  • FaceRecognize[training,{image1,image2,…}], returns recognized faces in all imagei.
  • By default, FaceRecognize gives a list of names associated with faces it recognizes.
  • Possible settings for property prop are:
  • "BoundingBox"bounding Rectangle of the face
    "Image"a crop of image corresponding to the face
    "Name"name associated to a face
    "Position"the position of each face given as {x,y}
    "Probability"probability for a specific match
    "RarerProbability"probability to generate a sample with lower PDF than faces in image
    {prop1,prop2,…}a list of property specifications
  • The following options can be given:
  • AcceptanceThreshold Automaticthreshold to consider an example anomalous
    ClassPriors Automaticprior probability for a match
    Method Automaticmethod to use
  • By default, a uniform prior is assumed over all the names. Use ClassPriors<|name1p1,…|> to specify different priors.
  • By default, the faces are detected automatically. Use Method{"FaceBoxes"boxes} to specify bounding boxes around faces.
  • Possible values for boxes can be any of the following:
  • Automaticuse FindFaces to find the face boxes (default)
    Fullthe whole image is assumed to be one face
    {bbox1,…}a list of bounding boxes for faces
  • FaceRecognize uses machine learning. Its methods, training sets and biases included therein may change and yield varied results in different versions of the Wolfram Language.
  • FaceRecognize may download resources that will be stored in your local object store at $LocalBase, and that can be listed using LocalObjects[] and removed using ResourceRemove.

Examples

open allclose all

Basic Examples  (3)

Recognize if a given person is present in an image:

Create a ClassifierFunction from a set of images:

Apply the classifier to a face:

If a face is not among the training examples, Missing is returned:

Recognize multiple faces:

Highlight the faces on the original image:

Scope  (6)

Create a ClassifierFunction that can recognize faces:

Recognize a face:

If the face is not recognized, Missing is returned:

Provide multiple references for the same person:

Group the references in an Association:

Return a list of properties:

Return all supported properties:

Recognize multiple faces in an image:

Recognize multiple faces in a list of images:

Options  (3)

AcceptanceThreshold  (1)

Specify AcceptanceThreshold to control how many faces are recognized:

Use a lower value to recognize faces far from the training distribution:

Using AcceptanceThreshold0 always returns the nearest class to the test image:

ClassPriors  (1)

By default, FaceRecognize assumes uniform probability among the classes:

Specify the class priors:

Method  (1)

By default, faces are detected and extracted from the test image:

Use Method{"FaceBoxes"Full} to assume the test image is a single face crop:

Use Method{"FaceBoxes"bboxes} to recognize faces in the specified bounding boxes bboxes:

Applications  (4)

Verify whether two faces belong to the same person:

Create a function that detects whether an image contains a specified person:

Test whether a person appears in an image:

FaceRecognize can be used to find the face nearest to the test image:

Build a face-search function that returns the position of images that contain a specific person:

Possible Issues  (2)

Training is still performed with images that may not be faces:

Testing can also be done with images that may not be faces:

FaceRecognize expects face crops for all training face samples:

Compare with already-cropped face samples:

Wolfram Research (2020), FaceRecognize, Wolfram Language function, https://reference.wolfram.com/language/ref/FaceRecognize.html.

Text

Wolfram Research (2020), FaceRecognize, Wolfram Language function, https://reference.wolfram.com/language/ref/FaceRecognize.html.

CMS

Wolfram Language. 2020. "FaceRecognize." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/FaceRecognize.html.

APA

Wolfram Language. (2020). FaceRecognize. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/FaceRecognize.html

BibTeX

@misc{reference.wolfram_2024_facerecognize, author="Wolfram Research", title="{FaceRecognize}", year="2020", howpublished="\url{https://reference.wolfram.com/language/ref/FaceRecognize.html}", note=[Accessed: 22-November-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_facerecognize, organization={Wolfram Research}, title={FaceRecognize}, year={2020}, url={https://reference.wolfram.com/language/ref/FaceRecognize.html}, note=[Accessed: 22-November-2024 ]}