Skip to main content

Recognize faces from Python or from the command line

Project description

Face Recognition

Recognize and manipulate faces from Python or from the command line with
the world's simplest face recognition library.

Built using `dlib <>`__'s state-of-the-art face
recognition built with deep learning. The model has an accuracy of
99.38% on the `Labeled Faces in the
Wild <>`__ benchmark.

This also provides a simple ``face_recognition`` command line tool that
lets you do face recognition on a folder of images from the command

|image0| |image1|


Find faces in pictures

Find all the faces that appear in a picture:

.. figure::

.. code:: python

import face_recognition
image = face_recognition.load_image_file("your_file.jpg")
face_locations = face_recognition.face_locations(image)

Find and manipulate facial features in pictures

Get the locations and outlines of each person's eyes, nose, mouth and

.. figure::

.. code:: python

import face_recognition
image = face_recognition.load_image_file("your_file.jpg")
face_landmarks_list = face_recognition.face_landmarks(image)

Finding facial features is super useful for lots of important stuff. But
you can also use for really stupid stuff like applying `digital
make-up <>`__
(think 'Meitu'):

.. figure::

Identify faces in pictures

Recognize who appears in each photo.

.. figure::

.. code:: python

import face_recognition
known_image = face_recognition.load_image_file("biden.jpg")
unknown_image = face_recognition.load_image_file("unknown.jpg")

biden_encoding = face_recognition.face_encodings(known_image)[0]
unknown_encoding = face_recognition.face_encodings(unknown_image)

results = face_recognition.compare_faces([biden_encoding], unknown_encoding)


Python 3 is fully supported. Python 2 should also work. Only macOS and
Linux are tested. I have no idea if this will work on Windows.

You can install this module from pypi using ``pip3`` (or ``pip2`` for
Python 2):

.. code:: bash

$ pip3 install face_recognition

It's very likely that you will run into problems when pip tries to
compile the ``dlib`` dependency. If that happens, check out this guide
to installing dlib from source instead to fix the error:

`How to install dlib from
source <>`__

After manually installing ``dlib``, try running
``pip3 install face_recognition`` again.


Command-Line Interface

When you install ``face_recognition``, you get a simple command-line
program called ``face_recognition`` that you can use to recognize faces
in a photograph or folder full for photographs.

First, you need to provide a folder with one picture of each person you
already know. There should be one image file for each person with the
files named according to who is in the picture:

.. figure::
:alt: known


Next, you need a second folder with the files you want to identify:

.. figure::
:alt: unknown


Then in you simply run the commnad ``face_recognition``, passing in the
folder of known people and the folder (or single image) with unknown
people and it tells you who is in each image:

.. code:: bash

$ face_recognition ./pictures_of_people_i_know/ ./unknown_pictures/

/unknown_pictures/unknown.jpg,Barack Obama

There's one line in the output for each face. The data is
comma-separated with the filename and the name of the person found.

An ``unknown_person`` is a face in the image that didn't match anyone in
your folder of known people.

If you simply want to know the names of the people in each photograph
but don't care about file names, you could do this:

.. code:: bash

$ face_recognition ./pictures_of_people_i_know/ ./unknown_pictures/ | cut -d ',' -f2

Barack Obama

Python Module

You can import the ``face_recognition`` module and then easily
manipulate faces with just a couple of lines of code. It's super easy!

API Docs:

Automatically find all the faces in an image

.. code:: python

import face_recognition

image = face_recognition.load_image_file("my_picture.jpg")
face_locations = face_recognition.face_locations(image)

# face_locations is now an array listing the co-ordinates of each face!

See `this
example <>`__
to try it out.

Automatically locate the facial features of a person in an image

.. code:: python

import face_recognition

image = face_recognition.load_image_file("my_picture.jpg")
face_landmarks_list = face_recognition.face_landmarks(image)

# face_landmarks_list is now an array with the locations of each facial feature in each face.
# face_landmarks_list[0]['left_eye'] would be the location and outline of the first person's left eye.

See `this
example <>`__
to try it out.

Recognize faces in images and identify who they are

.. code:: python

import face_recognition

picture_of_me = face_recognition.load_image_file("me.jpg")
my_face_encoding = face_recognition.face_encodings(picture_of_me)[0]

# my_face_encoding now contains a universal 'encoding' of my facial features that can be compared to any other picture of a face!

unknown_picture = face_recognition.load_image_file("unknown.jpg")
unknown_face_encoding = face_recognition.face_encodings(unknown_picture)[0]

# Now we can see the two face encodings are of the same person with `compare_faces`!

results = face_recognition.compare_faces([my_face_encoding], unknown_face_encoding)

if results[0] == True:
print("It's a picture of me!")
print("It's not a picture of me!")

See `this
example <>`__
to try it out.

Python Code Examples

All the examples are available
`here <>`__.

- `Find faces in an
photograph <>`__
- `Identify specific facial features in a
photograph <>`__
- `Apply (horribly ugly) digital
make-up <>`__
- `Find and recognize unknown faces in a photograph based on
photographs of known
people <>`__


- The face recognition model is trained on adults does not work very
well on children. It tends to mix up children quite easy using the
default comparison threshold of 0.6.


- Many, many thanks to `Davis King <>`__
([@nulhom]( for creating dlib and for
providing the trained facial feature detection and face encoding
models used in this library. For more information on the ResNet the
powers the face encodings, check out his `blog
post <>`__.
- Everyone who works on all the awesome Python data science libraries
like numpy, scipy, scikit-image, pillow, etc, etc that makes this
kind of stuff so easy and fun in Python.
- `Cookiecutter <>`__ and the
`audreyr/cookiecutter-pypackage <>`__
project template for making Python project packaging way more

.. |image0| image::
.. |image1| image::


0.1.0 (2017-03-03)

* First test release.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

face_recognition-0.1.4.tar.gz (1.4 MB view hashes)

Uploaded Source

Built Distribution

face_recognition-0.1.4-py2.py3-none-any.whl (11.8 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page