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Recognize faces from Python or from the command line

Project description

Face Recognition

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

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

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

| |PyPI|
| |Build Status|
| |Documentation Status|


Find faces in pictures

Find all the faces that appear in a picture:


.. 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


.. 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'):


Identify faces in pictures

Recognize who appears in each photo.


.. 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)[0]

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


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

Install this module from pypi using ``pip3`` (or ``pip2`` for Python 2):

.. code:: bash

pip3 install face_recognition

| IMPORTANT NOTE: 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
| dlib from source (instead of from pip) to fix the error:

`How to install dlib from
source <>`__

| After manually installing ``dlib``, try running
``pip3 install face_recognition``
| again to complete your installation.


Command-Line Interface

| When you install ``face_recognition``, you get a simple command-line
| 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
| already know. There should be one image file for each person with the
| files named according to who is in the picture:


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


| Then in you simply run the command ``face_recognition``, passing in
| the folder of known people and the folder (or single image) with
| 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
| with the filename and the name of the person found.

| An ``unknown_person`` is a face in the image that didn't match anyone
| 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
| 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 a
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 <>`__
- `Recognize faces in live video using your webcam (Requires OpenCV to
installed) <>`__

How Face Recognition Works

| If you want to learn how face location and recognition work instead of
| depending on a black box library, `read my
article <>`__.


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

Common Issues

Issue: ``Illegal instruction (core dumped)`` when using face\_recognition or running examples.

| Solution: ``dlib`` is compiled with SSE4 or AVX support, but your CPU
is too old and doesn't support that.
| You'll need to recompile ``dlib`` after `making the code change
here <>`__.

Issue: ``RuntimeError: Unsupported image type, must be 8bit gray or RGB image.`` when running the webcam example.

Solution: Your webcam probably isn't set up correctly with OpenCV. `Look
here for
more <>`__.

Issue: ``MemoryError`` when running ``pip2 install face_recognition``

| Solution: The face\_recognition\_models file is too big for your
available pip cache memory. Instead,
| try ``pip2 --no-cache-dir install face_recognition`` to avoid the


- 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 that powers
the face encodings, check out
his `blog
post <>`__.
- Thanks to 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
- Thanks to `Cookiecutter <>`__
and the
`audreyr/cookiecutter-pypackage <>`__
project template
for making Python project packaging way more tolerable.

.. |PyPI| image::
.. |Build Status| image::
.. |Documentation Status| image::
.. |image3| image::
.. |image4| image::
.. |image5| image::
.. |image6| image::
.. |known| image::
.. |unknown| image::


0.1.11 (2017-03-30)

* Fixed a minor bug in the command-line interface.

0.1.10 (2017-03-21)

* Minor pref improvements with face comparisons.
* Test updates.

0.1.9 (2017-03-16)

* Fix minimum scipy version required.

0.1.8 (2017-03-16)

* Fix missing Pillow dependency.

0.1.7 (2017-03-13)

* First working release.

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