Metadata-Version: 1.1
Name: face-recognition
Version: 0.1.4
Summary: Recognize faces from Python or from the command line
Home-page: https://github.com/ageitgey/face_recognition
Author: Adam Geitgey
Author-email: ageitgey@gmail.com
License: MIT license
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 <http://dlib.net/>`__'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 <http://vis-www.cs.umass.edu/lfw/>`__ 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
        line!
        
        |image0| |image1|
        
        Features
        --------
        
        Find faces in pictures
        ^^^^^^^^^^^^^^^^^^^^^^
        
        Find all the faces that appear in a picture:
        
        .. figure:: https://cloud.githubusercontent.com/assets/896692/23625227/42c65360-025d-11e7-94ea-b12f28cb34b4.png
           :alt: 
        
        .. 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
        chin.
        
        .. figure:: https://cloud.githubusercontent.com/assets/896692/23625282/7f2d79dc-025d-11e7-8728-d8924596f8fa.png
           :alt: 
        
        .. 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 <https://github.com/ageitgey/face_recognition/blob/master/examples/digital_makeup.py>`__
        (think 'Meitu'):
        
        .. figure:: https://cloud.githubusercontent.com/assets/896692/23625283/80638760-025d-11e7-80a2-1d2779f7ccab.png
           :alt: 
        
        Identify faces in pictures
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        Recognize who appears in each photo.
        
        .. figure:: https://cloud.githubusercontent.com/assets/896692/23625229/45e049b6-025d-11e7-89cc-8a71cf89e713.png
           :alt: 
        
        .. 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)
        
        Installation
        ------------
        
        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 <https://gist.github.com/ageitgey/629d75c1baac34dfa5ca2a1928a7aeaf>`__
        
        After manually installing ``dlib``, try running
        ``pip3 install face_recognition`` again.
        
        Usage
        -----
        
        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:: https://cloud.githubusercontent.com/assets/896692/23582466/8324810e-00df-11e7-82cf-41515eba704d.png
           :alt: known
        
           known
        
        Next, you need a second folder with the files you want to identify:
        
        .. figure:: https://cloud.githubusercontent.com/assets/896692/23582465/81f422f8-00df-11e7-8b0d-75364f641f58.png
           :alt: unknown
        
           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
            /face_recognition_test/unknown_pictures/unknown.jpg,unknown_person
        
        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
            unknown_person
        
        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: https://face-recognition.readthedocs.io.
        
        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 <https://github.com/ageitgey/face_recognition/blob/master/examples/find_faces_in_picture.py>`__
        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 <https://github.com/ageitgey/face_recognition/blob/master/examples/find_facial_features_in_picture.py>`__
        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!")
            else:
                print("It's not a picture of me!")
        
        See `this
        example <https://github.com/ageitgey/face_recognition/blob/master/examples/recognize_faces_in_pictures.py>`__
        to try it out.
        
        Python Code Examples
        --------------------
        
        All the examples are available
        `here <https://github.com/ageitgey/face_recognition/tree/master/examples>`__.
        
        -  `Find faces in an
           photograph <https://github.com/ageitgey/face_recognition/blob/master/examples/find_faces_in_picture.py>`__
        -  `Identify specific facial features in a
           photograph <https://github.com/ageitgey/face_recognition/blob/master/examples/find_facial_features_in_picture.py>`__
        -  `Apply (horribly ugly) digital
           make-up <https://github.com/ageitgey/face_recognition/blob/master/examples/digital_makeup.py>`__
        -  `Find and recognize unknown faces in a photograph based on
           photographs of known
           people <https://github.com/ageitgey/face_recognition/blob/master/examples/recognize_faces_in_pictures.py>`__
        
        Caveats
        -------
        
        -  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.
        
        Thanks
        ------
        
        -  Many, many thanks to `Davis King <https://github.com/davisking>`__
           ([@nulhom](https://twitter.com/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 <http://blog.dlib.net/2017/02/high-quality-face-recognition-with-deep.html>`__.
        -  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 <https://github.com/audreyr/cookiecutter>`__ and the
           `audreyr/cookiecutter-pypackage <https://github.com/audreyr/cookiecutter-pypackage>`__
           project template for making Python project packaging way more
           tolerable.
        
        .. |image0| image:: https://img.shields.io/pypi/v/face_recognition.svg
        .. |image1| image:: https://travis-ci.org/ageitgey/face_recognition
        
        
        
        =======
        History
        =======
        
        0.1.0 (2017-03-03)
        ------------------
        
        * First test release.
        
Keywords: face_recognition
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
