# Face Recognition
_You can also read a translated version of this file [in Chinese 简体中文版](https://github.com/ageitgey/face_recognition/blob/master/README_Simplified_Chinese.md) or [in Korean 한국어](https://github.com/ageitgey/face_recognition/blob/master/README_Korean.md) or [in Japanese 日本語](https://github.com/m-i-k-i/face_recognition/blob/master/README_Japanese.md)._
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!
[![PyPI](https://img.shields.io/pypi/v/face_recognition.svg)](https://pypi.python.org/pypi/face_recognition)
[![Build Status](https://github.com/ageitgey/face_recognition/workflows/CI/badge.svg?branch=master&event=push)](https://github.com/ageitgey/face_recognition/actions?query=workflow%3ACI)
[![Documentation Status](https://readthedocs.org/projects/face-recognition/badge/?version=latest)](http://face-recognition.readthedocs.io/en/latest/?badge=latest)
## Features
#### Find faces in pictures
Find all the faces that appear in a picture:
![](https://cloud.githubusercontent.com/assets/896692/23625227/42c65360-025d-11e7-94ea-b12f28cb34b4.png)
```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.
![](https://cloud.githubusercontent.com/assets/896692/23625282/7f2d79dc-025d-11e7-8728-d8924596f8fa.png)
```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 it for really stupid stuff
like applying [digital make-up](https://github.com/ageitgey/face_recognition/blob/master/examples/digital_makeup.py) (think 'Meitu'):
![](https://cloud.githubusercontent.com/assets/896692/23625283/80638760-025d-11e7-80a2-1d2779f7ccab.png)
#### Identify faces in pictures
Recognize who appears in each photo.
![](https://cloud.githubusercontent.com/assets/896692/23625229/45e049b6-025d-11e7-89cc-8a71cf89e713.png)
```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)
```
You can even use this library with other Python libraries to do real-time face recognition:
![](https://cloud.githubusercontent.com/assets/896692/24430398/36f0e3f0-13cb-11e7-8258-4d0c9ce1e419.gif)
See [this example](https://github.com/ageitgey/face_recognition/blob/master/examples/facerec_from_webcam_faster.py) for the code.
## Online Demos
User-contributed shared Jupyter notebook demo (not officially supported): [![Deepnote](https://beta.deepnote.org/buttons/try-in-a-jupyter-notebook.svg)](https://beta.deepnote.org/launch?template=face_recognition)
## Installation
### Requirements
* Python 3.3+ or Python 2.7
* macOS or Linux (Windows not officially supported, but might work)
### Installation Options:
#### Installing on Mac or Linux
First, make sure you have dlib already installed with Python bindings:
* [How to install dlib from source on macOS or Ubuntu](https://gist.github.com/ageitgey/629d75c1baac34dfa5ca2a1928a7aeaf)
Then, make sure you have cmake installed:
```brew install cmake```
Finally, install this module from pypi using `pip3` (or `pip2` for Python 2):
```bash
pip3 install face_recognition
```
Alternatively, you can try this library with [Docker](https://www.docker.com/), see [this section](#deployment).
If you are having trouble with installation, you can also try out a
[pre-configured VM](https://medium.com/@ageitgey/try-deep-learning-in-python-now-with-a-fully-pre-configured-vm-1d97d4c3e9b).
#### Installing on an Nvidia Jetson Nano board
* [Jetson Nano installation instructions](https://medium.com/@ageitgey/build-a-hardware-based-face-recognition-system-for-150-with-the-nvidia-jetson-nano-and-python-a25cb8c891fd)
* Please follow the instructions in the article carefully. There is current a bug in the CUDA libraries on the Jetson Nano that will cause this library to fail silently if you don't follow the instructions in the article to comment out a line in dlib and recompile it.
#### Installing on Raspberry Pi 2+
* [Raspberry Pi 2+ installation instructions](https://gist.github.com/ageitgey/1ac8dbe8572f3f533df6269dab35df65)
#### Installing on FreeBSD
```bash
pkg install graphics/py-face_recognition
```
#### Installing on Windows
While Windows isn't officially supported, helpful users have posted instructions on how to install this library:
* [@masoudr's Windows 10 installation guide (dlib + face_recognition)](https://github.com/ageitgey/face_recognition/issues/175#issue-257710508)
#### Installing a pre-configured Virtual Machine image
* [Download the pre-configured VM image](https://medium.com/@ageitgey/try-deep-learning-in-python-now-with-a-fully-pre-configured-vm-1d97d4c3e9b) (for VMware Player or VirtualBox).
## Usage
### Command-Line Interface
When you install `face_recognition`, you get two simple command-line
programs:
* `face_recognition` - Recognize faces in a photograph or folder full for
photographs.
* `face_detection` - Find faces in a photograph or folder full for photographs.
#### `face_recognition` command line tool
The `face_recognition` command lets you 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:
![known](https://cloud.githubusercontent.com/assets/896692/23582466/8324810e-00df-11e7-82cf-41515eba704d.png)
Next, you need a second folder with the files you want to identify:
![unknown](https://cloud.githubusercontent.com/assets/896692/23582465/81f422f8-00df-11e7-8b0d-75364f641f58.png)
Then in you simply run the command `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:
```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.
#### `face_detection` command line tool
The `face_detection` command lets you find the location (pixel coordinatates)
of any faces in an image.
Just run the command `face_detection`, passing in a folder of images
to check (or a single image):
```bash
$ face_detection ./folder_with_pictures/
examples/image1.jpg,65,215,169,112
examples/image2.jpg,62,394,211,244
examples/image2.jpg,95,941,244,792
```
It prints one line for each face that was detected. The coordinates
reported are the top, right, bottom and left coordinates of the face (in pixels).
##### Adjusting Tolerance / Sensitivity
If you are getting multiple matches for the same person, it might be that
the people in your photos look very similar and a lower tolerance value
is needed
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The_world's_simplest_facial_recognition (106个子文件)
make.bat 6KB
setup.cfg 508B
Dockerfile 2KB
Dockerfile 2KB
Dockerfile 1KB
Dockerfile 497B
Dockerfile 497B
Dockerfile-python-example 573B
.editorconfig 292B
.gitignore 795B
Dockerfile.gpu 1KB
MANIFEST.in 264B
tox.ini 299B
track_faces_on_video_realtime.ipynb 111KB
john1.jpeg 111KB
john2.jpeg 68KB
alex_lacamoire1.jpg 756KB
obama3.jpg 582KB
obama_and_biden.jpg 546KB
two_people.jpg 476KB
obama_partial_face2.jpg 467KB
obama_partial_face.jpg 413KB
obama-1080p.jpg 378KB
biden.jpg 345KB
biden.jpg 345KB
biden.jpg 345KB
obama.jpg 273KB
obama.jpg 273KB
obama.jpg 273KB
biden2.jpg 264KB
johnsnow_test1.jpg 224KB
obama-720p.jpg 197KB
img1.jpg 187KB
obama2.jpg 180KB
obama2.jpg 180KB
obama2.jpg 180KB
img2.jpg 155KB
kit_with_rose.jpg 130KB
obama-480p.jpg 100KB
obama1.jpg 77KB
img1.jpg 51KB
obama-240p.jpg 36KB
obama_small.jpg 33KB
LICENSE 1KB
Makefile 7KB
Makefile 2KB
README_Japanese.md 22KB
README_Korean.md 20KB
README_Simplified_Chinese.md 19KB
README.md 19KB
README.md 2KB
ISSUE_TEMPLATE.md 432B
hamilton_clip.mp4 4.9MB
short_hamilton_clip.mp4 600KB
32bit.png 867KB
lin-manuel-miranda.png 492KB
alex-lacamoire.png 178KB
test_face_recognition.py 15KB
api.py 10KB
facerec_ipcamera_knn.py 9KB
face_recognition_knn.py 9KB
conf.py 9KB
facerec_from_webcam_multiprocessing.py 7KB
web_service_example.py 5KB
web_service_example_Simplified_Chinese.py 5KB
face_recognition_cli.py 5KB
facerec_from_webcam_faster.py 4KB
blink_detection.py 3KB
facerec_from_webcam.py 3KB
facerec_from_video_file.py 3KB
identify_and_draw_boxes_on_faces.py 3KB
face_detection_cli.py 3KB
face_recognition_svm.py 2KB
benchmark.py 2KB
find_faces_in_batches.py 2KB
facerec_on_raspberry_pi.py 2KB
face_distance.py 2KB
facerec_on_raspberry_pi_Simplified_Chinese.py 2KB
setup.py 2KB
blur_faces_on_webcam.py 2KB
digital_makeup.py 1KB
recognize_faces_in_pictures.py 1KB
find_faces_in_picture_cnn.py 1KB
find_facial_features_in_picture.py 973B
find_faces_in_picture.py 907B
__init__.py 246B
__init__.py 24B
README.rst 17KB
HISTORY.rst 3KB
CONTRIBUTING.rst 3KB
usage.rst 2KB
installation.rst 1KB
AUTHORS.rst 573B
index.rst 302B
face_recognition.rst 178B
modules.rst 85B
contributing.rst 33B
history.rst 28B
authors.rst 28B
readme.rst 27B
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