Step-by-Step Guide to Building a Face Recognition System on Ubuntu with Python

Environment Requirements

Ubuntu 17.10

Python 2.7.14

Environment Setup

Install Ubuntu 17.10 (installation steps linked in the original article).

Python 2.7.14 is the default version on Ubuntu 17.10.

Install git, cmake, and python‑pip.

# Install git
$ sudo apt-get install -y git
# Install cmake
$ sudo apt-get install -y cmake
# Install python-pip
$ sudo apt-get install -y python-pip

Compile and install dlib (requires Boost).

# Install Boost
$ sudo apt-get install libboost-all-dev

# Clone dlib source
$ git clone https://github.com/davisking/dlib.git
$ cd dlib
$ mkdir build
$ cd build
$ cmake .. -DDLIB_USE_CUDA=0 -DUSE_AVX_INSTRUCTIONS=1
$ cmake --build .   # note the space
$ cd ..
$ python setup.py install --yes USE_AVX_INSTRUCTIONS --no DLIB_USE_CUDA

Install the face_recognition package.

# Install face_recognition
$ pip install face_recognition
# Dependencies such as numpy and scipy are installed automatically

Face Recognition Examples

Example 1: One‑line face recognition

Prepare a folder of known people (one image per person, filename is the name) and another folder of images to identify, then run the face_recognition command with both folders as arguments.

Example 2: Detect all faces in a picture

# filename: find_faces_in_picture.py
# -*- coding: utf-8 -*-
from PIL import Image
import face_recognition

image = face_recognition.load_image_file("/opt/face/unknown_pic/all_star.jpg")
face_locations = face_recognition.face_locations(image)
print("I found {} face(s) in this photograph.".format(len(face_locations)))
for face_location in face_locations:
    top, right, bottom, left = face_location
    print("A face is located at pixel location Top: {}, Left: {}, Bottom: {}, Right: {}".format(top, left, bottom, right))
    face_image = image[top:bottom, left:right]
    pil_image = Image.fromarray(face_image)
    pil_image.show()

Example 3: Automatic facial feature detection

# filename: find_facial_features_in_picture.py
# -*- coding: utf-8 -*-
from PIL import Image, ImageDraw
import face_recognition

image = face_recognition.load_image_file("biden.jpg")
face_landmarks_list = face_recognition.face_landmarks(image)
print("I found {} face(s) in this photograph.".format(len(face_landmarks_list)))
for face_landmarks in face_landmarks_list:
    facial_features = ['chin','left_eyebrow','right_eyebrow','nose_bridge','nose_tip','left_eye','right_eye','top_lip','bottom_lip']
    for facial_feature in facial_features:
        print("The {} in this face has the following points: {}".format(facial_feature, face_landmarks[facial_feature]))
    pil_image = Image.fromarray(image)
    d = ImageDraw.Draw(pil_image)
    for facial_feature in facial_features:
        d.line(face_landmarks[facial_feature], width=5)
    pil_image.show()

Example 4: Identify a specific person

# filename: recognize_faces_in_pictures.py
# -*- coding: utf-8 -*-
import face_recognition

babe_image = face_recognition.load_image_file("/opt/face/known_people/babe.jpeg")
rong_image = face_recognition.load_image_file("/opt/face/known_people/Rong zhu er.jpg")
unknown_image = face_recognition.load_image_file("/opt/face/unknown_pic/babe2.jpg")

babe_face_encoding = face_recognition.face_encodings(babe_image)[0]
rong_face_encoding = face_recognition.face_encodings(rong_image)[0]
unknown_face_encoding = face_recognition.face_encodings(unknown_image)[0]

known_faces = [babe_face_encoding, rong_face_encoding]
results = face_recognition.compare_faces(known_faces, unknown_face_encoding)

print("Is the unknown face Babe? {}".format(results[0]))
print("Is the unknown face Rong Zhu Er? {}".format(results[1]))
print("Is the unknown face a new person? {}".format(not any(results)))

Example 5: Facial feature beautification

# filename: digital_makeup.py
# -*- coding: utf-8 -*-
from PIL import Image, ImageDraw
import face_recognition

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

for face_landmarks in face_landmarks_list:
    pil_image = Image.fromarray(image)
    d = ImageDraw.Draw(pil_image, 'RGBA')
    d.polygon(face_landmarks['left_eyebrow'], fill=(68, 54, 39, 128))
    d.polygon(face_landmarks['right_eyebrow'], fill=(68, 54, 39, 128))
    d.line(face_landmarks['left_eyebrow'], fill=(68, 54, 39, 150), width=5)
    d.line(face_landmarks['right_eyebrow'], fill=(68, 54, 39, 150), width=5)
    d.polygon(face_landmarks['top_lip'], fill=(150, 0, 0, 128))
    d.polygon(face_landmarks['bottom_lip'], fill=(150, 0, 0, 128))
    d.line(face_landmarks['top_lip'], fill=(150, 0, 0, 64), width=8)
    d.line(face_landmarks['bottom_lip'], fill=(150, 0, 0, 64), width=8)
    d.polygon(face_landmarks['left_eye'], fill=(255, 255, 255, 30))
    d.polygon(face_landmarks['right_eye'], fill=(255, 255, 255, 30))
    d.line(face_landmarks['left_eye'] + [face_landmarks['left_eye'][0]], fill=(0, 0, 0, 110), width=6)
    d.line(face_landmarks['right_eye'] + [face_landmarks['right_eye'][0]], fill=(0, 0, 0, 110), width=6)
    pil_image.show()