In [1]:

    

import cv2

print('OpenCV Version: {}'.format(cv2.__version__))


    

    




OpenCV Version: 3.3.0

In [2]:

    

# Used to display the images.
%matplotlib inline
from matplotlib import pyplot as plt


    

In [3]:

    

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')


    

In [5]:

    

image = cv2.imread('./input/liv-tyler.jpg')


    

In [13]:

    

scale_factor = 1.1
min_neighbors = 3
min_size = (30, 30)
flags = cv2.CASCADE_SCALE_IMAGE

faces = face_cascade.detectMultiScale(image,
                                      scaleFactor=scale_factor,
                                      minNeighbors=min_neighbors,
                                      minSize=min_size,
                                      flags=flags)

x, y, w, h = faces[0]


    

In [7]:

    

cv2.rectangle(image, (x, y), (x + w, y + h), (255, 255, 0), 2)

cv2.imwrite('./output/highlight-liv-tyler-face.jpg', image)


    

    
Out[7]:





True

In [8]:

    

image = cv2.imread('./input/liv-tyler.jpg')

crop_image = image[y-50:y+h+50, x-50:x+w+50]

cv2.imwrite('./output/crop-liv-tyler-face.jpg', crop_image)


    

    
Out[8]:





True

In [9]:

    

image = cv2.imread('./input/justice-league.jpg')


    

In [10]:

    

scale_factor = 1.1
min_neighbors = 3
min_size = (30, 30)
flags = cv2.CASCADE_SCALE_IMAGE

faces = face_cascade.detectMultiScale(image,
                                      scaleFactor=scale_factor,
                                      minNeighbors=min_neighbors,
                                      minSize=min_size,
                                      flags=flags)


    

In [14]:

    

for x, y, w, h in faces:
    cv2.rectangle(image, (x, y), (x + w, y + h), (255, 255, 0), 2)

cv2.imwrite('./output/highlight-faces-justice-leauge.jpg', image)


    

    
Out[14]:





True

In [15]:

    

image = cv2.imread('./input/justice-league.jpg')

for x, y, w, h in faces:
    crop_image = image[y-50:y+h+50, x-50:x+w+50]
    cv2.imwrite('./output/crop-justice-leauge-face_{0}-{1}.jpg'.format(x, y), crop_image)


    

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