In [1]:

    

import numpy as np
import cv2


    

In [2]:

    

im = np.load('/home/mckc/all_test/Abhay_10.npy')
plt.imshow(im)


    

In [6]:

    

image = cv2.imread('/home/mckc/All Data/Abhay_cap_specs_0.jpg') 
plt.imshow(image)


    

In [4]:

    

import matplotlib.pyplot as plt
%matplotlib inline


    

In [13]:

    

face_cascade = cv2.CascadeClassifier('/home/mckc/Downloads/opencv-2.4.13/data/haarcascades_GPU/haarcascade_frontalface_default.xml')

faces  = face_cascade.detectMultiScale(image,scaleFactor=1.3,minNeighbors=5,minSize=(70, 70))
for (x,y,w,h) in faces:
    fac_cv = np.array(image)[y:(y+h),x:(x+h)]
plt.imshow(fac_cv)


    

    
Out[13]:





<matplotlib.image.AxesImage at 0x7f6030fb5a10>






    

In [15]:

    

import dlib

detector = dlib.get_frontal_face_detector()
faces = detector(image, 1)
for a,b in enumerate(faces):
    fac_dlib = np.array(image)[b.top():b.bottom(),b.left():b.right(),:]
plt.imshow(fac_dlib)


    

    
Out[15]:





<matplotlib.image.AxesImage at 0x7f602a71ac10>






    

In [18]:

    

print fac_dlib.shape,fac_cv.shape


    

    




(799, 799, 3) (945, 945, 3)

In [20]:

    

from skimage.transform import resize

n_fac_dlib = resize(fac_dlib,(224,224,3))
n_fac_cv = resize(fac_cv,(224,224,3))


    

In [21]:

    

plt.imshow(n_fac_cv)


    

    
Out[21]:





<matplotlib.image.AxesImage at 0x7f601c561890>






    

In [22]:

    

plt.imshow(n_fac_dlib)


    

    
Out[22]:





<matplotlib.image.AxesImage at 0x7f601c4a9310>






    

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