python2.7,opencvで顔認識

faceDetect.py

import cv2
from os import path
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline

cascades_dir = path.normpath(path.join(cv2.__file__, '..', '..', '..', '..', 'share', 'OpenCV', 'haarcascades'))
cascade_f = cv2.CascadeClassifier(path.join(cascades_dir, 'haarcascade_frontalface_alt2.xml'))

def faceDetect(filePath):
    img = cv2.imread(filePath)
    
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    faces = cascade_f.detectMultiScale(img, 1.3, 5)

    if len(faces) > 0:
        cnt = 1
        for(x, y, w, h) in faces:
#             顔を四角で囲む
            cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
#             顔だけを表示
            cut_face_img = img[y:y+h,x:x+w]            
    
#             横一列に顔を表示
            plt.subplot(1, len(faces), cnt)
            plt.imshow(cv2.cvtColor(cut_face_img, cv2.COLOR_BGR2RGB))
            
            cnt += 1
            
        plt.show()
        
    else:
        print 'no face'
    
faceDetect('images/mai001.jpg')

def getCroppedFace(filePath):
    img = cv2.imread(filePath)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    faces = cascade_f.detectMultiScale(img, 1.3, 5)
    
    cropped_size = 100

    if len(faces) > 0:
        for(x, y, w, h) in faces:
            cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
            cut_face_img = img[y:y+h,x:x+w]
            
            return cut_face_img
    else:
        print 'no face'
        return false

def getResizedImage(img):
    cropped_size = 100
    resized_img = cv2.resize(img, (cropped_size, cropped_size))
    return resized_img
    
croppedFace = getCroppedFace('images/mai001.jpg')
# croppedFace = getResizedImage(croppedFace)
plt.imshow(cv2.cvtColor(croppedFace, cv2.COLOR_BGR2RGB))
plt.show()

def getRotateImage(img, angle):
    original_width, original_height = img.shape[:2]
    size = original_width
    matrix = cv2.getRotationMatrix2D((size / 2, size / 2), angle, 1.0)
    rotated_img = cv2.warpAffine(img, matrix, (size, size))
    
    return rotated_img
    
for delta_angle in range(-150, 150, 50):
    rotated_img = getRotateImage(croppedFace, delta_angle)

    plt.imshow(cv2.cvtColor(rotated_img, cv2.COLOR_BGR2RGB))
    plt.show()