In [3]:

    

import numpy as np
import cv2
import time
import os
os.chdir("/home/mckc/Imagedb/")
import uuid
import scipy.misc


face_cascade = cv2.CascadeClassifier('/home/mckc/Downloads/opencv-2.4.13/data/haarcascades_GPU/haarcascade_frontalface_default.xml')
cap = cv2.VideoCapture('/home/mckc/Downloads/2.mp4')


    

In [ ]:

    

i = 0
while(cap.grab()):
    #print 'inside'    
    time.sleep(0.01)
    ret, frame = cap.read()
    if i % 9 == 0:
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        cv2.imshow('Video', gray)
        gray = cv2.equalizeHist(gray)
        faces = face_cascade.detectMultiScale(gray,
        scaleFactor=1.1,
        minNeighbors=5,
        minSize=(50, 50),flags=cv2.cv.CV_HAAR_SCALE_IMAGE)
            # Draw a rectangle around the faces
        if len(faces)>0:    
            for (x, y, w, h) in faces:
                cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
                fac = np.array(gray)[y:(y+h),x:(x+h)]
                scipy.misc.toimage(fac).save(str(uuid.uuid4()) +'.jpg')
                fac = np.array(frame)[y:(y+h),x:(x+h)]
            cv2.imshow('Video', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
    i = i + 1
cap.release()
cv2.destroyAllWindows()


    

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