Face Recognition - Fixed Tonderai's Script

import cv2
import numpy as np

face_cascade = cv2.CascadeClassifier('cascades/haarcascade_frontalface_alt.xml')

face_mask = cv2.imread('images/p2.png')
h_mask, w_mask = face_mask.shape[:2]

if face_cascade.empty():
    raise IOError('Unable to load the face cascade classifier xml file')

cap = cv2.VideoCapture(0)
scaling_factor = 0.5

while True:
    ret, frame = cap.read()
    frame = cv2.resize(frame, None, fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_AREA)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    face_rects = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x,y,w,h) in face_rects:
        if h > 0 and w > 0:
            h, w = int(2.0*h), int(1.7*w)
            y -= int(0.3*h)
            x -= int(0.2*w)

            face_mask_small = cv2.resize(face_mask, (w,h), interpolation=cv2.INTER_AREA)

            # Trimming the face mask when it goes beyond frame boundaries
            frame_height, frame_width = frame.shape[:2]

            trim_top, trim_bottom = 0, 0
            if (y + h > frame_height):
                trim_bottom = (y + h) - frame_height
            if (y < 0):
                trim_top = -y

            trim_left, trim_right = 0, 0
            if (x + w > frame_width):
                trim_right = (x + w) - frame_width
            if (x < 0):
                trim_left = -x

            face_mask_small = face_mask_small[trim_top:(h - trim_bottom),trim_left:(w - trim_right)]

            frame_roi = frame[(y+trim_top):(y+h-trim_bottom), (x+trim_left):(x+w-trim_right)]


            gray_mask = cv2.cvtColor(face_mask_small, cv2.COLOR_BGR2GRAY)
            ret, mask = cv2.threshold(gray_mask, 220, 255, cv2.THRESH_BINARY_INV)
            mask_inv = cv2.bitwise_not(mask)
            print("mask_small",face_mask_small.shape)
            print("mask_roi",frame_roi.shape)


            masked_frame = cv2.bitwise_and(frame_roi, frame_roi, mask=mask_inv)

            masked_face = cv2.bitwise_and(face_mask_small, face_mask_small, mask=mask)

            frame_roi[:,:] = cv2.add(masked_face, masked_frame)


    #cv2.namedWindow("window", cv2.WND_PROP_FULLSCREEN)
    #cv2.setWindowProperty("window",cv2.WND_PROP_FULLSCREEN, cv2.cv.CV_WINDOW_FULLSCREEN)
    cv2.imshow('Face Detector', frame)

    c = cv2.waitKey(1)
    if c == 27:
        break

cap.release()
cv2.destroyAllWindows()