laugh.py

import cv2
import numpy as np
import datetime
import time

cap = cv2.VideoCapture(2)
cascade_path = "path/to/haarcascade_frontalface_alt.xml"
cascade = cv2.CascadeClassifier(cascade_path)

index = 0

img_list = []
img_size = 700
image_number = 45

## microseconds
interval = 70000
## seconds
actual_interval = 0

# Load image
for i in range(0,image_number):
    src = "src/laugh" + str(i).zfill(2) + ".png"
    img = cv2.imread(src,-1)
    rate = img.shape[0] / img.shape[1]
    img = cv2.resize(img,(img_size,int(img_size*rate)))
    img_list.append(img)


while(True):
    start = datetime.datetime.now()

    # Capture frame-by-frame
    ret, frame = cap.read()

    # Detect face
    facerect = cascade.detectMultiScale(frame, scaleFactor=1.1, minNeighbors=2, minSize=(250,250))

    # Prepare image
    img = img_list[index]
    width, height = img.shape[0:2]

    # Extract α channel
    mask = img[:,:,3]
    mask = cv2.cvtColor(mask,cv2.COLOR_GRAY2BGR)
    img = img[:,:,:3]

    # Image composition
    if len(facerect) > 0:
        for rect in facerect:
            x = int((rect[1] + rect[3] / 2) - (width / 2))
            y = int((rect[0] + rect[2] / 2) - (height / 2))

            try:
                frame[x:x+width,y:y+height] = np.uint8(frame[x:x+width,y:y+height] * (1 - mask / 255.0))
                frame[x:x+width,y:y+height] = frame[x:x+width,y:y+height] + np.uint8(img *  (mask / 255.0))
            except:
                pass

    # Display the result frame
    cv2.imshow('laugh',frame)

    # Increment index
    index = (index + 1) % image_number

    # Quit when 'q' key pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

    # Adjust fps
    spend_time = datetime.datetime.now() - start
    actual_interval = (interval - spend_time.microseconds) / 1000000
    if actual_interval > 0 :
        time.sleep(actual_interval)

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()