OpenCV 3 Computer Vision with Python Cookbook

How to do it

You need to complete the following steps:

1. Import the necessary modules:

import cv2import numpy as np

2. Define a function that opens a video file and applies a few background subtraction algorithms to each frame:

def split_image_fgbg(subtractor, open_sz=(0,0), close_sz=(0,0), show_bg=False, show_shdw=False):    kernel_open = kernel_close = None        if all(i > 0 for i in open_sz):        kernel_open = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, open_sz)        if all(i > 0 for i in close_sz):        kernel_close = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, close_sz)    cap = cv2.VideoCapture('../data/traffic.mp4')    while True:        status_cap, frame = cap.read()        if not status_cap:            break                frame = cv2.resize(frame, None, fx=0.5, fy=0.5)         fgmask = subtractor.apply(frame) ...