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car_detection.py
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#import libraries of python opencv
import cv2
import numpy as np
#create VideoCapture object and read from video file
cap = cv2.VideoCapture('cars.mp4')
#use trained cars XML classifiers
car_cascade = cv2.CascadeClassifier('cars.xml')
#read until video is completed
while True:
#capture frame by frame
ret, frame = cap.read()
#convert video into gray scale of each frames
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#detect cars in the video
cars = car_cascade.detectMultiScale(gray, 1.1, 3)
#to draw arectangle in each cars
for (x,y,w,h) in cars:
cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
#display the resulting frame
cv2.imshow('video', frame)
#press Q on keyboard to exit
if cv2.waitKey(25) & 0xFF == ord('q'):
break
#release the videocapture object
cap.release()
#close all the frames
cv2.destroyAllWindows()