carspeeddetect.py

import cv2
import time
cap = cv2.VideoCapture('traffic.mp4')  #Path to footage
car_cascade = cv2.CascadeClassifier('cars.xml')  #Path to cars.xml


#Coordinates of polygon in frame::: [[x1,y1],[x2,y2],[x3,y3],[x4,y4]]
coord=[[637,352],[904,352],[631,512],[952,512]]

#Distance between two horizontal lines in (meter)
dist = 3

while True:
    ret, img = cap.read()
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    cars=car_cascade.detectMultiScale(gray,1.8,2)

    for (x,y,w,h) in cars:
        cv2.rectangle(img,(x,y),(x+w,y+h),(225,0,0),2)


    cv2.line(img, (coord[0][0],coord[0][1]),(coord[1][0],coord[1][1]),(0,0,255),2)   #First horizontal line
    cv2.line(img, (coord[0][0],coord[0][1]), (coord[2][0],coord[2][1]), (0, 0, 255), 2) #Vertical left line
    cv2.line(img, (coord[2][0],coord[2][1]), (coord[3][0], coord[3][1]), (0, 0, 255), 2) #Second horizontal line
    cv2.line(img, (coord[1][0],coord[1][1]), (coord[3][0], coord[3][1]), (0, 0, 255), 2) #Vertical right line
    for (x, y, w, h) in cars:
        if(x>=coord[0][0] and y==coord[0][1]):
            cv2.line(img, (coord[0][0], coord[0][1]), (coord[1][0], coord[1][1]), (0, 255,0), 2) #Changes line color to green
            tim1= time.time() #Initial time
            print("Car Entered.")

        if (x>=coord[2][0] and y==coord[2][1]):
            cv2.line(img, (coord[2][0],coord[2][1]), (coord[3][0], coord[3][1]), (0, 0, 255), 2) #Changes line color to green
            tim2 = time.time() #Final time
            print("Car Left.")
            #We know that distance is 3m
            print("Speed in (m/s) is:", dist/((tim2-tim1)))

    cv2.imshow('img',img) #Shows the frame



    if cv2.waitKey(20) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()