Vehicles_detection.py

# OpenCV Python program to detect cars in video frame
# import libraries of python OpenCV 

import numpy
import imutils
import argparse
import cv2

 
# capture frames from a video
cap = cv2.VideoCapture('video-1.mov')
#'8-00-51--8-01-01.mp4'
fps = int(cap.get(cv2.CAP_PROP_FPS))
print(fps)
# Trained XML classifiers describes some features of some object we want to detect
car_cascade = cv2.CascadeClassifier('cars.xml')
 
# loop runs if capturing has been initialized.
while(True):
    # reads frames from a video
    ret, frames = cap.read()
    if(ret == False):
        print("okay")
    if ret == True:    
        # convert to gray scale of each frames
        gray = cv2.cvtColor(frames, cv2.COLOR_BGR2GRAY)
        # Detects cars of different sizes in the input image
        cars = car_cascade.detectMultiScale(gray,2,1)#1.1,1
     
        # To draw a rectangle in each cars
        for (x,y,w,h) in cars:
            cv2.rectangle(frames,(x,y),(x+w,y+h),(0,0,255),2)
         
       # Display frames in a window 
        cv2.imshow('video2', frames)
     
       # Wait for Esc key to stop
        if cv2.waitKey(33) == 27:
            break
 
# De-allocate any associated memory usage
cv2.destroyAllWindows()