Project 9

# OpenCV Python program to detect cars in video frame
# import libraries of python OpenCV 
import cv2


# capture frames from a video
cap = cv2.VideoCapture('traffic.mp4')
  
# Trained XML classifiers describes some features of some object we want to detect
car_cascade = cv2.CascadeClassifier('cars.xml')
frame_width = int(cap.get(3))
frame_height = int(cap.get(4))
size = (frame_width,frame_height)
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))


# loop runs if capturing has been initialized.
while True:
    # reads frames from a video
    ret, frames = cap.read()
    if frames is None:
        break
      
    # 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, 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
cap.release()
cv2.destroyAllWindows()