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)

# 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)

result = cv2.VideoWriter('output.mp4',cv2.VideoWriter_fourcc(*'MP4V'),15,size)
# 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()