car_detection.py

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

# capture frames from a video
# cap = cv2.VideoCapture('data/sample_video.mp4')
cap = cv2.VideoCapture('data/it_1.mp4')

# Trained XML classifiers describes some features of some object we want to detect
car_cascade = cv2.CascadeClassifier('data/car_cascades.xml')

# loop runs if capturing has been initialized.
while True:
    # reads frames from a video
    ret, frames = cap.read()
    # 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('Car Detection', frames)
    # Wait for Enter key to stop
    if cv2.waitKey(33) == 13:
        break

cv2.destroyAllWindows()