Real-time Vehicle Detection using OpenCV Python with Source Code

The Real-Time Car Detection OpenCV Python was developed using Python OpenCV, Vehicle detection is one of the widely used features by companies and organizations these days. This technology uses computer vision to detect different types of vehicles in a video or real-time via a camera. It

In this, we will learn how to build a car tracking system in python for both recorded and live cam streamed videos. To start executing Real-Time Car Detection OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm on your computer.

Installed Libraries

import numpy as np
import cv2

Complete Source Code

import numpy as np
import cv2

cascade_src = 'cars.xml'
# video = 'data/Cars_On_Highway.mp4'
video = 'data/video1.avi'
# video = 'data/video2.avi'


def detectCars(filename):
  rectangles = []
  cascade = cv2.CascadeClassifier(cascade_src)

  vc = cv2.VideoCapture(filename)

  if vc.isOpened():
      rval , frame = vc.read()
  else:
      rval = False


  while rval:
    rval, frame = vc.read()
    frameHeight, frameWidth, fdepth = frame.shape

    # Resize
    frame = cv2.resize(frame, ( 600,  400 ))
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # haar detection.
    cars = cascade.detectMultiScale(gray, 1.3, 3)


    for (x, y, w, h) in cars:
      cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 2)


    # show result
    cv2.imshow("Result",frame)

    if cv2.waitKey(33) == ord('q'):
      break

  vc.release()


detectCars(video)

Output

Download Code Files

Happy Coding !!!

#python #opencv