Live Car Detection App in 7 Minutes | Computer Vision | OpenCV
In this tutorial I have touched you, how to create Live Car Detection App in only 7 Minutes. Its computer vision Artificial Intelligence project and I used OpenCV Python Library and Cascade Classifier.

Live Car Detection App Project
import cv2 #import time # Load the Cascade Classifier car_cascade = cv2.CascadeClassifier("haarcascade_car.xml") #startt web cam cap = cv2.VideoCapture('videos/Traffic - 20581.mp4') while True: #time.sleep(0.2) #read image from webcam respose, color_img = cap.read() if respose == False: break # Convert to grayscale gray_img = cv2.cvtColor(color_img, cv2.COLOR_BGR2GRAY) # Detect the faces faces = car_cascade.detectMultiScale(gray_img, 1.1, 1) #display rectrangle i=0 for (x, y, w, h) in faces: if i%2==0: cv2.rectangle(color_img, (x, y), (x+w, y+h), (0, 0, 255), 2) i +=1 else: cv2.rectangle(color_img, (x, y), (x+w, y+h), (0, 255, 0), 2) i +=1 # display image cv2.imshow('img', color_img) if cv2.waitKey(1) & 0xFF == ord('q'): break # Release the VideoCapture object cap.release() cv2.destroyAllWindows()