Number_plate_detection.py

import cv2
import numpy as np

frameWidth = 640    #Frame Width
franeHeight = 480   # Frame Height

plateCascade = cv2.CascadeClassifier("Sentinel_number_plate.xml")
minArea = 500

cap =cv2.VideoCapture(0)
cap.set(3,frameWidth)
cap.set(4,franeHeight)
cap.set(10,150)
count = 0

while True:
    success , img  = cap.read()

    imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    numberPlates = plateCascade .detectMultiScale(imgGray, 1.1, 4)

    for (x, y, w, h) in numberPlates:
        area = w*h
        if area > minArea:
            cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
            cv2.putText(img,"NumberPlate",(x,y-5),cv2.FONT_HERSHEY_COMPLEX,1,(0,0,255),2)
            imgRoi = img[y:y+h,x:x+w]
            cv2.imshow("ROI",imgRoi)
    cv2.imshow("Result",img)
    if cv2.waitKey(1) & 0xFF ==ord('s'):
        cv2.imwrite("Images"+str(count)+".jpg",imgRoi)
        cv2.rectangle(img,(0,200),(640,300),(0,255,0),cv2.FILLED)
        cv2.putText(img,"Saved Successfully",(15,265),cv2.FONT_HERSHEY_DUPLEX,2,(255, 214, 51),3)
        cv2.imshow("Result",img)
        cv2.waitKey(500)
        count+=1