number_plate.py

import cv2

harcascade = "model/haarcascade_russian_plate_number.xml"

cap= cv2.VideoCapture(0)

cap.set(3, 640) #width
cap.set(4, 480) #height

min_area = 500
count=0

while True:
    success, img = cap.read()
    
    plate_cascade = cv2.CascadeClassifier(harcascade)
    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    plates = plate_cascade.detectMultiScale(img_gray, 1.1, 4)
    
    for (x, y, w,h) in plates:
        area = w * h 
        
        if area > min_area:
            cv2.rectangle(img, (x,y), (x+w, y+h), (0,255,0), 2) #(0,255,0)is RGB(red,green, blue)
            cv2.putText(img, "Number Plate", (x,y-5), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (255, 0, 255), 2) #txtfont, skill, color, 2=thcknss of txt
            
            img_roi = img[y : y+h, x:x+w]  #to crop only no.plate prtn         #roi(region of interest)
            cv2.imshow("Roi", img_roi)
        
    cv2.imshow("Result", img)
    
    if cv2.waitKey(1) & 0xFF == ord('s'):
        cv2.imwrite("plates/scanned_img_" + str(count) + ".jpg", img_roi)
        cv2.rectangle(img, (0,200), (640,300), (0,255,0), cv2.FILLED)
        cv2.putText(img, "Plate Saved", (150, 265), cv2.FONT_HERSHEY_COMPLEX_SMALL, 2, (0, 0, 255), 2)
        cv2.imshow("Results",img)
        cv2.waitKey(500)
        count += 1