<reponame>PrabhavD/Number_Plate_Detector
import cv2
import numpy as np

####################################
frameWidth = 640
frameHeight = 480
nPlateCascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_russian_plate_number.xml')
minArea = 500
color = (255,0,255)
####################################

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

while True:
    success, img = cap.read()
    imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    number_plates = nPlateCascade.detectMultiScale(imgGray, 1.1, 4)
    for(x, y, w, h) in number_plates:
        area = h * w
        if area > minArea:
            cv2.rectangle(img, (x,y), (x+w, y+h), (255,0,255), 2)
            cv2.putText(img, "Number Plate", (x,y-5), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, color, 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("venv/Scanned/NumPlate_"+str(count)+".jpg", imgROI)
        cv2.rectangle(img, (0,200), (640,300), (0,255,0), cv2.FILLED)
        cv2.putText(img, "Scan Saved", (150,265), cv2.FONT_HERSHEY_COMPLEX, 2, (0,0,255), 2)
        cv2.imshow("Result", img)
        cv2.waitKey(500)
        count += 1
    elif cv2.waitKey(1) & 0xFF == ord('q'):
        cap.release()
        cv2.destroyAllWindows()
        break

