import cv2
frameWidth = 640 frameHeight = 480 nPlateCascade = cv2.CascadeClassifier("Resources/haarcascade_russian_plate_number.xml") minArea = 200 color = (255,0,255)
cap = cv2.VideoCapture("Resources/video12.mp4")
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) numberPlates = nPlateCascade.detectMultiScale(imgGray, 1.1, 10) for (x, y, w, h) in numberPlates: area = w*h 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("Resources/Scanned/NoPlate_"+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_DUPLEX,
2,(0,0,255),2)
cv2.imshow("Result",img)
cv2.waitKey(500)
count +=1