import cv2

import numpy as np

import pytesseract

from PIL import Image

class Recognition:

def ExtractNumber(self):

Number='/home/boramPi/Desktop/python/testimg3.jpg' # 파일 경로 수정

img=cv2.imread(Number,cv2.IMREAD_COLOR)

copy_img=img.copy()

img2=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

cv2.imwrite('gray.jpg',img2)

blur = cv2.GaussianBlur(img2,(3,3),0)

cv2.imwrite('blur.jpg',blur)

canny=cv2.Canny(blur,100,200)

cv2.imwrite('canny.jpg',canny)

contours, hierarchy = cv2.findContours(canny, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) # 반환값 수정

box1=[]

f_count=0

select=0

plate_width=0

for i in range(len(contours)):

cnt=contours[i]

area = cv2.contourArea(cnt)

x,y,w,h = cv2.boundingRect(cnt)

rect_area=w*h #area size

aspect_ratio = float(w)/h # ratio = width/height

if (aspect_ratio>=0.2)and(aspect_ratio<=1.0)and(rect_area>=100)and(rect_area<=700):

cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),1)

box1.append(cv2.boundingRect(cnt))

for i in range(len(box1)): ##Buble Sort on python

for j in range(len(box1)-(i+1)):

if box1[j][0]>box1[j+1][0]:

temp=box1[j]

box1[j]=box1[j+1]

box1[j+1]=temp

#to find number plate measureing length between rectangles

for m in range(len(box1)):

count=0

for n in range(m+1,(len(box1)-1)):

delta_x=abs(box1[n+1][0]-box1[m][0])

if delta_x > 150:

break

delta_y =abs(box1[n+1][1]-box1[m][1])

if delta_x ==0:

delta_x=1

if delta_y ==0:

delta_y=1

gradient =float(delta_y) /float(delta_x)

if gradient<0.25:

count=count+1

#measure number plate size

if count > f_count:

select = m

f_count = count;

plate_width=delta_x

cv2.imwrite('snake.jpg',img)

number_plate=copy_img[box1[select][1]-10:box1[select][3]+box1[select][1]+20,box1[select][0]-10:140+box1[select][0]]

resize_plate=cv2.resize(number_plate,None,fx=1.8,fy=1.8,interpolation=cv2.INTER_CUBIC+cv2.INTER_LINEAR)

plate_gray=cv2.cvtColor(resize_plate,cv2.COLOR_BGR2GRAY)

ret,th_plate = cv2.threshold(plate_gray,150,255,cv2.THRESH_BINARY)

cv2.imwrite('plate_th.jpg',th_plate)

kernel = np.ones((3,3),np.uint8)

er_plate = cv2.erode(th_plate,kernel,iterations=1)

er_invplate = er_plate

cv2.imwrite('er_plate.jpg',er_invplate)

result = pytesseract.image_to_string(Image.open('er_plate.jpg'), lang='kor')

return(result.replace(" ",""))

recogtest=Recognition()

result=recogtest.ExtractNumber()

print(result)