#!/usr/bin/etc python

import cv2
import numpy as np
import pytesseract
from  PIL import Image

class Recognition:
     def ExtractNumber(self):
          Number='testimg3.jpg' 
          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)
          cnts,contours,hierarchy  = cv2.findContours(canny, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

          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)

AttributeError: 'NoneType' object has no attribute 'copy' 이런 오류문구가 뜨네요 ㅠ

!/usr/bin/etc python

import cv2 import numpy as np import pytesseract from PIL import Image

class Recognition: def ExtractNumber(self): Number='testimg3.jpg' 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) cnts,contours,hierarchy = cv2.findContours(canny, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

      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)

!/usr/bin/etc python

import cv2 import numpy as np import pytesseract from PIL import Image

class Recognition: def ExtractNumber(self): Number='testimg3.jpg' 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) cnts,contours,hierarchy = cv2.findContours(canny, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

      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)

AttributeError: 'NoneType' object has no attribute 'copy' 이런 오류문구가 뜨네요 ㅠ