OPTİK KOD OKUYUCU
Optik kod için 3 farklı form vardır hepsini github içinde bulabilirsiniz.
İstediğiniz formu istediğiniz şekilde kullanabilirsiniz.
Eğer bu konu ile ilgili bir eğitim isterseniz https://bionluk.com/bknproduct adresinden ulaşabilirsiniz.
KOD
"""
LGS
"""
import json
from imutils.perspective import four_point_transform
from imutils import contours
import numpy as np
import argparse
import imutils
import cv2
import utils
path = "ornekler/sorun2.jpeg"
heightImg = 700
widthImg = 700
try:
img= cv2.imread(path)
#hazırlık ^^^^^^^^^^^^
img= cv2.resize(img,(widthImg,heightImg))
imgContours = img.copy()
imgBiggestContours = img.copy()
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray,(5,5),1)
imgCanny = cv2.Canny(imgBlur,10,50)
contours, hierarchy = cv2.findContours(imgCanny,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
cv2.drawContours(imgContours,contours,-1,(0,255,0),10)
rectCon= utils.rectContour(contours)
#cv2.imshow("gosterme paper", imgContours)
#cv2.waitKey(0)
#ad-soyad kısmı
biggestContour_1 = utils.getCornerPoints(rectCon[0])
#sosyal kısmı
biggestContour_2 = utils.getCornerPoints(rectCon[1])
#fen kısmı
biggestContour_3=utils.getCornerPoints(rectCon[2])
#matematik
biggestContour_4=utils.getCornerPoints(rectCon[3])
#Türkçe kısmı
biggestContour_5=utils.getCornerPoints(rectCon[4])
#Kurum kodu
biggestContour_6=utils.getCornerPoints(rectCon[5])
#Sınav Kodu
biggestContour_7=utils.getCornerPoints(rectCon[6])
#ögr no
biggestContour_8=utils.getCornerPoints(rectCon[7])
#gereksiz
biggestContour_9=utils.getCornerPoints(rectCon[8])
#Kitapçık
#biggestContour_10=utils.getCornerPoints(rectCon[9])
##print("Türkçe:%s \n sosyal:%s \n matematik:%s \n fen:%s \n"%(biggestContour_5,biggestContour_2,biggestContour_4,biggestContour_3))
##print(len(biggestContour))
##print(biggestContour)
##print(gradePoints)
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(0,255,0),20)
cv2.drawContours(imgBiggestContours,biggestContour_2,-1,(255,200,0),20)
cv2.drawContours(imgBiggestContours,biggestContour_3,-1,(100,255,0),20)
cv2.drawContours(imgBiggestContours,biggestContour_4,-1,(255,0,59),20)
cv2.drawContours(imgBiggestContours,biggestContour_5,-1,(45,255,79),20)
cv2.drawContours(imgBiggestContours,biggestContour_6,-1,(255,99,67),20)
cv2.drawContours(imgBiggestContours,biggestContour_7,-1,(89,255,98),20)
cv2.drawContours(imgBiggestContours,biggestContour_8,-1,(0,255,0),20)
cv2.drawContours(imgBiggestContours,biggestContour_9,-1,(255,235,99),20)
#cv2.drawContours(imgBiggestContours,biggestContour_10,-1,(0,255,0),20)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
except:
imgBiggestContours = img.copy()
biggestContour_1 = utils.getCornerPoints(rectCon[0])
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(0,255,0),20)
biggestContour=utils.reorder(biggestContour_1)
##cv2.imshow("gosterme paper", imgBiggestContours)
##cv2.waitKey(0)
heightImg = 1080
widthImg = 720
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[0,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
##cv2.imshow("cropped", imgWarpColored)
##cv2.waitKey(0)
img= imgWarpColored
#hazırlık ^^^^^^^^^^^^
img= cv2.resize(img,(widthImg,heightImg))
imgContours = img.copy()
imgBiggestContours = img.copy()
imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray,(5,5),1)
imgCanny = cv2.Canny(imgBlur,10,50)
contours, hierarchy = cv2.findContours(imgCanny,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
cv2.drawContours(imgContours,contours,-1,(0,255,0),10)
rectCon= utils.rectContour(contours)
##cv2.imshow("gosterme paper", imgContours)
##cv2.waitKey(0)
#ad-soyad kısmı
biggestContour_1 = utils.getCornerPoints(rectCon[0])
#sosyal kısmı
biggestContour_2 = utils.getCornerPoints(rectCon[1])
#fen kısmı
biggestContour_3=utils.getCornerPoints(rectCon[2])
#matematik
biggestContour_4=utils.getCornerPoints(rectCon[3])
#Türkçe kısmı
biggestContour_5=utils.getCornerPoints(rectCon[4])
#Kurum kodu
biggestContour_6=utils.getCornerPoints(rectCon[5])
#Sınav Kodu
biggestContour_7=utils.getCornerPoints(rectCon[6])
#ögr no
biggestContour_8=utils.getCornerPoints(rectCon[7])
#gereksiz
biggestContour_9=utils.getCornerPoints(rectCon[8])
#Kitapçık
#biggestContour_10=utils.getCornerPoints(rectCon[9])
##print(len(biggestContour))
##print(biggestContour)
##print(gradePoints)
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(0,255,0),20)
cv2.drawContours(imgBiggestContours,biggestContour_2,-1,(255,200,0),20)
cv2.drawContours(imgBiggestContours,biggestContour_3,-1,(100,255,0),20)
cv2.drawContours(imgBiggestContours,biggestContour_4,-1,(255,0,59),20)
cv2.drawContours(imgBiggestContours,biggestContour_5,-1,(45,255,79),20)
cv2.drawContours(imgBiggestContours,biggestContour_6,-1,(255,99,67),20)
cv2.drawContours(imgBiggestContours,biggestContour_7,-1,(89,255,98),20)
cv2.drawContours(imgBiggestContours,biggestContour_8,-1,(0,255,0),20)
cv2.drawContours(imgBiggestContours,biggestContour_9,-1,(255,235,99),20)
#cv2.drawContours(imgBiggestContours,biggestContour_10,-1,(0,255,0),20)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
"""
Sıralama hatası çözümü
"""
#print("Türkçe:%s \n inkılap:%s \n din:%s \n yabancı dil:%s \n mat:%s \n fen:%s \n ogr:%s \n"%(biggestContour_1,biggestContour_2,biggestContour_3,biggestContour_4,biggestContour_5,biggestContour_6,biggestContour_7))
siralama=[]
sag_siralama=[]
if biggestContour_1[0][0][1] < 300:
siralama.append(biggestContour_1[0][0][0])
if biggestContour_2[0][0][1] < 300:
siralama.append(biggestContour_2[0][0][0])
if biggestContour_3[0][0][1] < 300:
siralama.append(biggestContour_3[0][0][0])
if biggestContour_4[0][0][1] < 300:
siralama.append(biggestContour_4[0][0][0])
if biggestContour_5[0][0][1] < 300:
siralama.append(biggestContour_5[0][0][0])
if biggestContour_6[0][0][1] < 300:
siralama.append(biggestContour_6[0][0][0])
if biggestContour_7[0][0][1] < 300:
siralama.append(biggestContour_7[0][0][0])
if biggestContour_8[0][0][1] < 300:
siralama.append(biggestContour_8[0][0][0])
if biggestContour_9[0][0][1] < 300:
siralama.append(biggestContour_9[0][0][0])
if biggestContour_1[0][0][1] > 300:
sag_siralama.append(biggestContour_1[0][0][0])
if biggestContour_2[0][0][1] > 300:
sag_siralama.append(biggestContour_2[0][0][0])
if biggestContour_3[0][0][1] > 300:
sag_siralama.append(biggestContour_3[0][0][0])
if biggestContour_4[0][0][1] > 300:
sag_siralama.append(biggestContour_4[0][0][0])
if biggestContour_5[0][0][1] > 300:
sag_siralama.append(biggestContour_5[0][0][0])
if biggestContour_6[0][0][1] > 300:
sag_siralama.append(biggestContour_6[0][0][0])
if biggestContour_7[0][0][1] > 300:
sag_siralama.append(biggestContour_7[0][0][0])
if biggestContour_8[0][0][1] > 300:
sag_siralama.append(biggestContour_8[0][0][0])
if biggestContour_9[0][0][1] > 300:
sag_siralama.append(biggestContour_9[0][0][0])
siralama.sort()
sag_siralama.sort()
### 0000000 ######
if sag_siralama[0]==biggestContour_1[0][0][0]:
ogr_no=biggestContour_1
elif sag_siralama[0]==biggestContour_2[0][0][0]:
ogr_no=biggestContour_2
elif sag_siralama[0]==biggestContour_3[0][0][0]:
ogr_no=biggestContour_3
elif sag_siralama[0]==biggestContour_4[0][0][0]:
ogr_no=biggestContour_4
elif sag_siralama[0]==biggestContour_5[0][0][0]:
ogr_no=biggestContour_5
elif sag_siralama[0] == biggestContour_6[0][0][0]:
ogr_no=biggestContour_6
elif sag_siralama[0] == biggestContour_7[0][0][0]:
ogr_no=biggestContour_7
elif sag_siralama[0]==biggestContour_8[0][0][0]:
ogr_no=biggestContour_8
elif sag_siralama[0]==biggestContour_9[0][0][0]:
ogr_no=biggestContour_9
###### 111111 #######
if sag_siralama[1]==biggestContour_1[0][0][0]:
kurum_kodu=biggestContour_1
elif sag_siralama[1]==biggestContour_2[0][0][0]:
kurum_kodu=biggestContour_2
elif sag_siralama[1]==biggestContour_3[0][0][0]:
kurum_kodu=biggestContour_3
elif sag_siralama[1]==biggestContour_4[0][0][0]:
kurum_kodu=biggestContour_4
elif sag_siralama[1]==biggestContour_5[0][0][0]:
kurum_kodu=biggestContour_5
elif sag_siralama[1] == biggestContour_6[0][0][0]:
kurum_kodu=biggestContour_6
elif sag_siralama[1] == biggestContour_7[0][0][0]:
kurum_kodu=biggestContour_7
elif sag_siralama[1]==biggestContour_8[0][0][0]:
kurum_kodu=biggestContour_8
elif sag_siralama[1]==biggestContour_9[0][0][0]:
kurum_kodu=biggestContour_9
##### 2222222 ########
if sag_siralama[2]==biggestContour_1[0][0][0]:
sinav_turu=biggestContour_1
elif sag_siralama[2]==biggestContour_2[0][0][0]:
sinav_turu=biggestContour_2
elif sag_siralama[2]==biggestContour_3[0][0][0]:
sinav_turu=biggestContour_3
elif sag_siralama[2]==biggestContour_4[0][0][0]:
sinav_turu=biggestContour_4
elif sag_siralama[2]==biggestContour_5[0][0][0]:
sinav_turu=biggestContour_5
elif sag_siralama[2] == biggestContour_6[0][0][0]:
sinav_turu=biggestContour_6
elif sag_siralama[2] == biggestContour_7[0][0][0]:
sinav_turu=biggestContour_7
elif sag_siralama[2]==biggestContour_8[0][0][0]:
sinav_turu=biggestContour_8
elif sag_siralama[2]==biggestContour_9[0][0][0]:
sinav_turu=biggestContour_9
#### üst kısım #######
"""
#### üst kısım #######
"""
# türkçe
if siralama[0]==biggestContour_1[0][0][0]:
turkce_kisimi=biggestContour_1
elif siralama[0]==biggestContour_2[0][0][0]:
turkce_kisimi=biggestContour_2
elif siralama[0]==biggestContour_3[0][0][0]:
turkce_kisimi=biggestContour_3
elif siralama[0]==biggestContour_4[0][0][0]:
turkce_kisimi=biggestContour_4
elif siralama[0]==biggestContour_5[0][0][0]:
turkce_kisimi=biggestContour_5
elif siralama[0] == biggestContour_6[0][0][0]:
turkce_kisimi=biggestContour_6
elif siralama[0] == biggestContour_7[0][0][0]:
turkce_kisimi=biggestContour_7
elif siralama[0]==biggestContour_8[0][0][0]:
turkce_kisimi=biggestContour_8
elif siralama[0]==biggestContour_9[0][0][0]:
turkce_kisimi=biggestContour_9
# ink tarihi
if siralama[1]==biggestContour_1[0][0][0]:
inkilap_kisimi=biggestContour_1
elif siralama[1]==biggestContour_2[0][0][0]:
inkilap_kisimi=biggestContour_2
elif siralama[1]==biggestContour_3[0][0][0]:
inkilap_kisimi=biggestContour_3
elif siralama[1]==biggestContour_4[0][0][0]:
inkilap_kisimi=biggestContour_4
elif siralama[1]==biggestContour_5[0][0][0]:
inkilap_kisimi=biggestContour_5
elif siralama[1] == biggestContour_6[0][0][0]:
inkilap_kisimi=biggestContour_6
elif siralama[1] == biggestContour_7[0][0][0]:
inkilap_kisimi=biggestContour_7
elif siralama[1]==biggestContour_8[0][0][0]:
inkilap_kisimi=biggestContour_8
elif siralama[1]==biggestContour_9[0][0][0]:
inkilap_kisimi=biggestContour_9
# din
if siralama[2]==biggestContour_1[0][0][0]:
din_kisimi=biggestContour_1
elif siralama[2]==biggestContour_2[0][0][0]:
din_kisimi=biggestContour_2
elif siralama[2]==biggestContour_3[0][0][0]:
din_kisimi=biggestContour_3
elif siralama[2]==biggestContour_4[0][0][0]:
din_kisimi=biggestContour_4
elif siralama[2]==biggestContour_5[0][0][0]:
din_kisimi=biggestContour_5
elif siralama[2] == biggestContour_6[0][0][0]:
din_kisimi=biggestContour_6
elif siralama[2] == biggestContour_7[0][0][0]:
din_kisimi=biggestContour_7
elif siralama[2]==biggestContour_8[0][0][0]:
din_kisimi=biggestContour_8
elif siralama[2]==biggestContour_9[0][0][0]:
din_kisimi=biggestContour_9
# yabanci
if siralama[3]==biggestContour_1[0][0][0]:
yabanci_kisimi=biggestContour_1
elif siralama[3]==biggestContour_2[0][0][0]:
yabanci_kisimi=biggestContour_2
elif siralama[3]==biggestContour_3[0][0][0]:
yabanci_kisimi=biggestContour_3
elif siralama[3]==biggestContour_4[0][0][0]:
yabanci_kisimi=biggestContour_4
elif siralama[3]==biggestContour_5[0][0][0]:
yabanci_kisimi=biggestContour_5
elif siralama[3] == biggestContour_6[0][0][0]:
yabanci_kisimi=biggestContour_6
elif siralama[3] == biggestContour_7[0][0][0]:
yabanci_kisimi=biggestContour_7
elif siralama[3]==biggestContour_8[0][0][0]:
yabanci_kisimi=biggestContour_8
elif siralama[3]==biggestContour_9[0][0][0]:
yabanci_kisimi=biggestContour_9
# mat
if siralama[4]==biggestContour_1[0][0][0]:
mat_kisimi=biggestContour_1
elif siralama[4]==biggestContour_2[0][0][0]:
mat_kisimi=biggestContour_2
elif siralama[4]==biggestContour_3[0][0][0]:
mat_kisimi=biggestContour_3
elif siralama[4]==biggestContour_4[0][0][0]:
mat_kisimi=biggestContour_4
elif siralama[4]==biggestContour_5[0][0][0]:
mat_kisimi=biggestContour_5
elif siralama[4] == biggestContour_6[0][0][0]:
mat_kisimi=biggestContour_6
elif siralama[4] == biggestContour_7[0][0][0]:
mat_kisimi=biggestContour_7
elif siralama[4]==biggestContour_8[0][0][0]:
mat_kisimi=biggestContour_8
elif siralama[4]==biggestContour_9[0][0][0]:
mat_kisimi=biggestContour_9
# fen
if siralama[5]==biggestContour_1[0][0][0]:
fen_kisimi=biggestContour_1
elif siralama[5]==biggestContour_2[0][0][0]:
fen_kisimi=biggestContour_2
elif siralama[5]==biggestContour_3[0][0][0]:
fen_kisimi=biggestContour_3
elif siralama[5]==biggestContour_4[0][0][0]:
fen_kisimi=biggestContour_4
elif siralama[5]==biggestContour_5[0][0][0]:
fen_kisimi=biggestContour_5
elif siralama[5] == biggestContour_6[0][0][0]:
fen_kisimi=biggestContour_6
elif siralama[5] == biggestContour_7[0][0][0]:
fen_kisimi=biggestContour_7
elif siralama[5]==biggestContour_8[0][0][0]:
fen_kisimi=biggestContour_8
elif siralama[5]==biggestContour_9[0][0][0]:
fen_kisimi=biggestContour_9
#### optik okumalara geçelim #####
"""
Türkçe
"""
imgBiggestContours = img.copy()
biggestContour_1=turkce_kisimi
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(255,0,59),20)
biggestContour=utils.reorder(biggestContour_1)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 800
widthImg = 200
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[0,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[17:775, 49:180]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
#cv2.imshow("gosterme", thresh) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
threshd = cv2.resize(thresh, (720, 800))
#cv2.imshow("gosterme", threshd) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
"""
#kontrolcüm
for i in range (1,50):
try:
rows = np.vsplit(threshd,i)
#print(i)
except:
#print("hata")
"""
def splitBoxes(img):
#rows = np.hsplit(threshd,5)
rows = np.vsplit(threshd,20)
###cv2.imshow("split",rows[5])
###cv2.waitKey(0)
boxes =[]
for r in rows:
cols = np.hsplit(r,4)
###cv2.imshow("split",cols[0])
###cv2.waitKey(0)
for box in cols:
boxes.append(box)
###cv2.imshow("split",box)
###cv2.waitKey(0)
return boxes
boxes=splitBoxes(threshd)
#cv2.imshow("test",boxes[0])
#cv2.waitKey(0)
##print(cv2.countNonZero(boxes[0]),cv2.countNonZero(boxes[6]))
#cevap alma
myPixelVal=np.zeros((20,4))
countC=0
countR=0
cvp_sil=[]
for image in boxes:
totalPixels = cv2.countNonZero(image)
cvp_sil.append(totalPixels)
cvp_sil=np.array(cvp_sil)
cvp_sil=cvp_sil.reshape(20,4)
#cvp_sil[27]
myPixelVal=cvp_sil
#TEST
#İLK 1,2,3,4 VB 2. A,B,C,D
#myPixelVal[26][2]
turkce_cvp_anahtari = """{ }"""
turkce_cvp_anahtari_gercek = json.loads(turkce_cvp_anahtari)
cevap_kontrolcu=[]
for x in range (0,20):
arr=myPixelVal[x]
##print("arr",arr)
arr_kont=np.amax(arr)
kontrol_veri=arr_kont
cevap_kontrolcu = arr.tolist()
if kontrol_veri >= 4000:
##print("adanam")
for i in range (0,4):
kontrol=cevap_kontrolcu[i]
##print(kontrol)
i+=1
if kontrol==kontrol_veri:
##print("dogru")
yeri=cevap_kontrolcu.index(kontrol)
if yeri == 0:
gercek_cvp="a"
elif yeri == 1:
gercek_cvp="b"
elif yeri == 2:
gercek_cvp="c"
elif yeri == 3:
gercek_cvp="d"
elif yeri == 4:
gercek_cvp="e"
#print("Türkçe %s sorunun cevabı:%s"%((x+1),gercek_cvp))
turkce_cvp_anahtari_gercek[x+1] = gercek_cvp
"""
ink. tarihi
"""
imgBiggestContours = img.copy()
biggestContour_1=inkilap_kisimi
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(255,0,59),20)
biggestContour=utils.reorder(biggestContour_1)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 800
widthImg = 200
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[0,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[17:775, 49:180]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
#cv2.imshow("gosterme", thresh) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
threshd = cv2.resize(thresh, (720, 800))
#cv2.imshow("gosterme", threshd) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
"""
#kontrolcüm
for i in range (1,50):
try:
rows = np.vsplit(threshd,i)
#print(i)
except:
#print("hata")
"""
def splitBoxes(img):
#rows = np.hsplit(threshd,5)
rows = np.vsplit(threshd,20)
###cv2.imshow("split",rows[5])
###cv2.waitKey(0)
boxes =[]
for r in rows:
cols = np.hsplit(r,4)
###cv2.imshow("split",cols[0])
###cv2.waitKey(0)
for box in cols:
boxes.append(box)
###cv2.imshow("split",box)
###cv2.waitKey(0)
return boxes
boxes=splitBoxes(threshd)
#cv2.imshow("test",boxes[0])
#cv2.waitKey(0)
##print(cv2.countNonZero(boxes[0]),cv2.countNonZero(boxes[6]))
#cevap alma
myPixelVal=np.zeros((20,4))
countC=0
countR=0
cvp_sil=[]
for image in boxes:
totalPixels = cv2.countNonZero(image)
cvp_sil.append(totalPixels)
cvp_sil=np.array(cvp_sil)
cvp_sil=cvp_sil.reshape(20,4)
#cvp_sil[27]
myPixelVal=cvp_sil
#TEST
#İLK 1,2,3,4 VB 2. A,B,C,D
#myPixelVal[26][2]
ink_cvp_anahtari = """{ }"""
ink_cvp_anahtari_gercek = json.loads(ink_cvp_anahtari)
cevap_kontrolcu=[]
for x in range (0,20):
arr=myPixelVal[x]
##print("arr",arr)
arr_kont=np.amax(arr)
kontrol_veri=arr_kont
cevap_kontrolcu = arr.tolist()
if kontrol_veri >= 4000:
##print("adanam")
for i in range (0,4):
kontrol=cevap_kontrolcu[i]
##print(kontrol)
i+=1
if kontrol==kontrol_veri:
##print("dogru")
yeri=cevap_kontrolcu.index(kontrol)
if yeri == 0:
gercek_cvp="a"
elif yeri == 1:
gercek_cvp="b"
elif yeri == 2:
gercek_cvp="c"
elif yeri == 3:
gercek_cvp="d"
elif yeri == 4:
gercek_cvp="e"
#print("inkilap %s sorunun cevabı:%s"%((x+1),gercek_cvp))
ink_cvp_anahtari_gercek[x+1] = gercek_cvp
"""
din kültürü
"""
imgBiggestContours = img.copy()
biggestContour_1=din_kisimi
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(255,0,59),20)
biggestContour=utils.reorder(biggestContour_1)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 800
widthImg = 200
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[0,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[17:775, 49:180]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
#cv2.imshow("gosterme", thresh) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
threshd = cv2.resize(thresh, (720, 800))
#cv2.imshow("gosterme", threshd) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
"""
#kontrolcüm
for i in range (1,50):
try:
rows = np.vsplit(threshd,i)
#print(i)
except:
#print("hata")
"""
def splitBoxes(img):
#rows = np.hsplit(threshd,5)
rows = np.vsplit(threshd,20)
###cv2.imshow("split",rows[5])
###cv2.waitKey(0)
boxes =[]
for r in rows:
cols = np.hsplit(r,4)
###cv2.imshow("split",cols[0])
###cv2.waitKey(0)
for box in cols:
boxes.append(box)
###cv2.imshow("split",box)
###cv2.waitKey(0)
return boxes
boxes=splitBoxes(threshd)
#cv2.imshow("test",boxes[0])
#cv2.waitKey(0)
##print(cv2.countNonZero(boxes[0]),cv2.countNonZero(boxes[6]))
#cevap alma
myPixelVal=np.zeros((20,4))
countC=0
countR=0
cvp_sil=[]
for image in boxes:
totalPixels = cv2.countNonZero(image)
cvp_sil.append(totalPixels)
cvp_sil=np.array(cvp_sil)
cvp_sil=cvp_sil.reshape(20,4)
#cvp_sil[27]
myPixelVal=cvp_sil
#TEST
#İLK 1,2,3,4 VB 2. A,B,C,D
#myPixelVal[26][2]
din_cvp_anahtari = """{ }"""
din_cvp_anahtari_gercek = json.loads(din_cvp_anahtari)
cevap_kontrolcu=[]
for x in range (0,20):
arr=myPixelVal[x]
##print("arr",arr)
arr_kont=np.amax(arr)
kontrol_veri=arr_kont
cevap_kontrolcu = arr.tolist()
if kontrol_veri >= 4000:
##print("adanam")
for i in range (0,4):
kontrol=cevap_kontrolcu[i]
##print(kontrol)
i+=1
if kontrol==kontrol_veri:
##print("dogru")
yeri=cevap_kontrolcu.index(kontrol)
if yeri == 0:
gercek_cvp="a"
elif yeri == 1:
gercek_cvp="b"
elif yeri == 2:
gercek_cvp="c"
elif yeri == 3:
gercek_cvp="d"
elif yeri == 4:
gercek_cvp="e"
#print("din %s sorunun cevabı:%s"%((x+1),gercek_cvp))
din_cvp_anahtari_gercek[x+1] = gercek_cvp
"""
Yabancı dil
"""
imgBiggestContours = img.copy()
biggestContour_1=yabanci_kisimi
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(255,0,59),20)
biggestContour=utils.reorder(biggestContour_1)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 800
widthImg = 200
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[0,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[17:775, 49:180]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
#cv2.imshow("gosterme", thresh) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
threshd = cv2.resize(thresh, (720, 800))
#cv2.imshow("gosterme", threshd) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
"""
#kontrolcüm
for i in range (1,50):
try:
rows = np.vsplit(threshd,i)
#print(i)
except:
#print("hata")
"""
def splitBoxes(img):
#rows = np.hsplit(threshd,5)
rows = np.vsplit(threshd,20)
###cv2.imshow("split",rows[5])
###cv2.waitKey(0)
boxes =[]
for r in rows:
cols = np.hsplit(r,4)
###cv2.imshow("split",cols[0])
###cv2.waitKey(0)
for box in cols:
boxes.append(box)
###cv2.imshow("split",box)
###cv2.waitKey(0)
return boxes
boxes=splitBoxes(threshd)
#cv2.imshow("test",boxes[0])
#cv2.waitKey(0)
##print(cv2.countNonZero(boxes[0]),cv2.countNonZero(boxes[6]))
#cevap alma
myPixelVal=np.zeros((20,4))
countC=0
countR=0
cvp_sil=[]
for image in boxes:
totalPixels = cv2.countNonZero(image)
cvp_sil.append(totalPixels)
cvp_sil=np.array(cvp_sil)
cvp_sil=cvp_sil.reshape(20,4)
#cvp_sil[27]
myPixelVal=cvp_sil
#TEST
#İLK 1,2,3,4 VB 2. A,B,C,D
#myPixelVal[26][2]
yabanci_cvp_anahtari = """{ }"""
yabanci_cvp_anahtari_gercek = json.loads(yabanci_cvp_anahtari)
cevap_kontrolcu=[]
for x in range (0,20):
arr=myPixelVal[x]
##print("arr",arr)
arr_kont=np.amax(arr)
kontrol_veri=arr_kont
cevap_kontrolcu = arr.tolist()
if kontrol_veri >= 4000:
##print("adanam")
for i in range (0,4):
kontrol=cevap_kontrolcu[i]
##print(kontrol)
i+=1
if kontrol==kontrol_veri:
##print("dogru")
yeri=cevap_kontrolcu.index(kontrol)
if yeri == 0:
gercek_cvp="a"
elif yeri == 1:
gercek_cvp="b"
elif yeri == 2:
gercek_cvp="c"
elif yeri == 3:
gercek_cvp="d"
elif yeri == 4:
gercek_cvp="e"
#print("yabanci %s sorunun cevabı:%s"%((x+1),gercek_cvp))
yabanci_cvp_anahtari_gercek[x+1] = gercek_cvp
"""
Mat
"""
imgBiggestContours = img.copy()
biggestContour_1=mat_kisimi
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(255,0,59),20)
biggestContour=utils.reorder(biggestContour_1)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 800
widthImg = 200
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[0,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[17:775, 49:180]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
#cv2.imshow("gosterme", thresh) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
threshd = cv2.resize(thresh, (720, 800))
#cv2.imshow("gosterme", threshd) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
"""
#kontrolcüm
for i in range (1,50):
try:
rows = np.vsplit(threshd,i)
#print(i)
except:
#print("hata")
"""
def splitBoxes(img):
#rows = np.hsplit(threshd,5)
rows = np.vsplit(threshd,20)
###cv2.imshow("split",rows[5])
###cv2.waitKey(0)
boxes =[]
for r in rows:
cols = np.hsplit(r,4)
###cv2.imshow("split",cols[0])
###cv2.waitKey(0)
for box in cols:
boxes.append(box)
###cv2.imshow("split",box)
###cv2.waitKey(0)
return boxes
boxes=splitBoxes(threshd)
#cv2.imshow("test",boxes[0])
#cv2.waitKey(0)
##print(cv2.countNonZero(boxes[0]),cv2.countNonZero(boxes[6]))
#cevap alma
myPixelVal=np.zeros((20,4))
countC=0
countR=0
cvp_sil=[]
for image in boxes:
totalPixels = cv2.countNonZero(image)
cvp_sil.append(totalPixels)
cvp_sil=np.array(cvp_sil)
cvp_sil=cvp_sil.reshape(20,4)
#cvp_sil[27]
myPixelVal=cvp_sil
#TEST
#İLK 1,2,3,4 VB 2. A,B,C,D
#myPixelVal[26][2]
mat_cvp_anahtari = """{ }"""
mat_cvp_anahtari_gercek = json.loads(mat_cvp_anahtari)
cevap_kontrolcu=[]
for x in range (0,20):
arr=myPixelVal[x]
##print("arr",arr)
arr_kont=np.amax(arr)
kontrol_veri=arr_kont
cevap_kontrolcu = arr.tolist()
if kontrol_veri >= 4000:
##print("adanam")
for i in range (0,4):
kontrol=cevap_kontrolcu[i]
##print(kontrol)
i+=1
if kontrol==kontrol_veri:
##print("dogru")
yeri=cevap_kontrolcu.index(kontrol)
if yeri == 0:
gercek_cvp="a"
elif yeri == 1:
gercek_cvp="b"
elif yeri == 2:
gercek_cvp="c"
elif yeri == 3:
gercek_cvp="d"
elif yeri == 4:
gercek_cvp="e"
#print("matematik %s sorunun cevabı:%s"%((x+1),gercek_cvp))
mat_cvp_anahtari_gercek[x+1] = gercek_cvp
"""
FEN
"""
imgBiggestContours = img.copy()
biggestContour_1=fen_kisimi
cv2.drawContours(imgBiggestContours,biggestContour_1,-1,(255,0,59),20)
biggestContour=utils.reorder(biggestContour_1)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 800
widthImg = 200
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[0,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[17:775, 49:180]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
#cv2.imshow("gosterme", thresh) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
threshd = cv2.resize(thresh, (720, 800))
#cv2.imshow("gosterme", threshd) # Show image
###cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
"""
#kontrolcüm
for i in range (1,50):
try:
rows = np.vsplit(threshd,i)
#print(i)
except:
#print("hata")
"""
def splitBoxes(img):
#rows = np.hsplit(threshd,5)
rows = np.vsplit(threshd,20)
###cv2.imshow("split",rows[5])
###cv2.waitKey(0)
boxes =[]
for r in rows:
cols = np.hsplit(r,4)
###cv2.imshow("split",cols[0])
###cv2.waitKey(0)
for box in cols:
boxes.append(box)
###cv2.imshow("split",box)
###cv2.waitKey(0)
return boxes
boxes=splitBoxes(threshd)
#cv2.imshow("test",boxes[0])
#cv2.waitKey(0)
##print(cv2.countNonZero(boxes[0]),cv2.countNonZero(boxes[6]))
#cevap alma
myPixelVal=np.zeros((20,4))
countC=0
countR=0
cvp_sil=[]
for image in boxes:
totalPixels = cv2.countNonZero(image)
cvp_sil.append(totalPixels)
cvp_sil=np.array(cvp_sil)
cvp_sil=cvp_sil.reshape(20,4)
#cvp_sil[27]
myPixelVal=cvp_sil
#TEST
#İLK 1,2,3,4 VB 2. A,B,C,D
#myPixelVal[26][2]
fen_cvp_anahtari = """{ }"""
fen_cvp_anahtari_gercek = json.loads(fen_cvp_anahtari)
cevap_kontrolcu=[]
for x in range (0,20):
arr=myPixelVal[x]
##print("arr",arr)
arr_kont=np.amax(arr)
kontrol_veri=arr_kont
cevap_kontrolcu = arr.tolist()
if kontrol_veri >= 4000:
##print("adanam")
for i in range (0,4):
kontrol=cevap_kontrolcu[i]
##print(kontrol)
i+=1
if kontrol==kontrol_veri:
##print("dogru")
yeri=cevap_kontrolcu.index(kontrol)
if yeri == 0:
gercek_cvp="a"
elif yeri == 1:
gercek_cvp="b"
elif yeri == 2:
gercek_cvp="c"
elif yeri == 3:
gercek_cvp="d"
elif yeri == 4:
gercek_cvp="e"
#print("fen %s sorunun cevabı:%s"%((x+1),gercek_cvp))
fen_cvp_anahtari_gercek[x+1] = gercek_cvp
"""
ögr numarası
"""
imgBiggestContours = img.copy()
biggestContour_6=ogr_no
cv2.drawContours(imgBiggestContours,biggestContour_6,-1,(255,99,67),20)
biggestContour=utils.reorder(biggestContour_6)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 860
widthImg = 400
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[10,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
##cv2.imshow("cropped", imgWarpColored)
##cv2.waitKey(0)
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[140:820, 65:370]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 127, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
##cv2.imshow("gosterme", thresh) # Show image
####cv2.imshow("gosterme paper", imgBiggestContours)
##cv2.waitKey(0)
threshd = cv2.resize(thresh, (700, 1000))
###cv2.imshow("gosterme", threshd) # Show image
####cv2.imshow("gosterme paper", imgBiggestContours)
###cv2.waitKey(0)
def splitBoxes(img):
#rows = np.hsplit(threshd,5)
rows = np.vsplit(threshd,10)
####cv2.imshow("split",rows[5])
####cv2.waitKey(0)
boxes =[]
for r in rows:
cols = np.hsplit(r,7)
####cv2.imshow("split",cols[0])
####cv2.waitKey(0)
for box in cols:
boxes.append(box)
####cv2.imshow("split",box)
####cv2.waitKey(0)
return boxes
boxes=splitBoxes(threshd)
####cv2.imshow("test",boxes[6])
####cv2.waitKey(0)
##print(cv2.countNonZero(boxes[14]),cv2.countNonZero(boxes[9]))
#cevap alma
myPixelVal=np.zeros((10,7))
countC=0
countR=0
cvp_sil=[]
for image in boxes:
totalPixels = cv2.countNonZero(image)
cvp_sil.append(totalPixels)
cvp_sil=np.array(cvp_sil)
cvp_sil=cvp_sil.reshape(10,7)
#cvp_sil[27]
myPixelVal=cvp_sil
#TEST
#İLK 1,2,3,4 VB 2. A,B,C,D
#myPixelVal[3][3]
HaydiBakalim=myPixelVal[0][0]
sayac=0
sınav_kodu_buldum=[]
numara_kontrolcu=[]
for deneme in range (0,7):
for x in range(0,10):
arr=myPixelVal[x][deneme]
##print(arr)
#deneme
##print("arr: ",arr)
##print("x",x)
if arr >=4000:
if x==0:
numara_kontrolcu.append(0)
elif x== 1:
numara_kontrolcu.append(1)
elif x== 2:
numara_kontrolcu.append(2)
elif x== 3:
numara_kontrolcu.append(3)
elif x== 4:
numara_kontrolcu.append(4)
elif x== 5:
numara_kontrolcu.append(5)
elif x== 6:
numara_kontrolcu.append(6)
elif x== 7:
numara_kontrolcu.append(7)
elif x== 8:
numara_kontrolcu.append(8)
elif x== 9:
numara_kontrolcu.append(9)
s = numara_kontrolcu
# using list comprehension
ogr_no = ' '.join(map(str, s))
##print(kurum_kodu_no)
ogr_no=ogr_no.replace(" ","")
#sonuç
#print("ogr_no: %s "%ogr_no)
"""
Kurum Kodu
"""
imgBiggestContours = img.copy()
biggestContour_6=kurum_kodu
cv2.drawContours(imgBiggestContours,biggestContour_6,-1,(255,99,67),20)
biggestContour=utils.reorder(biggestContour_6)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 860
widthImg = 400
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[10,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
##cv2.imshow("cropped", imgWarpColored)
##cv2.waitKey(0)
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[140:818, 65:365]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 127, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
##cv2.imshow("gosterme", thresh) # Show image
####cv2.imshow("gosterme paper", imgBiggestContours)
##cv2.waitKey(0)
threshd = cv2.resize(thresh, (700, 1000))
###cv2.imshow("gosterme", threshd) # Show image
####cv2.imshow("gosterme paper", imgBiggestContours)
###cv2.waitKey(0)
def splitBoxes(img):
#rows = np.hsplit(threshd,5)
rows = np.vsplit(threshd,10)
####cv2.imshow("split",rows[5])
####cv2.waitKey(0)
boxes =[]
for r in rows:
cols = np.hsplit(r,7)
####cv2.imshow("split",cols[0])
####cv2.waitKey(0)
for box in cols:
boxes.append(box)
####cv2.imshow("split",box)
####cv2.waitKey(0)
return boxes
boxes=splitBoxes(threshd)
####cv2.imshow("test",boxes[6])
####cv2.waitKey(0)
##print(cv2.countNonZero(boxes[14]),cv2.countNonZero(boxes[9]))
#cevap alma
myPixelVal=np.zeros((10,7))
countC=0
countR=0
cvp_sil=[]
for image in boxes:
totalPixels = cv2.countNonZero(image)
cvp_sil.append(totalPixels)
cvp_sil=np.array(cvp_sil)
cvp_sil=cvp_sil.reshape(10,7)
#cvp_sil[27]
myPixelVal=cvp_sil
#TEST
#İLK 1,2,3,4 VB 2. A,B,C,D
#myPixelVal[3][3]
HaydiBakalim=myPixelVal[0][0]
sayac=0
sınav_kodu_buldum=[]
numara_kontrolcu=[]
for deneme in range (0,7):
for x in range(0,10):
arr=myPixelVal[x][deneme]
##print(arr)
#deneme
##print("arr: ",arr)
##print("x",x)
if arr >=4000:
if x==0:
numara_kontrolcu.append(0)
elif x== 1:
numara_kontrolcu.append(1)
elif x== 2:
numara_kontrolcu.append(2)
elif x== 3:
numara_kontrolcu.append(3)
elif x== 4:
numara_kontrolcu.append(4)
elif x== 5:
numara_kontrolcu.append(5)
elif x== 6:
numara_kontrolcu.append(6)
elif x== 7:
numara_kontrolcu.append(7)
elif x== 8:
numara_kontrolcu.append(8)
elif x== 9:
numara_kontrolcu.append(9)
s = numara_kontrolcu
# using list comprehension
kurum_koddd = ' '.join(map(str, s))
##print(kurum_kodu_no)
kurum_koddd=kurum_koddd.replace(" ","")
#sonuç
#print("ogr_no: %s "%kurum_koddd)
"""
Oturum sınav türü
"""
imgBiggestContours = img.copy()
biggestContour_6=sinav_turu
cv2.drawContours(imgBiggestContours,biggestContour_6,-1,(255,99,67),20)
biggestContour=utils.reorder(biggestContour_6)
#cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
heightImg = 860
widthImg = 400
#imgBiggestContours = cv2.resize(imgBiggestContours, (heightImg, widthImg))
pt1= np.float32(biggestContour)
pt2 = np.float32([[10,0],[widthImg,0],[0,heightImg],[widthImg,heightImg]])
matrix = cv2.getPerspectiveTransform(pt1,pt2)
imgWarpColored= cv2.warpPerspective(img,matrix,(widthImg,heightImg))
##cv2.imshow("cropped", imgWarpColored)
##cv2.waitKey(0)
gray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
crop_img = gray[410:480, 175:220]
#cv2.imshow("cropped", crop_img)
#cv2.waitKey(0)
docCnt = None
#crop_img=four_point_transform(crop_img, docCnt.reshape(4, 2))
thresh = cv2.threshold(crop_img, 127, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
#bu kısımda kesme işlemi yapabilirsin ad ve soyad için
#thresh = cv2.resize(thresh, (199, 1363))
##cv2.imshow("gosterme", thresh) # Show image
####cv2.imshow("gosterme paper", imgBiggestContours)
##cv2.waitKey(0)
threshd = cv2.resize(thresh, (100, 100))
#cv2.imshow("gosterme", threshd) # Show image
####cv2.imshow("gosterme paper", imgBiggestContours)
#cv2.waitKey(0)
# !!!!!!!! >>>
totalPixels = cv2.countNonZero(threshd)
if totalPixels > 3500:
sinav_tur_a="sayisal"
else:
sinav_tur_a="sözel"
"""
Json çıkarma
"""
import json
x = {
"kurum_kodu": kurum_koddd,
"ogr_no": ogr_no,
"turkce": turkce_cvp_anahtari_gercek,
"inkilap": ink_cvp_anahtari_gercek,
"din": din_cvp_anahtari_gercek,
"yabancidil": yabanci_cvp_anahtari_gercek,
"mat": mat_cvp_anahtari_gercek,
"fen": fen_cvp_anahtari_gercek,
"sinav_tur": sinav_tur_a,
}
sonuc_json=(json.dumps(x, ensure_ascii=False).encode('utf8'))
print("!!!!! json çıktı !!!!")
print(sonuc_json.decode())
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 24 13:38:45 2021
@author: yazılım
"""
"""
utils
"""
import cv2
import numpy as np
## TO STACK ALL THE IMAGES IN ONE WINDOW
def stackImages(imgArray,scale,lables=[]):
rows = len(imgArray)
cols = len(imgArray[0])
rowsAvailable = isinstance(imgArray[0], list)
width = imgArray[0][0].shape[1]
height = imgArray[0][0].shape[0]
if rowsAvailable:
for x in range ( 0, rows):
for y in range(0, cols):
imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR)
imageBlank = np.zeros((height, width, 3), np.uint8)
hor = [imageBlank]*rows
hor_con = [imageBlank]*rows
for x in range(0, rows):
hor[x] = np.hstack(imgArray[x])
hor_con[x] = np.concatenate(imgArray[x])
ver = np.vstack(hor)
ver_con = np.concatenate(hor)
else:
for x in range(0, rows):
imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
hor= np.hstack(imgArray)
hor_con= np.concatenate(imgArray)
ver = hor
if len(lables) != 0:
eachImgWidth= int(ver.shape[1] / cols)
eachImgHeight = int(ver.shape[0] / rows)
#print(eachImgHeight)
for d in range(0, rows):
for c in range (0,cols):
cv2.rectangle(ver,(c*eachImgWidth,eachImgHeight*d),(c*eachImgWidth+len(lables[d])*13+27,30+eachImgHeight*d),(255,255,255),cv2.FILLED)
cv2.putText(ver,lables[d],(eachImgWidth*c+10,eachImgHeight*d+20),cv2.FONT_HERSHEY_COMPLEX,0.7,(255,0,255),2)
return ver
def reorder(myPoints):
myPoints = myPoints.reshape((4, 2)) # REMOVE EXTRA BRACKET
#print(myPoints)
myPointsNew = np.zeros((4, 1, 2), np.int32) # NEW MATRIX WITH ARRANGED POINTS
add = myPoints.sum(1)
#print(add)
#print(np.argmax(add))
myPointsNew[0] = myPoints[np.argmin(add)] #[0,0]
myPointsNew[3] =myPoints[np.argmax(add)] #[w,h]
diff = np.diff(myPoints, axis=1)
myPointsNew[1] =myPoints[np.argmin(diff)] #[w,0]
myPointsNew[2] = myPoints[np.argmax(diff)] #[h,0]
#print(diff)
return myPointsNew
def rectContour(contours):
rectCon = []
max_area = 0
for i in contours:
area = cv2.contourArea(i)
#print(area)
if area > 50:
peri = cv2.arcLength(i, True)
approx = cv2.approxPolyDP(i, 0.02 * peri, True)
#print("koşeler:",len(approx))
if len(approx) == 4:
rectCon.append(i)
#print(rectCon)
rectCon = sorted(rectCon, key=cv2.contourArea,reverse=True)
#print(len(rectCon))
return rectCon
def getCornerPoints(cont):
peri = cv2.arcLength(cont, True) # LENGTH OF CONTOUR
approx = cv2.approxPolyDP(cont, 0.02 * peri, True) # APPROXIMATE THE POLY TO GET CORNER POINTS
return approx
def splitBoxes(img):
rows = np.vsplit(img,30)
cv2.imshow("split",rows[0])
"""
boxes=[]
for r in rows:
cols= np.hsplit(r,5)
for box in cols:
boxes.append(box)
cv2.imshow("split",box)
return boxes
"""
def drawGrid(img,questions=5,choices=5):
secW = int(img.shape[1]/questions)
secH = int(img.shape[0]/choices)
for i in range (0,9):
pt1 = (0,secH*i)
pt2 = (img.shape[1],secH*i)
pt3 = (secW * i, 0)
pt4 = (secW*i,img.shape[0])
cv2.line(img, pt1, pt2, (255, 255, 0),2)
cv2.line(img, pt3, pt4, (255, 255, 0),2)
return img
def showAnswers(img,myIndex,grading,ans,questions=5,choices=5):
secW = int(img.shape[1]/questions)
secH = int(img.shape[0]/choices)
for x in range(0,questions):
myAns= myIndex[x]
cX = (myAns * secW) + secW // 2
cY = (x * secH) + secH // 2
if grading[x]==1:
myColor = (0,255,0)
#cv2.rectangle(img,(myAns*secW,x*secH),((myAns*secW)+secW,(x*secH)+secH),myColor,cv2.FILLED)
cv2.circle(img,(cX,cY),50,myColor,cv2.FILLED)
else:
myColor = (0,0,255)
#cv2.rectangle(img, (myAns * secW, x * secH), ((myAns * secW) + secW, (x * secH) + secH), myColor, cv2.FILLED)
cv2.circle(img, (cX, cY), 50, myColor, cv2.FILLED)
# CORRECT ANSWER
myColor = (0, 255, 0)
correctAns = ans[x]
cv2.circle(img,((correctAns * secW)+secW//2, (x * secH)+secH//2),
20,myColor,cv2.FILLED)
