OMR Reader using Python

Author: koshygeoji

Category.py

@@ -0,0 +1,37 @@
+import cv2
+import numpy as np
+
+def category(cat):
+    cate=""
+    orginal=np.uint8(cat)
+    orginal=cv2.resize(orginal,(202,626))
+    c = ["GEN","OBC1","OBC2","SC","ST","PH"]
+
+    h,w = orginal.shape
+    crop= orginal[140:h-5,140:w-5]
+#    cv2.imshow('l',crop)
+
+    h1,w1 = crop.shape
+    th, im_th = cv2.threshold(crop,127,255,0)
+
+    im_th=~im_th
+    kernel = np.ones((5,5), np.uint8) 
+    binary = cv2.erode(im_th, kernel, iterations=2) 
+    
+    count = 0
+    for x in range(0, h1,np.uint(np.floor(h1/6))):
+           
+        if (x+int(h1/6) > h1):
+               break
+        row = binary[x:x+int(h1/6),:] 
+        visr=crop[x:x+int(h1/6),:] 
+        count+=1
+    #    cv2.imshow("Foreground", visr)
+    #    cv2.waitKey(0)
+        _,cnts, _ = cv2.findContours(row, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)  
+        
+        if len(cnts) == 1: 
+            cate=c[count-1]               
+    
+
+    return cate

Center_code.py

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+import cv2
+import numpy as np
+
+def code(center):
+    
+    orginal=np.uint8(center)
+    orginal=cv2.resize(orginal,(267,583))
+
+    h,w = orginal.shape
+    crop= orginal[158:h-5,18:w-18]
+    
+    
+    th, im_th = cv2.threshold(crop,127,255,0)
+    im_th=~im_th
+    kernel = np.ones((5,5), np.uint8) 
+    binary = cv2.erode(im_th, kernel, iterations=2) 
+    
+    h1,w1 = crop.shape
+    code = []
+    for y in range(0, w1,np.uint(np.floor(w1/4))): 
+        if (y +int(w1/4) > w1):
+            break 
+        column = binary[0:h1, y: y +int(w1/4)]
+        visc=crop[0:h1, y: y +int(w1/4)]
+        count=0          
+        for x in range(0, h1,np.uint(np.floor(h1/10))):
+               
+            if (x+int(h1/10) > h1):
+                   break
+            row = column[x:x+int(h1/10),:] 
+            visr=visc[x:x+int(h1/10),:] 
+            count+=1
+            
+    #        cv2.imshow("Foreground", visr)
+    #        cv2.waitKey(0)
+            
+            _,cnts, _ = cv2.findContours(row, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)       
+            if len(cnts) == 1: 
+                code.append(str(count))
+    if len(code)>0:
+        code=['0' if x == '10' else x for x in code]
+        code=''.join(code)
+        code=int(code)
+    else:
+        code=""
+    return code
+
+            

Input/10.jpg

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+# -*- coding: utf-8 -*-
+"""
+Created on Tue Aug 25 23:40:17 2020
+
+@author: Koshy G
+"""
+
+
+import os
+import csv
+import Question_recog
+import segments
+import Name_recog
+import Mobile_recog
+import Roll_no
+import Center_code
+import Category
+
+
+
+In_path ="Input/"
+Score_path = "Score/"
+valid_images = [".jpg",".gif",".png",".tga"]
+data=[]
+data.append(['Centre Code','Roll No','Name','Category','Mobile Number','question'])
+
+
+
+#
+i=0
+for s in os.listdir(In_path):
+    
+        print(i)
+        i=i+1
+        ext = os.path.splitext(s)[1]
+        if ext.lower() not in valid_images:
+            continue
+        input_img=os.path.join(In_path,s)
+
+        q1,q2,q3,q4,q5,name,mob,roll,center,cat = segments.segment(input_img)
+        quest1=Question_recog.question(q1)
+        quest2=Question_recog.question(q2)
+        quest3=Question_recog.question(q3)
+        quest4=Question_recog.question(q4)
+        quest5=Question_recog.question(q5)
+        quest=quest1+quest2+quest3+quest4+quest5
+        name = Name_recog.nameread(name)
+        mobile = Mobile_recog.mobile(mob)
+        rollno = Roll_no.roll_no(roll)
+        code=Center_code.code(center)
+        cate = Category.category(cat)
+        
+        data.append([code,rollno,name,cate,mobile,quest])
+       
+        
+       
+with open('output.csv', 'w') as writeFile:
+    writer = csv.writer(writeFile)
+    writer.writerows(data)
+            
+       

Input/11.jpg

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+import cv2
+import numpy as np
+
+def mobile(mob):
+
+    orginal=np.uint8(mob)
+    orginal=cv2.resize(orginal,(555,629))
+#    cv2.imshow('a',orginal)
+        
+    h,w = orginal.shape
+    crop= orginal[200:h-9,15:w-15]
+    h1,w1 = crop.shape
+    th, im_th0 = cv2.threshold(crop,220,255,0)
+    im_th0=~im_th0
+    kernel1= np.ones((5,30), np.uint8)  
+    im_th0=cv2.morphologyEx(im_th0, cv2.MORPH_CLOSE, kernel1)
+    
+    kernel1=np.ones((5,30), np.uint8) 
+    im_th0 = cv2.erode(im_th0, kernel1, iterations=1) 
+    
+    kernel1=np.ones((5,w1), np.uint8) 
+    im_th0=cv2.morphologyEx(im_th0, cv2.MORPH_OPEN, kernel1)
+    
+    _,cnts0, _ = cv2.findContours(im_th0, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+    if len(cnts0)==9:
+        crop=orginal[150:h-9,15:w-15]
+        h1,w1=crop.shape
+    
+    th, im_th = cv2.threshold(crop,127,255,0)
+    im_th=~im_th
+    kernel = np.ones((5,5), np.uint8) 
+    number=[]
+    binary = cv2.erode(im_th, kernel, iterations=2) 
+#    cv2.imshow('a',binary)
+#    cv2.waitKey(0)
+    
+    for y in range(0, w1,np.uint(np.floor(w1/10))):
+        
+        if (y +int(w1/10) > w1):
+            break 
+        column = binary[0:h1, y: y +int(w1/10)]
+#        cv2.imshow('aa',column)
+#        cv2.waitKey(0)
+#        visc=crop[0:h1, y: y +int(w1/10)]
+        countn = 0 
+        for x in range(0, h1,np.uint(np.floor(h1/10))):
+           
+            if (x+int(h1/10) > h1):
+                   break
+            row = column[x:x+int(h1/10),:] 
+#            visr=visc[x:x+int(h1/10),:] 
+            countn+=1
+            
+#            cv2.imshow("Foreground", row)
+#            cv2.waitKey(0)
+            
+            _,cnts, _ = cv2.findContours(row, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+            if len(cnts) > 0: 
+                number.append(str(countn))
+    number=['0' if x == '10' else x for x in number]
+    number=''.join(number)
+
+    if len(number)>0:
+        number=number
+    else:
+        number=""
+#    print(number)
+    return number
+
+        
+
+