OMR_Grading_App / utlis.py
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Rename utils.py to utlis.py
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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][c])*13+27,30+eachImgHeight*d),(255,255,255),cv2.FILLED)
cv2.putText(ver,lables[d][c],(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]
return myPointsNew
def rectContour(contours):
rectCon = []
max_area = 0
for i in contours:
area = cv2.contourArea(i)
if area > 50:
peri = cv2.arcLength(i, True)
approx = cv2.approxPolyDP(i, 0.02 * peri, True)
if len(approx) == 4:
rectCon.append(i)
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,5)
boxes=[]
for r in rows:
cols= np.hsplit(r,5)
for box in cols:
boxes.append(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)