Recruitment-OMR-scanner/utils.py at main · creative-computing-society/Recruitment-OMR-scanner · GitHub

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import cv2
import numpy as np

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 rectCountour(coutors):
    rectCon=[]
    for i in coutors:
        area=cv2.contourArea(i)
        #print("Area",area)
        if area>50:
            peri=cv2.arcLength(i,True)
            approx = cv2.approxPolyDP(i,0.02*peri,True)
            #print("Corner points: ",len(approx))
            if len(approx)==4:
                rectCon.append(i)
    rectCon = sorted(rectCon,key=cv2.contourArea,reverse=True)
    return rectCon

def getCornerPoints(cont):
    peri = cv2.arcLength(cont, True)
    approx = cv2.approxPolyDP(cont, 0.02 * peri, True)
    return approx

def reorder(myPoints):
    myPoints = myPoints.reshape((4,2))
    myPointsNew = np.zeros((4,1,2),np.int32)
    #Array has 4 rows and 2 columns
    add = myPoints.sum(1)
    #print(myPoints)
    #print(add)
    #The smallest value would be the start
    myPointsNew[0] = myPoints[np.argmin(add)]
    myPointsNew[3]= myPoints[np.argmax(add)]
    diff = np.diff(myPoints,axis=1)
    myPointsNew[1]=myPoints[np.argmin(diff)]
    myPointsNew[2]=myPoints[np.argmax(diff)]

    return myPointsNew

def splitBoxes(img):
    rows = np.vsplit(img,20)
    boxes=[]
    for r in rows:
        cols = np.hsplit(r,4)
        for box in cols:
            boxes.append(box)
            #cv2.imshow("Split",box) total boxes

    return boxes

def splitBoxes1(img):
    rows1 = np.hsplit(img,9)
    boxes1=[]
    for r in rows1:
        cols1 = np.vsplit(r,10)
        for box in cols1:
            boxes1.append(box)
            #cv2.imshow("Split",box) total boxes

    return boxes1