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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) | |