Python-OpenCv-答题卡识别

 import cv2

    
 import numpy as np
    
  
    
 def cv_show(name,img):
    
     cv2.imshow(name,img)
    
     cv2.waitKey(0)
    
     cv2.destroyAllWindows()
    
  
    
 ANSWER_KEY = {0:1,1:4,2:0,3:3,4:1}
    
 img = cv2.imread("test_01.png")
    
 contours_Img = img.copy()
    
 gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)#灰度图
    
 blur = cv2.GaussianBlur(gray,(5,5),0)#高斯（平滑处理）
    
 edge = cv2.Canny(blur,75,200)#边缘检测
    
 #轮廓检测
    
 cnts,h = cv2.findContours(edge,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)#外边缘
    
 #cnts = cv2.findContours(edge,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)【0】功能一样
    
 cv2.drawContours(img,cnts,-1,(0,255,0),2)#绘制轮廓
    
 cv_show("img",img)

 def order_points(pts):

    
     rect = np.zeros((4,2),dtype="float32")
    
     s = pts.sum(axis=1)
    
     rect[0] = pts[np.argmin(s)]
    
     rect[2] = pts[np.argmax(s)]
    
     d = np.diff(pts,axis=1)
    
     rect[1]= pts[np.argmin(d)]    
    
     rect[3]= pts[np.argmax(d)]
    
     return rect
    
  
    
  
    
 def four_point_transform(img,pts):
    
     rect = order_points(pts)
    
     (tl,tr,br,bl) = rect
    
    
    
     widthA = np.sqrt(((br[0] - bl[0])**2)+((br[1] - bl[1])**2))
    
     #y2-y1的平方+x2-x1的平方再开根号
    
     widthB = np.sqrt(((tr[0] - tl[0])**2)+((tr[1] - tl[1])**2))
    
     maxWidth = max(int(widthA),int(widthB))
    
     heightA = np.sqrt(((tr[0] - br[0])**2)+((tr[1] - br[1])**2))
    
     heightB = np.sqrt(((tl[0] - bl[0])**2)+((tl[1] - bl[1])**2))  
    
     maxHeight = max(int(heightA),int(heightB))
    
     
    
     
    
     dst =np.array([[0,0],\
    
     [maxWidth - 1,0],\
    
     [maxWidth - 1,maxHeight - 1,],\
    
     [0,maxHeight - 1]],dtype = "float32")
    
    
    
     M =cv2.getPerspectiveTransform(rect,dst)
    
     warp = cv2.warpPerspective(img,M,(maxWidth,maxHeight))
    
    
    
     return warp#返回变换后的结果
    
 dotCnt = None
    
 if len(cnts)>0:
    
     cnts = sorted(cnts, key=cv2.contourArea,reverse = True)
    
     for c in cnts:
    
     peri = cv2.arcLength(c,True)
    
     approx = cv2.approxPolyDP(c,0.02*peri,True)
    
     if len(approx)==4:
    
         dotCnt=approx
    
  
    
 warp = four_point_transform(gray,dotCnt.reshape(4,2))
    
  
    
 cv_show("warp",warp)

 def sort_contours(cnts,method="left-to-right")

    
     reverse = False
    
     i = 0
    
     if method == "right-to-left" or method=="bottom-to-top":
    
     reverse = True
    
     if method == "top-to-bottom" or method=="bottom-to-top":
    
     i = 1
    
     boundingBoxes = [cv2.boundingRect(c) for c in cnts]
    
     (cnts,boundingBoxes) = zip(*sorted(zip(cnts,boundingBoxes),\
    
                                    key=lambda b:b[1][i], reverse=reverse))
    
     return cnts,boundingBoxes
    
  
    
 thresh = cv2.threshold(warp,0,255,cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
    
 thresh_contours = thresh.copy()
    
 cnts,h = cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    
  
    
 cv2.drawContours(thresh_contours,cnts,-1,(0,255,0),2)
    
 cv_show("thresh_contours",thresh_contours)

 questionCnts = []

    
  
    
 for c in cnts:
    
     (x,y,w,h) = cv2.boundingRect(c)
    
     ar = w / float(h)#宽高比
    
     if w > 20 and h > 20 and ar > 0.9 and ar < 1.1:#宽大于20个像素.....
    
     questionCnts.append(c)
    
    
    
 questionCnts = sort_contours(questionCnts, method = "top-to-bottom")
    
 cv2.drawContours(warp,questionCnts,1,(0,255,255),2)
    
 correct = 0
    
  
    
 for (q,i) in enumerate(np.arange(0,len(questionCnts),5)):   
    
     cnts = sort_contours(questionCnts[i:i + 5])[0]
    
     bubbled = None 
    
     for (j,c) in enumerate(cnts):      
    
     mask = np.zeros(thresh.shape,dtype="uint8")
    
     cv2.drawContours(mask,[c],-1,255,-1)
    
     cv_show("mask",mask)
    
    
    
     mask = cv2.bitwise_and(thresh,thresh,mask = mask)
    
     total = cv2.countNonZero(mask)#看mask里面那个是空的
    
    
    
     if bubbled is None or total > bubbled[0]:
    
         bubbled = (total,j)
    
      
    
     color = (0,0,255)
    
     k = ANSWER_KEY[q]
    
     if k == bubbled[1]:
    
     color = (0,255,0)
    
     correct += 1
    
     cv2.drawContours(warp,[cnts[k]],-1,color,3)
    
     
    
 score = (correct / 5.0)*100
    
 cv2.putText(warp,"Total:{:.2f}".format(score),(10,30),cv2.FONT_HERSHEY_SIMPLEX,\
    
         0.9,(0,0,0),2)
    
 cv_show("warp",warp)