python cv2 答题卡检测

import tkinter
import cv2 #
from PIL import Image,ImageTk
from tkinter import filedialog #打开文件需要
import imutils
import os
import numpy
root = tkinter.Tk()
root.geometry('1000x700')
root.title('答题卡识别系统')
Label_a = tkinter.Label(root)
Label_a.place(x=0,y=0)
Label_b = tkinter.Label(root)
Label_b.place(x=510,y=20)
Label_c = tkinter.Label(root)
Label_c.place(x=510, y=270)
Label_d = tkinter.Label(root)
Label_d.place(x=650,y=500)
def enter():
    filename = tkinter.filedialog.askopenfilename()  # 打开文件夹
    #保存图片，方便识别
    photo = Image.open(filename)
    photo.save('img.jpg')
    #展示图片
    photo = Image.open(filename).resize((500, 500))  # 打开图片
    photo = ImageTk.PhotoImage(photo)
    Label_a.config(image=photo)
    Label_a.image=photo
    #将框选内容清除，以便于下张图显示清除，否则会造成显示错误
    Range.clear()
Range = []
catch_Answer = []
def rectangle():
    img = cv2.imread('img.jpg')
    y,x,_ = img.shape
    print('原图像大小：',x,y)
    if x<=500:
        img = cv2.resize(img,(int(x*2),int(y*2))) #将图片宽高各除与2
    elif 1000<= x:
        img = cv2.resize(img,(int(x/2),int(y/2))) #将图片宽高各除与2
    x, y, w, h = cv2.selectROI(img, showCrosshair=True, fromCenter=False)
    screenshot = img[y:y + h, x:x + w]
    print('截图区域大小，判断条件：',x,y,w,h)
    #展示图
    screenshot = Image.fromarray(screenshot)
    screenshot = ImageTk.PhotoImage(image=screenshot)
    Label_b.config(image=screenshot)
    Label_b.image = screenshot
    # 截屏区域
    if x<=30:
        x1, x2, y1, y2 = x * 2.5, (x + w) * 2.5, y * 2.5, (y + h) * 2.5
    elif 30 < x <35:
        x1, x2, y1, y2 = x * 5, (x + w) * 5, y * 5, (y + h) * 5
    elif 35 <= x:
        x1, x2, y1, y2 = x * 10, (x + w) * 10, y * 10, (y + h) * 10
    Range.append((x1, x2, y1, y2)) #360 5080 3640 5940
    #调用识别模块
    discren('img.jpg',0)
Answer = []
def discren(path,name):
    #cv2读取
    # image = cv2.imread(path)
    # ay0,ax0,_ = image.shape
    #PIL——Image 读取
    image = Image.open(path)
    ax0,ay0 = image.size
    #转换成cv2可以识别的图
    image = numpy.asarray(image)
    # 将图像扩大五倍
    ax,ay = ax0*5,ay0*5
    # 转换为灰度图像
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    # 高斯滤波
    blurred = cv2.GaussianBlur(gray, (3, 3), 0)
    # 自适应二值化方法
    blurred = cv2.adaptiveThreshold(blurred, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 51, 2)
    # 重塑可能用到的图像
    thresh = cv2.resize(blurred, (ax, ay), cv2.INTER_LANCZOS4)
    fImage = cv2.resize(image, (ax, ay), cv2.INTER_LANCZOS4)
    # 均值滤波
    ChQImg = cv2.blur(thresh, (40, 40))
    # 二进制二值化
    ChQImg = cv2.threshold(ChQImg, 30, 225, cv2.THRESH_BINARY)[1]
    # 在二值图像中查找轮廓
    cnts = cv2.findContours(ChQImg, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    # 用边缘检测绘制
    cnts = cnts[1] if imutils.is_cv3() else cnts[0]
    x1,x2,y1,y2 = int(Range[0][0]),int(Range[0][1]),int(Range[0][2]),int(Range[0][3])
    for c in cnts:
        # 计算轮廓的边界框，然后利用边界框数据计算宽高比
        (x, y, w, h) = cv2.boundingRect(c)
        if (w > 75 and h > 13) and x > x1 and x < x2 and y > y1 and y < y2 :  # 原始数据： x>324 and x<4700 and y>3072 and y<5016
            M = cv2.moments(c)  # 矩形的宽高， 起点终点（划分区域）
            cX = int(M["m10"] / M["m00"])
            cY = int(M["m01"] / M["m00"])
            # 绘制中心及其轮廓
            cv2.drawContours(fImage, c, -1, (0, 0, 255), 8, lineType=0)
            cv2.circle(fImage, (cX, cY), 40, (255, 255, 255), -1)
            if name == 0 :
                # #保存题目坐标信息
                Answer.append((cX, cY))
            elif name == 1:
                #考试答案
                catch_Answer.append((cX,cY))
    #框选区域
    discren = fImage[y1:y2,x1:x2]
    y,x,_ = discren.shape
    print(y)
    print('判断显示，x:',x)
    if x <= 1000:
        discren = cv2.resize(discren, (int(x/2), int(y/1.5)))
    elif 1000 < x < 3500:
        discren = cv2.resize(discren, (int(x/5), int(y/5)))
    elif 3500 <= x:
        discren = cv2.resize(discren,(int(x/10),int(y/10)))

    #调用判断
    if Answer and catch_Answer:
        a = contrast(Answer, catch_Answer)
        cv2.circle(discren, a, 4, (255, 255, 255), -1)
        catch_Answer.clear()
    #展示图
    discren = Image.fromarray(discren)
    discren = ImageTk.PhotoImage(image=discren)
    Label_c.config(image=discren)
    Label_c.image = discren
def testing():
    # filename = tkinter.filedialog.askopenfilename()  # 打开文件夹
    # filename = filename.split('/')[::]
    # print(filename)
    path = 'D:/PyCharm Community Edition 2021.1.3/项目/答题卡项目/img'
    paths = os.listdir(path)
    for path in paths:
        print('./img/'+path)
        discren('./img/'+path,1)
def contrast(Answer,catch_Answer):
    a = 0
    for i in range(len(Answer)):
        if catch_Answer[i][0] - 5 <= Answer[i][0] <= catch_Answer[i][0] + 5 and catch_Answer[i][1] - 3 <= Answer[i][1] <= catch_Answer[i][1] + 3:
            a += 1
        else:
            if catch_Answer[i] in Answer:
                a += 1
            else:
                print(Answer[i], catch_Answer[i])
                return catch_Answer[i]
    # print('一共{}道题，XX答对{}，得分{}'.format(int(len(Answer)), a, a))
    Label_d['text'] = '一共{}道题，XX答对{}，得分{}'.format(int(len(Answer)), a, a)
tkinter.Label(root,text='框选区域').place(x=730,y=0)
tkinter.Label(root,text='识别结果').place(x=730,y=250)
tkinter.Button(root,text='答题卡模板',command=lambda:enter()).place(x=50,y=500)
tkinter.Button(root,text='框选区域',command=lambda:rectangle()).place(x=200,y=500)
tkinter.Button(root,text='识别的答题卡',command=lambda:testing()).place(x=350,y=500)
root.mainloop()