使用 Python OpenCV 检测图像中的所有圆圈(光学标记识别)

Detect All Circles in an image (Optical Mark Recognition) using Python OpenCV

我需要为我的高中假期项目制作一个使用 Python 的 OMR 检测系统(如果足够可靠,学校可能会在某种程度上使用它),我已经做了很多对它的研究,并尝试了从轮廓到模板匹配的一切,我觉得模板匹配工作正常但它只能检测 OMR sheet 中的许多圆圈中的一个圆圈,有人能帮我弄清楚我是怎么做的吗可以在omr sheet及其各自的坐标中检测到多个(所有)圆圈(无论它们是否冒泡),这对我来说就足够了。

我尝试过的:

import numpy as np
import cv2

img = cv2.resize(cv2.imread('assets/omr_match1.jpg', 0), (0, 0), fx=0.2, fy=0.5)
template = cv2.resize(cv2.imread('assets/circle.jpg', 0), (0, 0), fx=0.2, fy=0.5)
h, w = template.shape

methods = [cv2.TM_CCOEFF, cv2.TM_CCOEFF_NORMED, cv2.TM_CCORR,
            cv2.TM_CCORR_NORMED, cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]

methods=methods[0] 
# This is one among the above which works perfectly

for method in methods:
    img2 = img.copy()

    result = cv2.matchTemplate(img2, template, method)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
    if method in [cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]:
        location = min_loc
    else:
        location = max_loc

    bottom_right = (location[0] + w, location[1] + h)
    cv2.rectangle(img2, location,bottom_right, 0, 1)
    cv2.imshow('Match', img2)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

#circle.jpg

见上图,只标记了一个随机圆圈,而不是所有圆圈。

开始吧:

import cv2
import numpy as np
from matplotlib import pyplot as plt


img = cv2.imread('/path/tabela_circle.jpg', 0)

template = cv2.imread('/path/circle.jpg', 0)
h, w = template.shape

res = cv2.matchTemplate(img,template,cv2.TM_CCOEFF_NORMED)
threshold = 0.8
loc = np.where( res >= threshold)
for pt in zip(*loc[::-1]):
    cv2.rectangle(img, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)

cv2.imwrite('res.png',img)

也可以只检测答案: