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我需要计算长轴长度、短轴长度和偏心率。我正在使用 fitEllipse() 进行计算。但是某些对象的长轴长度给出的值高于高度值。我找不到如何解决这个问题。

这是代码：

    import cv2
    import numpy as np
    
    img = cv2.imread('Resources/son1.png')
    
    #input and output image
    def getContours(img,imgContour):
        #Find contours and set contour retrivial mode
        contours, hierarchy = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    
    
        #cnt is the one of the contours for every object in image
        for cnt in contours:
    
            # Contour for shape and I find area and length using this contour
            cv2.drawContours(imgContour, cnt,-1, (0, 255, 0), 1)

BoundingBox(Rectangle)：给出边界框参数 => (x,y,width,height)

            x, y, w, h = cv2.boundingRect(cnt)
            img = cv2.rectangle(imgContour,(x, y),(x+w, y+h),(0,255,0),2)
            print("bounding_box(x,y,w,h):", x, y, w, h)
    
    
            #W: and H: texts (Length)
            cv2.putText(imgContour, "w={},h={}".format(w,h), (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0),1,16)
    
            # give us specific contour (cnt) area
            area = cv2.contourArea(cnt)
    
            # Area text
            cv2.putText(imgContour, "Area: " + str(int(area)), (x + w + 20, y + 45), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
                        (255, 0, 0), 1, 16)
    
            # # #Center of objects in picture
            #
            # M = cv2.moments(cnt)
            # print(M)
            # centx = int(M['m10'] / M['m00'])
            # centy = int(M['m01'] / M['m00'])
            #
            # print(centx,centy)

长轴长度、短轴长度、偏心率

            (x,y), (minorAxisLength, majorAxisLength), angle = cv2.fitEllipse(cnt)
            ellipse = cv2.fitEllipse(cnt)
            cv2.ellipse(img,ellipse,(0, 0, 255), 2)
    
            #semi-major and semi-minor
            a = majorAxisLength / 2
            b = minorAxisLength / 2
    
            #Formula of eccentricity is :
            Eccentricity = round(np.sqrt(pow(a, 2) - pow(b, 2))/a, 2)
    
            x = int(x + w / 2) + 1
            y = int(y + h / 2) + 1
    
            cv2.putText(imgContour, 'Minor ='+str(round(minorAxisLength, 2)), (x+10, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1,16)
            cv2.putText(imgContour, 'Major ='+str(round(majorAxisLength, 2)), (x+10, y+20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1, 16)
            cv2.putText(imgContour, 'Eccentricity ='+str(round(Eccentricity, 3)), (x+10, y+40), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1, 16)
    
    
    imgContour = img.copy()
    imgBlur = cv2.GaussianBlur(img, (7, 7),1)
    imgGray = cv2.cvtColor(imgBlur, cv2.COLOR_BGR2GRAY)
    ImgThresh = cv2.threshold(imgGray, 100 , 255, cv2.THRESH_BINARY)[1]
    imgCanny = cv2.Canny(imgGray,50,50)
    getContours(imgCanny,imgContour)
    
    cv2.imshow("Original Image", img)
    cv2.imshow("Canny", imgCanny)
    cv2.imshow("Contour", imgContour)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

我添加了原始图像： 在此处输入图像描述

这是结果图像： 在此处输入图像描述

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