Opencv 检测瞳孔，但我试图从在线库存图片中检测虹膜

如何解决Opencv 检测瞳孔，但我试图从在线库存图片中检测虹膜

output input 我正在尝试隔离虹膜，但瞳孔被隔离成一个圆圈，我该如何更改它使其围绕虹膜而不是瞳孔。我也使用股票 jpeg 文件。我尝试了很多东西，但我对 opencv 和图像处理真的很陌生，所以任何帮助都会令人钦佩。此外，在某些图像中，它在非常奇怪的地方形成了一个圆圈，这让我觉得代码还有其他问题。

#import numpy
import cv2
import numpy as np

class pupil_detection():
    def __init__(self,image_path):
        '''
        initialize the class and set the class attributes
        '''
        self._img = None
        self._img_path = image_path
        self._pupil = None
        self._centroid = None

    def load_image(self):
        '''
        load the image based on the path passed to the class
        it should use the method cv2.imread to load the image
        it should also detect if the file exists
        '''
        self._img = cv2.imread(self._img_path)
        #self._img = cv2.resize(self._img,(300,300))
        # If the image doesn't exists or is not valid then imread returns None
        if type(self._img) == None:
            return False
        else:
            return True

    def show_image (self,img):
        cv2.imshow("Result",img)
        cv2.waitKey(0)

    def centroid (self):
        # convert image to grayscale image
        gray_image = cv2.cvtColor(self._img,cv2.COLOR_BGR2GRAY)
        # convert the grayscale image to binary image
        ret,thresh = cv2.threshold(gray_image,127,255,0)
        # calculate moments of binary image
        M = cv2.moments(thresh)
        # calculate x,y coordinate of center
        cX = int(M["m10"] / M["m00"])
        cY = int(M["m01"] / M["m00"])
        self._centroid = (cX,cY)
        cv2.circle(self._img,(cX,cY),5,(255,255),-1)

    def detect_pupil (self):
        dst = cv2.fastNlMeansDenoisingColored(self._img,None,10,7,21)
        blur = cv2.GaussianBlur(dst,(5,5),0)
        inv = cv2.bitwise_not(blur)
        thresh = cv2.cvtColor(inv,cv2.COLOR_BGR2GRAY)
        kernel = np.ones((2,2),np.uint8)
        erosion = cv2.erode(thresh,kernel,iterations = 1)
        ret,thresh1 = cv2.threshold(erosion,210,cv2.THRESH_BINARY)
        cnts,hierarchy = cv2.findContours(thresh1,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
        flag = 10000
        final_cnt = None
        for cnt in cnts:
            (x,y),radius = cv2.minenclosingCircle(cnt)
            distance = abs(self._centroid[0]-x)+abs(self._centroid[1]-y)
            if distance < flag :
                flag = distance
                final_cnt = cnt
            else:
                continue
        (x,radius = cv2.minenclosingCircle(final_cnt)
        center = (int(x),int(y))
        radius = int(radius)
        cv2.circle(self._img,center,radius,0),2)

        self._pupil = (center[0],center[1],radius)
        self.show_image(self._img)

    def start_detection(self):
        if(self.load_image()):
            self.centroid()
            self.detect_pupil()
        else:
            print('Image file "' + self._img_path + '" Could not be loaded.')

id = pupil_detection(r'rightlook2.jpg')
id.start_detection()