我试图分离虹膜，但是瞳孔被分离成一个圆圈，我如何改变它，使它包围虹膜而不是瞳孔。我还使用股票jpeg文件。我尝试了很多东西，但我对opencv和图像处理非常陌生，所以任何帮助都是令人钦佩的。在一些图片中，它在非常奇怪的地方画了一个圆圈，这让我觉得代码中还有其他东西。

# 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, 255), -1)

    def detect_pupil (self):
        dst = cv2.fastNlMeansDenoisingColored(self._img,None,10,10,7,21)
        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,210,255,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,y),radius = cv2.minEnclosingCircle(final_cnt)
        center = (int(x),int(y))
        radius = int(radius)
        cv2.circle(self._img,center,radius,(255,0,0),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()