段实例没有属性“ Kmeans”

Question

我有一些有关使用K-Means进行图像分割的教程，我对实例感到困惑。当我执行代码时，出现如下错误：“ AttributeError：细分实例没有属性'Kmeans”

我的代码

import cv2
import numpy as np

class Segment:
    def __init__(self,segments=5):
        #define number of segments, with default 5
        self.segments=segments
def kmeans(self,image):
       #Preprocessing step
       image=cv2.GaussianBlur(image,(7,7),0)
       vectorized=image.reshape(-1,3)
       vectorized=np.float32(vectorized)
       criteria=(cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,
              10, 1.0)
       ret,label,center=cv2.kmeans(vectorized,self.segments,None,
              criteria,10,cv2.KMEANS_RANDOM_CENTERS)
       res = center[label.flatten()]
       segmented_image = res.reshape((image.shape))
       return label.reshape((image.shape[0],image.shape[1])),segmented_image.astype(np.uint8)
if __name__=="__main__":
    import argparse
    import sys
    ap = argparse.ArgumentParser()
    ap.add_argument("-i", "--image", required = True,
                help = "photos/peppers.jpg")
    ap.add_argument("-n", "--segments", required = False,
               type = int,  help = "# of clusters")
    args = vars(ap.parse_args())
if len(sys.argv)==3:
      seg = Segment()
      label,result= seg.kmeans(image)
else:
    seg=Segment(args["segments"])
    label,result=seg.Kmeans(image)

def extractComponent(self,image,label_image,label):
       component=np.zeros(image.shape,np.uint8)
       component[label_image==label]=image[label_image==label]
       return component

extracted=seg.extractComponent(image,label,2)
cv2.imshow("extracted",extracted)
cv2.waitKey(0)

此行有误 label,result=seg.Kmeans(image)