#!/usr/bin/env python

import pylab as pl
import numpy as np
import cv2

def skeletonize(image):
    img = image
    size = np.size(img)
    skel = np.zeros(img.shape,np.uint8)

    ret,img = cv2.threshold(img,127,255,0)
    element = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))
    done = False

    img =cv2.bitwise_not(img)
    # original = img

    while( not done):
        eroded = cv2.erode(img,element)
        temp = cv2.dilate(eroded,element)
        temp = cv2.subtract(img,temp)
        skel = cv2.bitwise_or(skel,temp)
        img = eroded.copy()

        zeros = size - cv2.countNonZero(img)
        if zeros==size:
            done = True

    return skel, cv2.dilate(skel, element)

def collapse_contours(contours):
    contours = np.vstack(contours)
    contours = contours.squeeze()
    return contours

def get_rough_contour(image):
    """Return rough contour of character.
    image: Grayscale image.
    """
    skeleton, dskeleton = skeletonize(image)
    contours, hierarchy = cv2.findContours(skeleton,
                                           cv2.RETR_EXTERNAL,
                                           cv2.CHAIN_APPROX_SIMPLE)
    contour = collapse_contours(contours)
    return contour

def draw_contour(image, contour, colors=(255, 0, 0)):
    for p in contour:
        cv2.circle(image, tuple(p), 1, colors, -1)

def main():
    image = cv2.imread("s.png", 0)
    contour = get_rough_contour(image)
    # You will probably want to do some spline fitting here to
    # smooth the contour
    draw_contour(image, contour)
    pl.imshow(image, cmap=pl.cm.gray)

if __name__ == '__main__':
    main()

结果：

might wanna use from skimage.morphology import skeletonize https://scikit-image.org/docs/stable/auto_examples/edges/plot_skeleton.html

您正在寻找findcontours()函数
http://docs.opencv.org/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html?highlight=find%20contour#findcontours