如何从蒙版中绘制正确形状的多边形？

Question

我有一个带有不同标记区域的面具，如附图所示。
用活动轮廓函数分割后，我想在活动轮廓点的合成点周围画一个多边形，但是多边形是逐行读取点，所以多边形绘制不正确，如图所示附图，多边形应该看起来更像一个圆形区域。
请问如何解决？
图片
面具
多边形

import numpy as np
from skimage.io import imread, imsave
import skimage.filters as filters
from skimage.segmentation import active_contour
from scipy.sparse import csr_matrix
import matplotlib.pyplot as plt
from skimage.draw import polygon
#---------------------------------
img  = imread('image.jpg')
mask = imread('label.png')

def activeContour(img, mask, alpha=0.015, beta=10, gamma=0.001, iterations=500, max_step=0.5):
    lb_list = np.unique(mask)
    Result = np.zeros_like(img)
    for lb in lb_list:
        if(lb != 0):
            s = np.where(mask == lb)
            r = s[0].astype(np.uint8)
            c = s[1].astype(np.uint8)
            init = np.array([r, c]).T
            #-------PreProcessing----------------------------
            img2 = filters.gaussian(img, 3)
            #------- Active Contour  ------------------------
            snake = active_contour(img2, init, alpha=alpha, beta=beta, gamma=gamma, coordinates='rc',
             max_px_move=max_step, max_iterations=iterations)
            #------------------------------------------------
            vals = lb*np.ones_like(snake[:, 0],dtype=np.uint8)
            label = csr_matrix((vals, (snake[:, 1].astype(np.uint8), snake[:, 0].astype(np.uint8))), shape=(img.shape[0], img.shape[1])).toarray()
            Result = Result + label
    return Result


res = activeContour(img, mask, alpha=0, beta= 10, gamma= 0.0000001)
labels = np.unique(res)
ctr = 25
for label in labels:
    if label != 0:
        img = np.zeros_like(img)
        s = np.where(res == label)
        r = s[0].astype(np.uint8)
        c = s[1].astype(np.uint8)
        rr, cc = polygon(r, c)
        img[rr, cc] = 2*ctr
        plt.imshow(img, cmap='gray')
        plt.title('%d'%label)
        plt.axis('off')
        plt.show()
        ctr+=1

Answer 1

感谢Juan for his help, the theoritical part of this answer is here 并且实施失败。

import numpy as np

def sortVertices(array):
    s = np.where(array != 0)
    yr = s[0].astype(np.uint8)
    xc = s[1].astype(np.uint8)
    center_xc = np.sum(xc)/xc.shape 
    center_yr = np.sum(yr)/yr.shape 
    theta = np.arctan2(yr-center_yr, xc-center_xc) * 180 / np.pi
    indices = np.argsort(theta)
    x = xc[indices]
    y = yr[indices]
    return x, y

如何从蒙版中绘制正确形状的多边形？

How can I draw a polygon in the right shape from a mask?

polygon

image-processing

draw

python-3.x

scikit-image