Cacher is the code snippet organizer for pro developers

import numpy as np
import maxflow
from scipy.misc import imread
from matplotlib import pyplot as plt
import networkx as nx
import math

lumda = 1
k = 1


def create_graph():
    img = imread("result200.tif")
    row,column = img.shape
    g = maxflow.Graph[float]()
    nodeids = g.add_grid_nodes((img.shape))
　　　　　　　　# 画素値の差をノード間の重みにするのでパディング
    pad_im = np.pad(img, ((0, 0), (1, 1)), 'constant', constant_values=0)
    weights = np.zeros((img.shape))
    for i in range(img.shape[0]):
        for j in range(img.shape[1]):
            weights[i, j] = lumda * math.exp((-k) * abs(pad_im[i, j] - pad_im[i, j + 1]))
    structure = np.zeros((3, 3))
    structure[1, 2] = 1
    g.add_grid_edges(nodeids, structure=structure, weights=weights, symmetric=True)

    pad_im = np.pad(img, ((1, 1), (0, 0)), 'constant', constant_values=0)
    weights = np.zeros((img.shape))
    for i in range(img.shape[0]):
        for j in range(img.shape[1]):
            weights[i, j] = lumda * math.exp((-k) * abs(pad_im[i, j] - pad_im[i + 1, j]))
    structure = np.zeros((3, 3))
    structure[2, 1] = 1
    g.add_grid_edges(nodeids, structure=structure, weights=weights, symmetric=True)
　　　　　　　　# マスク画像をロード
    gro = imread('%05d.png' % 200)
    x, y = np.where(gro > 10) 
    for i in range(x.shape[0]): 
        if img[x[i], y[i]] >= 100: 
             temp = x[i] * column + y[i] 
             g.add_tedge(temp, 1000000000000, 0) 
             label[x[i], y[i]] = 1 
    x, y = np.where(img == 0) 
    for i in range(x.shape[0]): 
        temp = x[i] * column + y[i] 
        g.add_tedge(temp, 0, 100000) 
    return nodeids, g


if __name__ == '__main__':
    nodeids, g = create_graph()
    g.maxflow()
    sgm = g.get_grid_segments(nodeids)
    img = np.int_(np.logical_not(sgm))
    m = np.zeros((1040, 1392, 3)) 

    m[:, :, 0] = np.int_(np.logical_not(sgm)) 
    m = m.astype('uint8') * 255 
    img = cv2.imread("result200.tif") 
    dst = cv2.addWeighted(img, 0.5, m, 0.5, 0)     
    plt.imshow(dst), plt.show()