如何在镂空迷宫图像中找到最短路径？

Question

我正在使用图像处理和NetworkX搜索算法进行迷宫解决,需要找到这些线上两点之间的最短连接路径.

#Solving Maze Using Image Processing and NetWorkx search



    #Open Maze image
    img = cv2.imread("C:/Users/Dell/HandMadeMaze1.jpg")
    kernel = np.ones((1,1),np.uint8)

    #Convert to GrayScaledImage
    grayscaled = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    #B?naryThreshold + OtsuThreshold + BinaryThreshold
    retval, threshold = cv2.threshold(grayscaled, 10, 255, cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
    retval, threshold2 = cv2.threshold(threshold, 10, 255, cv2.THRESH_BINARY_INV)
    threshold2[threshold2 == 255] = 1

    #Skeletonize the Thresholded Image
    skel = skeletonize(threshold2)

    #Build Graph from skeleton
    graph = sknw.build_sknw(skel, multi=False)
    G = nx.Graph(graph)
    plt.imshow(img, cmap='gray')

    #Draw Edges by 'pts'
    for (s,e) in graph.edges():
        ps = graph[s][e]['pts']
        plt.plot(ps[:,1], ps[:,0], 'red')

    #Draw Node by 'o'   
    node, nodes = graph.node, graph.nodes()
    ps = np.array([node[i]['o'] for i in nodes])
    plt.plot(ps[:,1], ps[:,0], 'g.')
    plt.title('Skeletonize')
    plt.savefig('Overlay_Maze.jpg')
    plt.show()

    G = nx.path_graph(len(ps))
    G = nx.karate_club_graph()
    pos = nx.spring_layout(G)
    nx.draw(G,pos,node_color='b')

当我运行上面的代码时,我得到以下输出.

原始输入迷宫图像:

-

处理完图像后:

-

XY坐标上的节点:

-

路径信息:

我可以成功执行图像处理操作,但搜索算法可以找到两个节点之间最短的鸟类飞行距离.我想找到沿着Skeleton的最短路径.

当我在这个github上工作时,repo 显示我使用NetworkX库解决了这个问题,但我无法解决它,因为它没有给出任何细节.

如何使用图像处理和任何搜索算法找到迷宫图像骨架的最短路径？

提前致谢.

Answer 1

这是因为您在此处重新分配了对骨架图的引用

G = nx.path_graph(len(ps))
G = nx.karate_club_graph()