Question

我想在python中从图像（大量顶点...大约> 10 ^ 5个顶点）创建一个大的加权邻接矩阵。相邻像素之间的权重是颜色梯度（我会照顾这个）。通过迭代像素来做这件事非常慢......需要4分钟。 :-(是否有任何库可以在合理的时间内很好地完成这项工作？

以下是我的代码运行速度非常慢：

def indToCoord(ind, w, h):
    x = ind % w
    y = (ind - x)/h
    return (x,y)

def isAdj(p1, p2, im):
    adj = []
    w, h = im.size
    x1, y1 = p1
    x2, y2 = p2
    if (x1, y1) == (x2, y2):
        return 0
    elif abs(x1 - x2) > 1:
        return 0
    elif abs(y1 - y2) > 1:
        return 0
    elif abs(x1 - x2) + abs(y1 - y2) >= 2:
        return 0

    return util.colorGradient(im, p1, p2)

def adjForPixel(pixels, p1, im):
    return [isAdj(p1,p2,im) for p2 in pixels]

# The following is the function I use to create an Adjacency Matrix from an image
def getAdjMatrix(im):
    width, height = im.size 
    pixels = [(x,y) for x in xrange(width) for y in xrange(height)]

    pixelAdjMatr = [adjForPixel(pixels, p, im) for p in pixels]
    return pixelAdjMatr

adj_matrix = getAdjMatrix(im)

谢谢！

Answer 1

Python模块/库NetworkX具有邻接矩阵实现。它返回一个scipy矩阵

https://networkx.github.io/documentation/latest/reference/generated/networkx.linalg.graphmatrix.adjacency_matrix.html

import networkx as nx
import scipy as sp
g = nx.Graph([(1,1)])
a = nx.adjacency_matrix(g)
print a, type(a)

返回

(0, 0)  1 <class 'scipy.sparse.csr.csr_matrix'>

从python中的图像创建大的邻接矩阵

1 个答案: