识别二维numpy数组中的连续区域 [英] Identify contiguous regions in 2D numpy array

问题描述

我有一个很大的numpy数组，已对其应用过滤器.我想确定此蒙版数组中的连续区域.在这里，我定义了一个连续区域，如果对于任何索引(x1,y1)到任何其他索引(x2,y2)，如果在轴上沿着相等整数步长的True值路径都属于同一区域，则它们属于同一区域(对角线是有效步骤.

I have a large numpy array that I've applied a filter over. I'd like to identify the contiguous regions in this masked array. Here I'm defining a region to be contiguous if, for any index (x1,y1) to any other index (x2,y2), they belong to the same region if there is a path of True values along equal integer steps along the axes (diagonals are valid steps).

那可能不像一张简单的图片那么清晰.给定面具:

That may not be as clear as a simple picture. Given the mask:

0010000
0100000
0110000
0000011
1000010

应该确定三个区域，以使输出类似于

There should be three regions identified such that the output is something like

[ [[0,2],[1,1],[2,1],[2,2]], [[3,5],[3,6],[4,5]], [[4,0]] ]

我想使用numpy中内置的内容，而不必借助自己的 Flood Fill 算法.在文档中进行的少量研究仅显示了我要问的一维版本.

I'd like to use something built into numpy, without resorting to writing my own Flood Fill algorithm. A little bit of research in the docs only turned up a 1D version of what I'm asking.

推荐答案

您正在寻找scipy.ndimage.label，更多信息

You're looking for scipy.ndimage.label, more info here. label returns an array the same shape as the input where each "unique feature has a unique value", so if you want the indices of the features you can do something like:

labels, numL = label(array)
label_indices = [(labels == i).nonzero() for i in xrange(1, numL+1)]

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